Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: GENOMIC ANALYSIS OF VARIABILITY IN DELTA-TOXIN LEVELS BETWEEN STAPHYLOCOCCUS AUREUS STRAINS
Review round: 1
Reviewer: 3

Output:
Basic reporting: No comment.
Experimental design: The authors do define the research question well, but the methods require additional detail in several key places to allow for replication.
Validity of the findings: Not all underlying data is provided. The authors should link the sequence data to the delta-toxin production levels.
Additional comments: The authors present an interesting manuscript, performing multiple GWAS analyses to attempt to elucidate the genetic loci involved in delta toxin production in S. aureus. However, the paper appears to lack detail in several key areas. In addition, some of the analyses involve the selection of arbitrary cutoff values, that will require either further justification, or investigation into the effect of adjusting these values. Lastly, while the authors do publicly release the sequence data underpinning the paper, there appears to be no way to link this back to the toxin-production values, and so no way to verify or repeat the authors’ analysis.

Major Comments
Line 121: “Whole-genome shotgun sequencing”. This section requires more detail. The authors state Illumina chemistry was used, was this v2 or v3? Paired-end sequencing was performed, but what length reads? Was single or dual indexing performed?

Line 124: “Raw read data…” Were a minimum number of reads required for each strain, to be included in the study? If so, were additional sequencing runs performed? Or were strains simply excluded? Some of the strains listed in the SRA project accession number have a very low number of bases, e.g. NRS109 has only 12.7M bases (spread across two sequencing runs), NRS168 has only 7.7M bases (spread across two sequencing runs), while others have upwards of 400M bases. Also, none of the strains listed under this SRA project accession number are stated to have been sequenced using Illumina HiSeq (all are MiSeq), but the authors state both MiSeq and HiSeq was used.

Lines 125-126: “data were deposited in the NCBI Short Read Archive under project accession no. PRJNA289526.0”. Was unable to access this to verify (can find them without the “.0”). Does the publication or SRA project include any information that would link the raw sequence data to either the binary high/low phenotypes of toxin production, or the actual toxin production levels, so that others can attempt to replicate the analysis? I couldn’t find that information anywhere. This would be an important point to allow replication of experiments – just release of sequencing data is not sufficient.

Line 130: “Read trimming to eliminate Illumina adapters and for quality”. What parameters were used for trimming based on quality?

Lines 130-131: “Read errors and de novo genome assembly was performed”. What does read errors was performed mean? Were any parameters required to be met to keep an assembled genome (minimum N50? No. of contigs? Size of genome?).

Line 164: The authors used an “arbritary cutoff of 20,000” for determining binary Low/High of toxin production. What effect does varying this value have? For example, what if the median value of 8295 units was used?

Lines 193-194: “treeWAS was run with three unrooted trees”. But two of the trees the authors then describe are, by their own description, rooted.

Lines 235-236: “Strains used in the GWAS are split among the training and validation set”. Beyond the 70%/30%  split, how was this performed? Randomly? Did you force each set to contain a certain number of low/high toxin producers? Did each set contain representation across the clonal complexes, or at least the two main S. aureus groups?

Lines 332-333: “Using a ranked phenotype, genes common to all three analyses were fadD, vraD, degA, gdpP, ggt, opcR, rebM, thiD, and three uncharacterized proteins”. Table S1 also lists sufB for treeWAS? Was this not common to all three analyses? gdpP, opcR and rebM are not listed in Table S1. Do these only have the protein accession number/description? They should be labelled if being referred to specifically.

Minor Comments
Line 55: “CC30 had significantly lower levels of and toxin production”. Do you need the ‘and’ there?

Lines 134-135: “Agr type was determined using BLAST”. Using nucleotide or protein sequences? What coverage and identity cutoff values were used?

Line 143: “and to obtain a downsized core genome alignment of 42,406 bp” Is this just SNPs, or does it contain invariant data also (checking as you don’t include ‘I’ in the GTRGAMMA model for RAxML). If it does include invariant data, how many SNPs were there? Were gaps allowed in the alignment?

Line 144: What version of RAxML?

Lines 250-251: “All transposon mutants were… confirmed by PCR”. It might be nice to include a table of the primers in the supplementary data.

Lines 252-253: “Complementation was performed by cloning PCR fragments containing the USA300 genes in to the pOS1-Plgt vector and transforming back into the mutant strains”. Again, more detail is required here. Primers for PCR fragments? Conditions for transformation?

Line 296: Agr types: “NA:3”. The authors could comment on these. What does N/A mean here? Was agrD missing? Hybrid? Novel? If missing, was it because it was at the end of a contig? Or no BLAST match due to not meeting cutoff parameters for identity?

Line 297: Kruskal-Wallis, not “Kruskal-Wllis”.

Line 316-316: “which gave a set of 87 strains in the “low” toxin and 19 in the high toxin category”. That’s only 106 strains? There were 124 in total (although line 141 states 125 strains), so what happened to the other 18?

Line 369: “Of the eleven mutants tested, transposons in hemL, carA, glpD, isdC, thiD, and agrA significantly reduced δ-toxin production”. Discounting the positive control (agrA), the remaining five genes are fairly evenly split from across the GWAS methods (two detected using BUGWAS, two detected using Seer and one detected using TreeWAS). Might be worth commenting on in the discussion?

Lines 402-403: “while CC45 strains, which are high producers are associated with moderately severe disease”. It was unclear as to whether the authors meant severe disease in general, or for cases of AD.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: GENOMIC ANALYSIS OF VARIABILITY IN DELTA-TOXIN LEVELS BETWEEN STAPHYLOCOCCUS AUREUS STRAINS
Review round: 2
Reviewer: 1

Output:
Basic reporting: No comment
Experimental design: No comment
Validity of the findings: No comment
Additional comments: The manuscript describes an analysis of delta-toxin levels in different Staphylococcus aureus strains isolated from 9 countries and a number of different infections between 1935 and 2003 requested from the Network on Antimicrobial Resistance in Staphylococcus aureus (NARSA) biobank. The group studied the delta toxin of S. aureus because it has been shown to be linked with atopic dermatitis and they postulated that there would be a variation in toxin production from different S. aureus strains. The group examined a set of 124 S. aureus strains which were examined using whole genome sequencing and analysed using a number of genome wide association studies for association with high levels of production and specific genes. A very diverse set of samples were examined, the multiple approaches suggested the potential association between toxicity and 45 different genes, this was examined further with machine learning models and one gene (carA) was examined further and suggested to be involved with toxin production and toxicity for Caenorhabditis elegans.

Thank you for answering the previous comments, please find some further questions below.

Questions:
•	I would like to see a paragraph at the end of the introduction outlining what the study aims to achieve as an outline before the materials and methods
•	There needs to be more explanation about the strains that you studied. As I understand, you are interested in inflammatory skin diseases such as atopic dermatitis. The strain collection you examined were very mixed in the infections they caused – ranging from bacteraemia to impetigo and surgical incision.
•	With strains from such a mixed clinical background (with some unknown) I wonder if a GWAS approach on these samples is at all likely to find associations, compared to examining one clinical infection. This needs to be outlined in your discussion where a mixture of different clinical presentations might confound your analysis and dilute any associations with skin infections.
•	The limitations of the study need to be outlined fully in your discussion

Minor comments:
•	Conclusion section in first abstract: “The amount of stationary phase production of the toxin is a strain-specific phenotype likely affected by a complex interaction of number of genes with different levels of effect” should this read “… of a number of genes with different levels of effect’
•	The wording between the first and second abstracts are not the same, for example the results in the first abstract states “… with a precision of .875 but recall of .333” and the results section in the second abstract states “with a precision of .875 and specificity of .990 but recall of .333”; please ensure that the wording is the same for both


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: GENOMIC ANALYSIS OF VARIABILITY IN DELTA-TOXIN LEVELS BETWEEN STAPHYLOCOCCUS AUREUS STRAINS
Review round: 2
Reviewer: 2

Output:
Basic reporting: No comment.
Experimental design: No comment
Validity of the findings: No comment
Additional comments: The authors present an improved version of the manuscript, having addressed all of the reviewers’ comments. I have no concerns about the new version.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: DENTAL CHARACTERS USED IN PHYLOGENETIC ANALYSES OF MAMMALS SHOW HIGHER RATES OF EVOLUTION, BUT NOT REDUCED INDEPENDENCE
Review round: 1
Reviewer: 1

Output:
Basic reporting: see general comments
Experimental design: see general comments
Validity of the findings: see general comments
Additional comments: review of Brocklehurt & Benevento MS
"Dental characters used in phylogenetic analyses of mammals show higher rates of evolution, but not reduced independence"
PeerJ
Robert J. Asher, October 2019

This is an interesting & important paper which I'd like to see published. I've made a number of comments below which I hope help the authors to improve the delivery.

I'd be delighted if the authors were to better articulate the standard by which they measure accuracy. As expressed in my comments below pertaining to lines 69-72, 81 & 124, the authors perpetuate the awful habit in the literature of confusing "molecular" with "true". What the authors really mean is "well corroborated" and they should be clear about this (see below).

Intuitively, authors who select few dental characters may be choosing those that are more obvious, less variable, & easier to code vs. authors who include many dental characters, but this study doesn't really quantify how much of the overall character sample in a given study is represented by each partition (teeth, forelimb, cranium, etc.). The intuition for mammalian teeth is that they're diagnostic at species level, easily preserved, and are only present in the mouth so are typically atomized into relatively more characters per unit volume of phenotype compared to other partitions. This study is better than most in beginning to disentangle the relevant factors, for example by by narrowing the subject of comparison and not comparing teeth to (for example) "the skeleton". One could go farther still to try and get some parity; e.g., if an ankle or astragalus were atomized like teeth (many characters in small phenotypic volume), perhaps they too exhibit the various, negative properties often claimed in the literature, although the authors understandably do not want to recode morphology from these past studies and are limited by the extent to which past authors coded characters in one region or another. Nonetheless, could the authors state for each study (Beck et al., Pattinson et al., Bi et al., etc.) what proportions of the whole dataset each partition contributes? E.g., Beck et al. 2014 (basis for Beck's 2017 study) has about 25 dental out of 258 total characters, whereas Pattinson et al. 2015 (derived originally from Seiffert 2009) has 184 dental & jaw characters out of a total of 360. Does having only 10% vs. 50% dental contribute to any of the (even small) differences in signal in terms of rate, homoplasy, etc? Relatedly I'd be interested to know if the authors believe that the studies they've cited differ in character rate, signal, etc. due to something intrinsic to each partition & taxa, or because a given study (say Bi et al. vs. Beck et al.) used different criteria to select their characters.

The essence of their results are represented by the four figures, but for most readers these will be very difficult to interpret. Each has a Y axis value, a heat-map and horizontal thickness, but it's not at all clear to me what the heat map or thickness of each graphic are supposed to represent. It would be great if the authors could explain in plain English why (for example) all partitions except dentition & skull for the Bi et al. matrix appear to have little variation in Pagel's lambda (all w/ horizontal bars at 1.0, I guess median based on line 207 but the ingredients of each figure should be clear from its caption). In addition to a fuller explanation of what these figures mean in the main text, please try to make the captions more self-contained & accessible without forcing your readers to flip back-n-forth from Methods & Results; make clear what the units are and what the various axes are (including horizontal thickness).

Also the authors do not discuss at all a key discovery dating to the 1990s, namely that for any problem of a given partition in isolation, combination across partitions ameliorates bias and can reveal hidden support (Gatesy & Baker 2005 Syst Bio; Gatesy et al. 1999 Cladistics; Thompson et al. 2012 J Zoo Sys Evol Res). A key finding of Pattinson et al. 2015 was that incomplete fossils known for characters across morphological partitions were slightly but significantly better reconstructed than similarly complete fossils known for just one or few partitions. Surely this is relevant & worth discussion in this paper, which concludes (line 343) little more than the obvious platitude that one should "be cautious of basing assumption [sic] of character quality on the results of large meta-analyses".

abstract:
line 28: "...relationships. [new sentence] HOWEVER, variation in their evolutionary modes"

line 56: "morphological data ARE..."

lines 69-72: Other papers use "morphological" vs "molecular" as misleading adjectives for what's really meant, something like "potentially biased" vs "true". Here the authors have repeated the phrase "molecular tree", as if this were synonymous with "true tree" (although in fairness they're just paraphrasing other authors). Rather than repeating this sloppiness, just use adjectives like "molecular" to describe data, not trees, as the the authors have on occasion correctly done elsewhere (e.g., lines 50-52), but not lines 120-124, 132, 134, 138, 145, 338-39.

line 81: "molecular benchmark" is better than "molecular tree", but the authors could do even better by identifying a topology that is "well corroborated", as close to "true" as the philosophers will let us write. More to the point, some molecular datasets yield demonstrably wrong topologies (e.g., "the guinea pig is not a rodent"), whereas others show extraordinary congruence with completely different bodies of phylogenetic data, from embryology to the fossil record (e.g., monophyly of Sarcopterygia, Placentalia, Primates, etc.). In order to pass judgement on a given partition, the "benchmark" the authors need is actually a well-corroborated tree, these days usually but not always based on molecular data. The term "benchmark" does not do justice to this concept so write "well-corroborated tree" (which by the way is similar to but not identical with most of the topologies figured by Meredith et al. 2011 main text AND suppdata).

line 82: Is rate homogeneity really an "assumption" of parsimony, or do you really mean a feature of data that could yield statistical inconsistency when using parsimony as an optimality criterion? Analogously MP doesn't assume that all branches are short but can still be misled by accumulations of nonhomologous similarities on long branches. Note on the flip side that probabilistic assumptions of homogenous rates for taxa & characters proportional to branch length are also susceptible to error (see Goloboff et al. 2018 Palaeontology or Smith et al. 2018 Biol Letters).

lines 91-95: I don't think this is true. Your phrase "reliable results" implies error, but noise in the form of unequal character change probabilities across characters could also result in low support or polytomies, "reliably" conveying the existence of a tough phylogenetic problem. In theory it could also end up increasing hidden support (& congruence w/ a well-corroborated tree) when combined with other partitions (cf. Gatesy & Baker 2005 Syst Bio; Gatesy et al. 1999 Cladistics; Thompson et al. 2012 J Zoo Sys Evol Res).

line 101: "...most transitions to 0" you mean "non-adjacent" state changes, right? Also it might be best to reserve the term "transition" to DNA changes within purines or pyrimidines. Just write "state change" or similar for a morph character.

line 124: Note many divergence estimates from Meredith et al. 2011 are too old and have been superceded by several other, larger datasets (e.g., Dos Reis et al. 2012, Tarver et al. 2016, Phillips & Fruciano 2018). Also more recent studies (Tarver et al. 2016, Esselstyn et al. 2017) are similarly based on more data and show some conflict w/ Meredith (tree shrews, bats, rodent root...), depending on which topology from the latter paper you're using which you've not yet made clear in this MS (e.g., Meredith et al. 2011: fig. 1 based on AAs, or the various AA vs. nucleotide alignments figured in their suppdata file). Crucially, this again underscores the importance of using a well-corroborated tree (see above), not simply one that is "molecular" (a term which spans several decades of fine to bad to awful phylogenetic estimates of various groups).

line 132: use a colon only after a complete clause, so "...clades chosen were AS FOLLOWS:"
Artiodactyla is still valid with the inclusion of whales as sister taxon to hippos, not "Cetartiodactyla" (and line 229; see Asher & Helgen 2010 BMC Evol Biol).

line 315: Jervall not "Jervell"

Figure captions:
The Y-axis "rate" in each graph ("D") is unclear to me. It's labeled as a log scale but spans a heat-map (at right) showing a non-log scale of -2 to -7. Please explain in simple terms what this means and state this in the caption (if possible) or at least refer to the main text (e.g., "... as explained in Methods"). In general the captions are not self-contained, contain acronyms that most readers won't remember ("...the ER model") and thus require flipping back-n-forth to the main text to derive meaning. Please improve.

Note Pattinson et al. is 2015, not 2005, in Fig. 3 caption.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: DENTAL CHARACTERS USED IN PHYLOGENETIC ANALYSES OF MAMMALS SHOW HIGHER RATES OF EVOLUTION, BUT NOT REDUCED INDEPENDENCE
Review round: 1
Reviewer: 2

Output:
Basic reporting: The manuscript was well written with a well laid out narrative that was clear and comprehensible. There were a few typos that I caught and have highlighted in the attached PDF. There was a place in the introduction where I felt the narrative dropped a bit (have noted in PDF) and would suggest a sentence or two to make it feel more cohesive as an introduction.
A suitable array of literature was cited, however, I found a number of issues with the references: some names were misspelled, some citations were missing from the reference list and there were numerous formatting issues/inconsistencies in the reference list. I would strongly encourage the author(s) to invest some time in setting up a reference manager – it’s a slog to set up but very much worth it in the long run.
The article is well structured, with clear aims and nice intuitive figures. The tables are a little harder to comprehend but that is the nature of the results – I appreciated the authors writing out how the values should be interpreted in some instances and would encourage them to so for all the results. It would also be good to have a few sentences in the final paragraph/summary, explicitly linking your results back to the original aims of the paper.
Experimental design: The research article submitted by Brocklehurst and Benevento falls within the aims and scope of PeerJ’s remit. It builds upon the previous study of Sansom et al. (2017) and presents novel and meaningful findings that other researchers will no doubt benefit from. The objective of the study is clearly laid out and the methods are described adequately. That said, I do believe that the methods text would benefit by being fleshed out with a more explicit rationale as to why each metric/analysis has been used, the merits and caveats of each and how the results should be interpreted. By doing so I strongly believe that this paper will be more accessible to those who are perhaps daunted by more method heavy techniques for evaluating phylogenetic datasets.
I also have some concerns regarding the choice of datasets used – namely the morphological datasets for all mammals and artiodactyls (more detailed comments in PDF). There are several published datasets that I would think are better and more suitable, however, I recognise that rerunning and rewriting the current paper may not be feasible (that decision I leave to the authors discretion). If they chose to stick with the current datasets I would suggest expanding the methods/discussion sections to justify their choice more explicitly and discuss the caveats and impacts that it might have on their findings.
Validity of the findings: I have provided more detailed comments pertaining to this section in the manuscript PDF. I have no major concerns but do think that the caveats of your study should be more clearly stated. I have also added a few thoughts and comments in the discussion that can be taken or left as you deem appropriate.
Additional comments: To Neil Brocklehurst and Gemma Benevento,
I enjoyed reviewing your manuscript titled ‘Dental characters used in phylogenetic analyses of mammals show higher rates of evolution but not reduced independence’. It is an area of research I am very interested in and your study builds nicely on the study by Sansom et al. (2017) to address the issues of partitions and biases in phylogenetic data in more detail. It is heartening to know that dental characters are not necessarily as terrible as they seem, or perhaps everything else is just as bad as teeth.... Regardless, I am looking forward to seeing it published in PeerJ soon and being made use of by the research community to improve future phylogenetic analyses.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: DENTAL CHARACTERS USED IN PHYLOGENETIC ANALYSES OF MAMMALS SHOW HIGHER RATES OF EVOLUTION, BUT NOT REDUCED INDEPENDENCE
Review round: 1
Reviewer: 3

Output:
Basic reporting: The paper is generally well-written throughout, although there are a few minor typos – I have made a few suggested corrections on the attached pdf.
Experimental design: Although the matrices have been taken from published sources, in the interests of reproducibility, I would like the matrices used for the analyses (i.e. after removing selected taxa and characters) and the trees used as “benchmarks” to be included as supplementary data (or uploaded to a repository such as Dryad). Ideally, I would also like the R scripts to be included too.

I have issues with some of the analytical decisions. In particular, I am confused why you have chosen to treat the pectoral and pelvic girdles separately from the forelimb and hindlimb respectively. As you know, the pectoral girdle provides attachment sites for major muscles of the forelimb, and there is a clear functional linkage between the two; for example, the pectoral girdle of arboreal species normally allows considerable freedom of movement at the glenoid, and rotation of the scapula, and is typically combined with adaptations of the forelimb for grasping and pronation/supination movements (see e.g. Argot 2001 – J Morph). Similar functional linkages are seen between the pelvic girdle and the hindlimb (see e.g. Argot 2002 – J Morph). It makes more sense to me to treat the forelimb as including the pectoral girdle, and the hindlimb as including the pelvic girdle. This would also give you a larger number of characters to work with when comparing between partitions. At the very least, I would like to see better justification for why you picked these partitions.
Validity of the findings: The authors engage in some speculation, backed up with relevant citations, on why they observed the patterns they did. However, I think a lot of what they found is the result of particular idiosyncrasies of the matrices they used, and so are not easily generalisable to mammals as a whole. For example, they note that the dental partition for their marsupial dataset shows a lower rate of evolution and greater non-independence (or lower independence) than the dental partitions for the other datasets. However, the dental characters in the marsupial dataset represent a smaller proportion of the total characters than the other matrices (only ~11% compared to 23% in the cetartiodactyl dataset, and 49% in the primate dataset). Furthermore, the marsupial dental characters are relatively “coarse”/high level – 9 of the 29 marsupial dental characters refer to presence or absence of particular loci, which would seem, a priori, to be evolutionarily less labile than the very detailed, “low-level” characters that are much more common in the cetartiodactyl or primate matrices (many of which refer to relatively subtle differences in cusp and crest morphology).

Similarly, the high level of non-independence of dental characters found in the marsupial matrix is likely due to the fact that there are two clades with enlarged gliriform lower incisors (caenolestids/paucituberculatans and diprotodontians), and presence of the enlarged gliriform incisors is associated with a number of additional dental changes, specifically reduction/loss of the other antemolar teeth. This is a much more likely explanation than the proposal that marsupials are somehow “constrained” dentally due to the reproductive mode. The reference to the Werdelin (1987) paper (which is missing from your reference list, incidentally) is a bit misleading, as this was a comparison between Dasyuromorphia and Carnivora only, rather than a comparison across all placentals and all marsupials.  In fact, in terms of dental morphology, the order Diprotodontia is probably more variable than most if not all placental orders – it includes forms with bunodont, lophodont and selenodont molars, extreme variation in the morphology of the premolars, and one taxon (Tarsipes) has an almost vestigial postcanine dentition.

There are issues with partitions in some of the other matrices. For example, the very high phylogenetic signal in the soft tissue partition of the primates data matrix is not a “fair”/”honest” attempt to score soft tissues across primates, but is in fact entirely weighted towards characters that support strepsirhine monophyly. Similarly, the soft tissue characters of Bi et al. were clearly chosen to simply reflect the differences in reproductive mode between placentals, marsupials and monotremes, rather than to “honestly” score soft tissue variability across mammals.

I think it would be worth investigating whether there are correlations between your results (e.g. for phylogenetic signal and rate of evolution) and the absolute number of characters in each partition, which would represent a crude measure of sampling “intensity” – I suspect that the high rates of evolution in most dental partitions (with the exception of marsupials discussed above) are because they have been sampled more “intensely” than the other partitions, and so are likely to include very minor, likely highly labile traits. In Cetartiodactyla, the difference between the forelimb (35 characters, ~6% of total) and hindlimb (61 characters, ~10% of the total) may again simply be the result of sampling intensity of the different anatomical regions: nearly 2/3 of the hindlimb characters, for example, are scored off only two bones (astragalus and calcaneus). Testing for correlations between your results and the percentage of the total number of characters each partition represents would also be worth exploring.

Another thing to think about: you carried out tests for character non-independence between pairs of characters. Would it be possible to use the results of these to filter out those characters with the greatest degree of non-independence and then repeat your analyses? How would this affect your results? It would seem, for example, more justified to compare differences in rates of evolution between partitions after removing the characters that show the greatest degree of non-independence.

In summary, I think this paper is worth publishing because it takes a novel, quantitative approach to an interesting and topical question. However, I do genuinely think that many of the differences you have observed are due to idiosyncrasies in the different morphological matrices that make it difficult to compare them “fairly”. I’m therefore not sure whether this is telling us anything about the way that morphological data performs in general. I realise that this is a bit negative, and so I would recommend looking at applying your methods to “phenomic” datasets that have made a fair attempt to score variability across different systems in mammals. One obvious candidate is the O’Leary et al. matrix, although this will undoubtedly have huge amounts of character non-independence due to the decision to score each dental locus separately. Another one that you might consider is the primate matrix of Ni et al. (2013 – Nature), or subsequent updates of this matrix – it represents a fair attempt to score variability across the entire primate skeleton and also soft tissues, and so might be worth exploring for future studies.

In the interests of openness, I would like to sign my review, and I am happy for the authors to contact me if they require clarification of any of the points I have raised.

ROBIN M. D. BECK
Lecturer in Biology
School of Environment and Life Sciences
University of Salford, Manchester M5 4WT
T: +44(0) 0161 295 4994
Email: r.m.d.beck@salford.ac.uk
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: DENTAL CHARACTERS USED IN PHYLOGENETIC ANALYSES OF MAMMALS SHOW HIGHER RATES OF EVOLUTION, BUT NOT REDUCED INDEPENDENCE
Review round: 2
Reviewer: 1

Output:
Basic reporting: The authors have done a good job addressing the comments brought forward in the previous round of reviews. In this version of the manuscript, I have no major concerns although note there were a few typos that I caught and have highlighted in the attached PDF. I also found numerous inconsistencies in the reference list that require attention.
It would also be useful to have a list of the supplementary materials provided somewhere to make navigation of files simpler rather than just file names especially as some of the supplementary files do not include titles
Experimental design: I appreciated the authors taking on board my previous comments regarding expanding out their methodology and substituting out/adding to the datasets used in the analyses. I have no further comments.
Validity of the findings: I am still wary of the use of the Bi et al. matrix in the study. I recognise the authors reasoning for using this dataset and that they have included a biref statement in the methods section regarding the limitations of this dataset, but, I do feel there could be more information provided in the discussion (noted in annotated PDF attached with my review) following on from the comments provided by myself and the other reviewers in the previous round of reviews. I appreciate that this is a meta-analysis but at the same time, I do think it is important to be very clear about the limitations of the input data and what effect they could (and likely are) having on the results and conclusions of this study. In the present draft of this manuscript, these issues are mentioned but only briefly and, in my opinion, not given the weight they deserve.
Additional comments: Below are a few comments on the 'Response to reviewers' document. (Apologies, I am working in transit so is easier to copy and paste directly into this section)

R2 “I am not sure why you're comparing it [the Meredith tree] to Bi et al. which is targeting euharamyid anatomy (i.e. mostly fossils) and derived primarily from Zhou et al. 2013. Surely, something like O'Leary et al. The placental mammal ancestor and the post-K-Pg radiation of placentals (or derivatives thereof) which includes a greater number of extant taxa, would be more appropriate?

NB We rejected the O’Leary dataset for two reasons. One is that identified by reviewer 3; the matrix uses some extremely unusual practices in formulating characters that are neither reprehensive of usual procedures in phylogenetics nor particularly informative about evolutionary processes. The second is that a lot of the characters, particularly dental characters relating to number of teeth in particular regions, are scored as unknown for large numbers of taxa. Its isn’t clear quite why this is the case, but it means that the full array of morphologies cannot be analysed.

R2 Note that the missing scores in the Tree of Life datatset are the result of where decision cannot be made as to which tooth/teeth are present or lost in a series. The authors scored by tooth position – there are reasons both for and against this and for scoring just by number of teeth in a series. Both matrices have unusual practices for formulating characters. But ultimately, the O’Leary matrix produces a seemingly more accurate phylogeny than the Bi matrix for a ‘better’ sample of mammals. I appreciate your reasoning for using the Bi matrix and do not think it requires changing for this publication although moving forward it could be interesting to compare different Mammalia matrices using the methodology outlined in this study to see if there are consistent signals in character independence etc.

------------------------------------------------------

R2 “The inclusion of fossils does tend to improve the accuracy of phylogenies, and the lack of fossils in the O'Leary dataset is an issue but perhaps not for your purposes. Could also look at Halliday et al. (Resolving the relationships of Paleocene placental mammals) although that dataset has a whole host of problems so may be better going back to sources datasets of that study (e.g. Wible et al. 2009).”

NB  As we are analysing the evolution of characters over a molecular tree, fossil taxa are dropped from the matrix. Therefore the substantial inclusion of fossils in the O’Leary et al. and Halliday et al trees is not helpful for our analyses.

R2 I referring to the inclusion of fossils in the construction of matrices (apologies that that was not clear). I know the presence/absence of fossils is irrelevant for your analyses but if they improve the quality and accuracy of the dataset, both in how it is constructed and the results it produces, then using such a dataset would provide more credence to your meta-analysis and conclusions.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: DENTAL CHARACTERS USED IN PHYLOGENETIC ANALYSES OF MAMMALS SHOW HIGHER RATES OF EVOLUTION, BUT NOT REDUCED INDEPENDENCE
Review round: 2
Reviewer: 2

Output:
Basic reporting: A few additional typos need correcting - see attached marked up Word document.
Experimental design: This has been improved from the previous iteration, and I don't have any substantive comments.
Validity of the findings: no comment
Additional comments: The authors have done a good job at responding to my comments/suggestions and those of other reviewers. There are a few minor issues that I would like to be addressed in the revision, but these should be relatively easy to deal with. I have picked up some further typos in the revised text (including in the reference list) - see the MS document submitted with my review.

My major outstanding issues that I would like the authors to address are as follows:

1. I didn't pick this up before, but the authors emphasise that they used time-scaled/time-calibrated molecular phylogenies to compare their morphological characters against. However, what is the relevance/importance of the fact that the molecular phylogenies have divergence dates associated with them? Was this information used in the calculation of rates of evolution?

2. As I mentioned in a previous review, the soft tissue partition for the Bi et al. (2014) matrix is definitely not a "fair" reflection of soft tissue variability among living mammals: there are only 3 characters, and all of them relate to details of the reproductive system and have pretty obviously been selected to distinguish placentals from marsupials and monotremes. This should be acknowledged somewhere, and might explain why the violin plots for this partition are so odd looking.

3. A related point: for the violin plots, I recommend including in the labels the number of characters in each partition, e.g. "dentition (n = 100)" or "dentition (100 characters)" or something like that. This would enable readers to see whether the more "extreme" violin plots are for partitions with only a few characters in them.

4. The authors make a very interesting point about the possibility that the increase in rates of dental evolution in the artiodactyl dataset might be due to the large number of herbivorous taxa. This is a nice hypothesis that would definitely be worth testing further in future, but I would like the authors to expand this a bit and explain in more detail why this might be the case. How exactly have plants changed more than “meat” in terms of functional requirements? I am not an expert in this, but I would assume that the functional requirements for eating a leaf would be the same regardless if it was a Palaeocene or Pliocene leaf. However… clearly the evolution of abrasive grasses does represent a major change that likely led to a major change in dental structure of mammals, with the evolution of increasingly hypsodont and in some cases hypselodont teeth. Having said that, some authors have argued that exogenous grit has been the major driver of hypsodonty in mammals (see e.g. Madden’s book “Hypsodonty in Mammals”).


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: DENTAL CHARACTERS USED IN PHYLOGENETIC ANALYSES OF MAMMALS SHOW HIGHER RATES OF EVOLUTION, BUT NOT REDUCED INDEPENDENCE
Review round: 3
Reviewer: 1

Output:
Basic reporting: See General comments to the author section. Previous comments in this section have been addressed and in my opinion, now meet the requirements for publication.
Experimental design: See General comments to the author section. Previous comments in this section have been addressed and in my opinion, now meet the requirements for publication.
Validity of the findings: See General comments to the author section. Previous comments in this section have been addressed and in my opinion, now meet the requirements for publication.
Additional comments: I am happy with the changes the authors have made to the current manuscript and find that they have addressed my comments more than adequately.

Two tiny things:
In the manuscript references, there is an erroneous comma after Marjanovic in Marjanovic & Laurin 2019
In the supplementary tables (word doc) there is the use of cetartiodactyls in the caption for Table S1.

Otherwise, I endorse the acceptance and publication of this manuscript in PeerJ.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: DENTAL CHARACTERS USED IN PHYLOGENETIC ANALYSES OF MAMMALS SHOW HIGHER RATES OF EVOLUTION, BUT NOT REDUCED INDEPENDENCE
Review round: 3
Reviewer: 2

Output:
Basic reporting: Unchanged from previous version
Experimental design: Unchanged from previous version
Validity of the findings: Unchanged from previous version
Additional comments: The authors have responded to my few minor points appropriately - I'm now happy to see this published. Congratulations!


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: POTENTIAL OF THE ECONOMIC VALUATION OF SOIL-BASED ECOSYSTEM SERVICES TO INFORM SUSTAINABLE SOIL MANAGEMENT AND POLICY
Review round: 1
Reviewer: 1

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: This is a really nicely written and interesting paper on the potential for economic evaluation of soil ecosystem services, which I enjoyed reading and stimulated many questions and thoughts on the subject. As a non-specialist in the economics field, I can only offer general points for discussion and I am not qualified to offer specific technical comments on the text. My main points (and a few specific points) are listed below.

Authors state that current valuation studies are inadequate – too few ecosystem services and not using state of the art methods. These short falls are discussed in depth, but it's not clear to me what the "state of the art" methods actually are. What alternative approach would be recommended by the authors as a way forward? Could an example be given for clarity for the non-economist reader?

In a similar vein, the authors state that there is a need to express trade-offs between ecosystems services and suggest that economic valuation is the way to do this, but it is apparent from the review that most studies only focus on one or two services and cost these separately rather than take into account any trade-offs. Hedonic pricing approach is mentioned as a more advanced method for doing this, but this doesn’t seem to be defined for the non-economist anywhere and I personally don’t understand what this is (apologies!). Trade-offs are also referred to in the conclusions – line 678, but are there any specific examples of where economic evaluation have been used to quantify trade-offs?

Relatedly, given the criticisms and limitations of economic evaluation, what are the alternatives that may avoid these fundamental problems with this approach? E.g. line 270 – “valuations give an idea of “orders of magnitude” rather than precise costs. However, precise costs are then often quoted without qualification, even if they are only broad estimates. Once a precise value is attached to an object, then it becomes at risk of misinterpretation. Should these values not therefore be expressed in relative or qualitative terms (low, medium, high/ less or more?) which more accurately represent the analysis and avoid some of the dangers of misinterpretation? Are there any examples of these kinds of approaches? Also, in this same section, line 271 – what are the guidelines that are referred to? Do these exist already or do they need to be generated? If the former, could they be referred to here? If the latter, then what do they need to contain?

Authors state that the paper should be of interest to non-economists, which is really useful, but there are a few terms and phrases that are maybe tricky for a non-specialist to understand. E.g. hedonic pricing (as mentioned above), “use” and “non-use” values etc. Apologies if these are defined and I’ve just missed them, but it would help to have a brief layman’s description of these.

Section 2 – survey methodology. Just a personal preference, but the description of the survey method may be better placed at the start of section 4.2 where the lit review is reported. The overview isn't much of an overview and could do with a description of the method.

Section 4.1 – ecosystem services – here, only provisioning and regulating are mentioned? What about supporting and cultural services? … particularly as cultural services are mentioned explicitly later on (lines 285 and 332) and section 4.2.2.3

Trivial grammatical errors:
Line 171 “allows a comparison of the …”
Line 186 “we do not attempt for a …” (delete “for”)
Line 410 “disentanglement [of]…” (insert “of”)
Line 567 “…or specific public or merit good characteristics” (not sure I understand – rephrase?)
Line 589 “…a decision [of] which strategy…”(insert “of”) (and check this section (6.2) for grammar)

Table 2. I don’t think this is very useful on it’s own as just a list of references, though I can see it is necessary for the interpretation of table 3. Could these two tables be merged or combined in some way?

General comment: In section 5, there is much discussion on the factors that must be taken into account in order to more accurately cost the contribution of soils to ecosystem services, but it’s not clear what the point of this valuation is. Surely, there’s only need for a price tag if this is to be used to directly inform incentive schemes? But could incentive schemes not be based purely on how much is needed to convince a land manager to change his/her behaviour, regardless of the “actual” value of the soil/service (which, as stated previously is only a guide to the order of magnitude rather than an actual figure). Might this point be useful to bring out in the discussion? E.g. and again in section 6.2 line 611 on.

General comment: Section 6.1 – agenda setting. Line 580 “a comprehensive set of values for different ecosystem services…” Presumably these values don’t have to have a price tag associated with them? A prioritised list would be just as effective?

And another general point of discussion – section 6.3 care would need to be taken in using economic valuation of one particular component of the agroecosystem if comparable valuations are not available for other elements. So, if ecosystem services provided by soils have been costs and this is used to legitimise an incentive scheme, but the ecosystem services provided by above-ground biodiversity have not, then there is a risk that the prioritise for management interventions may be artificially skewed.

Conclusions – it would be nice to see a recommendation or description of what a more effective solution might look like. And also an opinion on whether alternatives to economic valuation (e.g. qualitative approaches) could be more or less effective (though I realise that these alternatives are outwith the specific scope of this review).
Similarly, line 681 “…needs to be complemented with other perspectives ..” Like what? Give example to make this more concrete?


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: POTENTIAL OF THE ECONOMIC VALUATION OF SOIL-BASED ECOSYSTEM SERVICES TO INFORM SUSTAINABLE SOIL MANAGEMENT AND POLICY
Review round: 1
Reviewer: 2

Output:
Basic reporting: Soil is the basis of life; the physical, chemical, and biological properties of soil supports various functions individually and in combinations, which are connected to the ecological end-points and eventually to human wellbeing. The topic is of significance.

I found the article more of a book chapter than a paper. Needs refinements.

Introduction needs improvement.

Some of the materials from section 3 could go to introduction.

Perhaps adding some texts on what has already been done in earlier publications, what the gap is  and how the current manuscript address the gap, would be helpful.
Experimental design: I am not sure why "Survey Methodology" is included for this manuscript.
This manuscript is based on literature review and not survey.

Refering to some more papers could also help for e.g.
Schmidt et al 2011. Persistence of soil organic matter as an ecosystem property. Nature Perspective

Brevik et al 2019 Shelter, clothing, and fuel: Often overlooked links between soils, ecosystem services, and human health. The Science of The Total Environment
Hansen and Ribaudo 2008.  Economic Measures of Soil Conservation Benefits
Pereira et al  Soil ecosystem services, sustainability, valuation and management.
I am skeptical about the extent of policy implications discussed with such limited studies available and  reviewed.
Also is summary section needed after section 6?
Validity of the findings: Tables 2 and 3 could be merged. information on results of each study could also be added along with the year of valuation, geographic region, temporal and spatial scale, as well as whether the status or the change is estimated.

The summary can then be presented in more concise and meaningful way.
Additional comments: The topic is important and this paper is a good undertaking of the authors.I found the article more like a book chapter. Needs refinements some in analysis and synthesis of the review and second in organizing.
Soil is the basis of life; the physical, chemical, and biological properties of soil supports various functions individually and in combinations, which are connected to the ecological end-points and eventually to human wellbeing. Creating a figure along this line using drawings/pictures could be helpful.

The manuscript may also benefit from revised tables and figure. The flow diagram could be revised by adding some examples that could help the audience to relate to.
I also have reservation regarding the policy implications part of the paper.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: POTENTIAL OF THE ECONOMIC VALUATION OF SOIL-BASED ECOSYSTEM SERVICES TO INFORM SUSTAINABLE SOIL MANAGEMENT AND POLICY
Review round: 2
Reviewer: 1

Output:
Basic reporting: Final check for correct English grammar recommended
Experimental design: no comment
Validity of the findings: no comment
Additional comments: The authors have dealt comprehensively with the reviewer recommendations from the original submission and the paper is now very much improved and I would recommend that this ms is now acceptable for publication without need for further review, once it has been thoroughly checked for English grammar.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: TRANSCRIPTOME SEQUENCING AND ANALYSIS REVEALS THE MOLECULAR RESPONSE TO SELENIUM STIMULI IN PUERARIA LOBATA (WILLD.) OHWI
Review round: 1
Reviewer: 1

Output:
Basic reporting: Except the introduction part, the English of the manuscript needs to be improved. In its current form, it is very difficult for the reader to understand the study. Please also check the formatting of the references and in-text citations, since it is not done in a consistent way (e.g., sometimes journal abbreviations are used, sometimes the full names; species names should be in italics etc.).
The introduction reads well, but in my opinion the paragraph about the medicinal effects of Pueraria (lines 41 to 52) needs some revisions. Several of the cited studies were conducted on rats. This is not clearly stated in the manuscript. The reader could get the expression that the mentioned medicinal effects are proven for humans.
Further, the order of the presented results should follow the order in the methods part.
Experimental design: The methods are well described (but see my comment on the English above), but some information is missing. Please indicate which software was used for read mapping (lines 112-113) and how much sodium selenite of different concentrations (line 119) was used for the treatment.
Validity of the findings: The analysis of SOD and MDA over the different sampling days is interesting (Fig. 1). I was wondering, whether the differences between sampling days as well as between concentrations are statistically significant. Maybe the authors could consider applying some statistical tests to provide more information about this.
In line 171 and Figure 3 the KEGG term “overview” is presented. Please check, whether this is correct. I have never heard about such a term.
In line 158 it is stated that 90961 genes were annotated. In the abstract, 43195 genes are reported to be annotated. Please check the correct number.
Please check the caption (and description in the Excel files) of Tables S9-S11. I think “corrected” needs to be replaced by “correlated”.
In the discussion part some more information could be added. In lines 252 to 254 it is stated that the investigation of MOD (I guess this is MDA) and SOD support 25mg/L as a suitable sodium selenite concentration. Here I miss some discussion about the content of SOD and MDA over the different treatments. For instance, can it be expected that SOD is decreasing, while MDA is increasing? Did other studies find similar results?
Furthermore, some sentences about the gene expression over the sampling days (Figure 5) could be added. I think this is an interesting result, which could be discussed.
In the conclusion part, the authors could also add some more information about the possible use of the results for other scientist and the cultivation of Pueraria lobata and could suggest some future studies.
Additional comments: The authors conducted a nice study, which revealed interesting results. The presentation of the results needs some improvement.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: TRANSCRIPTOME SEQUENCING AND ANALYSIS REVEALS THE MOLECULAR RESPONSE TO SELENIUM STIMULI IN PUERARIA LOBATA (WILLD.) OHWI
Review round: 1
Reviewer: 2

Output:
Basic reporting: Guo et al. performed transcriptome sequencing to elucidate the response to selenium in Pueraria lobata (willd.) Ohwi. Here are some suggsetions:
Line 26. Person should be 'Pearson'
Line 46. there is extra tracking in sentence
Line 51. Rewrite the sentence starting 'All the studies...'
Line 54. rewrite 'our health' sentence
The second paragraph should be justified
Line 72, 103, 106  there is extra tracking in sentence
Line 127 '.' should be at the end of the lit cited
Line 129 omit Wu et al. in the parenthesis
Line 132 Person should be Pearson
Lİne 136 physilogical word starts with capital letter
Line 145 '.' should be at the end of the sentence
Sequencing results and physiological results should exchange places
Lİne 177, 215, 216, 217, 218 there is extra tracking in sentence
Lİne 227 The word 'indicates'
Validation of the expression of the gens could be given as last results
Line 265. there is extra tracking in sentence
In discussion 4th paragraph should be justified
discussion could be written with more details and could be developed
Experimental design: The research is within the aims and scopes of the journal.
Research question is well defined and meaningful.
Here are some suggestion:
In materials and Methods, I believe the method for SOD and MDA analysis should be described.
And also for RNA isolation and library construction for sequencing should be described in brief also.
Validity of the findings: I think the findings are meaningful and literatures are clearly stated. The data is robust and statistically sound.

However, I believe discussion could be given in more detail and could be developed. The weak part of the manuscript is discussion, I suggest to support the findings with other studies.
Additional comments: Guo et al. performed transcriptome sequencing to elucidate the response to selenium in Pueraria lobata (willd.) Ohwi. Here are some suggsetions:
Line 26. Person should be 'Pearson'
Line 46. there is extra tracking in sentence
Line 51. Rewrite the sentence starting 'All the studies...'
Line 54. rewrite 'our health' sentence
The second paragraph should be justified
Line 72, 103, 106  there is extra tracking in sentence
Line 127 '.' should be at the end of the lit cited
Line 129 omit Wu et al. in the parenthesis
Line 132 Person should be Pearson
Lİne 136 physilogical word starts with capital letter
Line 145 '.' should be at the end of the sentence
Sequencing results and physiological results should exchange places
Lİne 177, 215, 216, 217, 218 there is extra tracking in sentence
Lİne 227 The word 'indicates'
Validation of the expression of the gens could be given as last results
Line 265. there is extra tracking in sentence
In discussion 4th paragraph should be justified
discussion could be written with more details and could be developed
The research is within the aims and scopes of the journal.
Research question is well defined and meaningful.
Here are some suggestion:
In materials and Methods, I believe the method for SOD and MDA analysis should be described.
And also for RNA isolation and library construction for sequencing should be described in brief also.
I think the findings are meaningful and literatures are clearly stated. The data is robust and statistically sound.

However, I believe discussion could be given in more detail and could be developed. The weak part of the manuscript is discussion, I suggest to support the findings with other studies.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: TRANSCRIPTOME SEQUENCING AND ANALYSIS REVEALS THE MOLECULAR RESPONSE TO SELENIUM STIMULI IN PUERARIA LOBATA (WILLD.) OHWI
Review round: 2
Reviewer: 1

Output:
Basic reporting: see below
Experimental design: see below
Validity of the findings: see below
Additional comments: I thank the authors for addressing my suggestions. Before publication, the text should be carefully checked for typing errors such as was -> were (line 122), Swissport -> Swissprot (line 126), seedling -> seedlings (line 149), very -> every (line 172), or person -> Pearson (line 212).


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: ALCOHOL CONSUMPTION AND EMPLOYMENT: A CROSS-SECTIONAL STUDY OF OFFICE WORKERS AND UNEMPLOYED PEOPLE
Review round: 1
Reviewer: 1

Output:
Basic reporting: I was uncertain where the death numbers came from, typically citations come after the information given, I assume perhaps it came from WHO since they were cited at the end of the paragraph on lines 85-89.  Perhaps a citation after the first sentence would alleviate this.
Experimental design: First scope of the journal well.

Research question was stated, but I'm not sure how it fills in any gaps unless there have not been other studies to identify actual biomarker differences in alcohol use among the employed and unemployed.  The health economics literature has plenty of identification of this difference from self reported alcohol use and alcohol expenditure data, I would highlight the contribution here is the actual biological measure of alcohol use.

The statistical analysis could use more support.  The questionnaire was said to have health status and sociodemographic data (on lines 118-119), however the authors only chose to use gender and age in their matching procedure, if you had other covariates why did you not include them?  At least give support for why they weren't relevant or exactly what other data you had on these individuals.  If age and gender were the only information you had, or you were concerned with standard errors becoming too large by including other controls then give a reasoning why you chose the two you did (mentioned on lines 161-162).  I would think gender would be a worse predictor of the treatment than something like health status would be, or other sociodemographic data.
Validity of the findings: The paper did a great job in the conclusion explaining the limitations of the results as causal, and highlighted the real finding of this research which is simply the difference in biomarker measures between those employed and unemployed.
Additional comments: I think the introduction  was a good motivator, however, I think it could have had more of the discussion found in the "discussion" section from lines 202-219.  It wasn't as clear where this research fit into the bigger pictures in the introduction, but once I read the discussion section it was more clear.  This is personal preference of where I would suggest to move that discussion.

I would think you could be worried about differences in the biomarker levels of your excluded sample.  Table 1 helps alleviate concerns that the covariates and propensity score of the treatment are similar across your unmatched and matched sample, but if those excluded (which are primarily t hose in the actual treatment of unemployed) had lower biomarker levels then I would be more skeptical of your results.  Perhaps including additional rows, or mentioning whether there are significant differences in the Results section would alleviate these concerns.

Similar concerns to my previous comment could be alleviated by providing results or mentioning the how results differ if with replacement is used.  This allows you to use the entire sample, and I realize this may increase standard errors to the point you can't find significant differences but if that it is the case I think that is important to note.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: ALCOHOL CONSUMPTION AND EMPLOYMENT: A CROSS-SECTIONAL STUDY OF OFFICE WORKERS AND UNEMPLOYED PEOPLE
Review round: 1
Reviewer: 2

Output:
Basic reporting: In the article "Alcohol consumption and employment: a cross-sectional study of office workers and unemployed people," the authors investigate multiple bio markers associated with alcohol use and employment. They found 4 of 5 markers were associated with significantly decreased odds of being an office worker. The investigation of how employment is associated with substance use is an important contribution to the literature as the protective factors of employment in addiction recovery are not well understood. There is a good deal of research demonstrating substance use disorders are associated with poor employment outcomes.  The strength of this paper is the connection with measurable bio markers of alcohol use. However, I have identified several areas in need of improvement or clarification, that if addressed, would improve this manuscript.

1.	The authors have presented a considerable amount of information pertaining to the social and physical costs of alcohol misuse and its consequences. However, this information makes up about 1/3 of the introduction. The problems associated with alcohol use are well known and accepted. Yet, the bio markers associated with alcohol-related unemployment are not understood. As this is the real novelty of the study, I suggest the authors provide much more evidence in the introduction that suggest the presently tested bio markers are worthy of investigation in connection with employment. Why were each marker included in the study? What existing research would suggest they are important and associated with alcohol-related unemployment? As it stands, the reader has no idea about the included predictor variables until the methods section, where they seem a bit of a surprise.

2.	The research cited about employment and alcohol seems to present how alcohol causes employment. This is a common theme in the literature. However, this can be easily addressed by avoiding causal language such as "affect". Please use words of association, such as related, associated, etc. For example, in the introduction the authors write, “Several studies have found that alcohol abuse negatively affects employment…” Further, there is some new literature that supports employment as a source of "recovery capital" and may support recovery. Please see recovery capital literature, as this may be aligned with the authors' hypotheses. (see Hennessy, 2017, Recovery capital: a systematic review of the literature).

3.	Do not use the terms "abuse", "abuser". These terms perpetuate negative stigma and are out of the current trend in addictions literature. Instead, the terms "alcohol use", "alcohol misuse", "alcohol use disorder" (DSM5), and alcohol dependence (ICD-10) are preferred. When referring to a patient, please use person first language; "a person who misuses alcohol". These terms occur throughout the manuscript.

4.	I am a bit lost by the presentation office workers use of VDT. It seems that the authors are suggesting the using a computer is associated with greater alcohol consumption. Please give more rationale for the population selection. Additionally, please explain and support with evidence, the connection to the VDT. This is all new information for me so I need more context. I am assuming that other readers may feel the same.

5.	It's a bit odd to have the limitations as part of the conclusion. I suggest placing them in the discussion and leave the conclusion for a summary and take-home message.

6.	References are listed by name in the text, but by number in the reference list. I suggest using PeerJ style.

7.	Table 2. - Decimals are used in the other tables. Please make Table 2 uniform to the others.

8.	Please add page numbers

9.	Table 3 - Please make clear the number of participants included in the regression analysis. The authors stated, "Unmatched subjects were discarded from the analysis," but for Table 3 Office workers n=105 and Unemployed=268 which does not fit the equal 157 in matched pairs. Additionally, I had to total Ns. Please put Ns in the column headings. Again this may be better explained in the analysis section because I assumed only the matched participants were included in the regression.
Experimental design: 1.	There is quite a difference in being unemployed and seeking, and unemployed due to being a housewife or student. Finding work is often detrimental for students and housewives.  In fact, being a student is associated with greater treatment outcomes (Sahker et al., 2015).  I am not convinced the distinction between employed and unemployed is justified. Please either (a) remove students/housewives from the analysis, (b) make a third group, or (c) provide a justification for the inclusion of housewives and students in the unemployed group.

2.	Please specify the outcome variable clearly in the methods and explain why it was selected. Currently, the reader must assume you are predicting office worker status from 6 biomedical markers, but this is not specifically stated.

3.	Please discuss the full logistic model including all predictors. Is it one model with only the 5 bio markers included? Did you control for other variables such as age, sex, ethnicity, etc.?

4.	The statistical analyses seem sound. However, a bit more explanation of a few items would strengthen the paper. I'm not understanding the need to match participants in a regression analysis. The Greedy matching algorithm with may be a bit new to most readers. Please explain how and why participants were matched. Additionally, removing extremes from the sample can add bias. The Greedy method is said to reduce bias and Parsons explains this, but more information is needed in this paper to avoid reader confusion.

5.	I'm left wondering if students and housewives were a significant proportion of the unmatched pairs.
Validity of the findings: 1.	There may be a bit of a misunderstanding here. The authors state, "In this study, office employment seems to be a protective factor against the increase in serum markers of alcohol consumption compared to unemployed participants." However, based on how it is explained, I thought the analysis was a multivariable logistic regression with 5 bio markers predicting 1=employed 0=unemployed. If this is indeed true, I'm not sure it makes sense to state employment protects against alcohol use. Rather, alcohol use bio markers predict employment status. If I am incorrect in my assumption, perhaps more explanation in required. Alternatively, the authors interpretation should be adjusted to represent the data.

2 .	Please give some suggestion of how the information found from this study is useful for research and clinical applications.
Additional comments: I found this research to be interesting.  I believe that it is an important contribution.  I think the majority of issues came from a lack of connection between bio markers, alcohol, and employment.  Most of this can be easily addressed with citing evidence and explaining connections.  Further, there are some methodological issues that need to be addressed.  And finally, I think the paper is missing the "so what?" statement.  How does this research fill a gap in the literature and why is is useful.  I believe addressing these comments will improve this manuscript.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: ALCOHOL CONSUMPTION AND EMPLOYMENT: A CROSS-SECTIONAL STUDY OF OFFICE WORKERS AND UNEMPLOYED PEOPLE
Review round: 2
Reviewer: 1

Output:
Basic reporting: I had several points of feedback in the first review and the authors gave the same response at least 3 times: “the logistic regression was performed considering the dichotomized values of each biomarkers (pathological vs normal) as a dependent variable and working status (office workers vs unemployed) as an independent variable.”
At times, adequate responses were given in their rebuttal, but they were not entirely incorporated into the manuscript. A good portion of my initial comments still stand.  Overall, there just needs to be more and better descriptions of the methods so readers understand the procedures and so the study could be replicated. Additionally, reviewer responses that were addressed, should be done so in the manuscript to improve reader understanding.

1. The authors have presented a considerable amount of information pertaining to the social and physical costs of alcohol misuse and its consequences. However, this information makes up about 1/3 of the introduction. The problems associated with alcohol use are well known and accepted. Yet, the bio markers associated with alcohol-related unemployment are not understood. As this is the real novelty of the study, I suggest the authors provide much more evidence in the introduction that suggest the presently tested bio markers are worthy of investigation in connection with employment. Why were each marker included in the study? What existing research would suggest they are important and associated with alcohol-related unemployment? As it stands, the reader has no idea about the included predictor variables until the methods section, where they seem a bit of a surprise.
ANSWER: We better explained the relationships between alcohol consumption and unemployment and between alcoholism and serum biomarkers of liver dysfunction.
RE-REVIEW: Authors partially responded with, “Biomarkers of alcohol consumption and liver function may respond to even rather low levels of ethanol intake in a gender-dependent manner (Alatalo et al., 2009), the overall accuracy of Carbohydrate-deficient transferrin (CDT) and Gamma-glutamyltransferase (GGT), appear to be the highest in the detection of problem drinking (Anttila et al., 2005).”  Readers may assume they randomly chose the other 3 biomarkers since there is nothing in the literature to suggest they are useful.  Please properly set up the analysis with background information on all variables used in the model.

 2. The research cited about employment and alcohol seems to present how alcohol causes employment. This is a common theme in the literature. However, this can be easily addressed by avoiding causal language such as "affect". Please use words of association, such as related, associated, etc. For example, in the introduction the authors write, “Several studies have found that alcohol abuse negatively affects employment…” Further, there is some new literature that supports employment as a source of "recovery capital" and may support recovery. Please see recovery capital literature, as this may be aligned with the authors' hypotheses. (see Hennessy, 2017, Recovery capital: a systematic review of the literature).
ANSWER: We thank the reviewer for the comment and the precious suggestions. We want to clarify that the aim of the study was the evaluation of the association between working status (office workers vs unemployed) and pathological level of biomarker (as dependent variables). We are in accord with the reviewer about the misuse of the term “affect” and similar because Logistic regression analyses and the cross sectional design do not permit to assume the causal effect. According to these suggestions, we modify the paper.
RE-REVIEW: I am still seeing phrases like “directly affecting the productivity…” please use a term of association here.
This phrase is not clear: “alcohol misuse negatively involves employment.”  Do you mean, “alcohol misuse is associated with negative employment outcomes?” and rather than stating, “by directly affecting the productivity and increasing the risk for injuries …” do you mean, “misuse is associated with reduced productivity and increased risk of injuries?”

4. I am a bit lost by the presentation office workers use of VDT. It seems that the authors are suggesting the using a computer is associated with greater alcohol consumption. Please give more rationale for the population selection. Additionally, please explain and support with evidence, the connection to the VDT. This is all new information for me so I need more context. I am assuming that other readers may feel the same.
ANSWER: In order to uniquely characterize the office workers, the exposure to the VDT was chosen to obtain a homogeneous population. Most of the European workforce, in fact, is active in the service sector, as also mentioned in lines 101-103, and the exposure to VDT represents a factor that unites these workers.
RE-REVIEW: Please explain this more clearly in the methods section and not just the response letter. It was confusing to me, so it may be confusing to others.
Experimental design: 1. There is quite a difference in being unemployed and seeking, and unemployed due to being a housewife or student. Finding work is often detrimental for students and housewives. In fact, being a student is associated with greater treatment outcomes (Sahker et al., 2015). I am not convinced the distinction between employed and unemployed is justified. Please either (a) remove students/housewives from the analysis, (b) make a third group, or (c) provide a justification for the inclusion of housewives and students in the unemployed group.
ANSWER: We are sorry for the mistake, in line 122 we wanted to state that we considered only jobless as unemployed excluding housewives and students. As reported in Figure 1 (added in the revised manuscript) housewives and students were considered as “other work conditions” and were excluded from the analysis.
RE-REVIEW: In the revised manuscript, the authors wrote, “unemployed people (UP) have been identified as those who declared to be jobless. Housewives and students were considered in the working group as “Others”. Only OW were included in the study.” But, I’m pretty sure both OW and UP were included in the study. Please revise.

3. Please discuss the full logistic model including all predictors. Is it one model with only the 5 bio markers included? Did you control for other variables such as age, sex, ethnicity, etc.?
ANSWER: We thank the reviewer for the comment. Due to the small number of subjects with pathological biomarker’s levels (dependent variables), we were not able to perform a multivariate analysis with all biomarkers. All presented models (one for each biomarker) were only adjusted for propensity score. The propensity score matching was performed to remove the effect of age and gender on study variables.
RE-REVIEW: This still needs to be clearly explained in the manuscript, not just the response. I am not entirely clear on your methods. I think is you conducted 5 regressions to generate a propensity score, then 5 separate logistic models were preformed, each controlling for only the model propensity matching score. Please explain your methods with enough detail.

4. The statistical analyses seem sound. However, a bit more explanation of a few items would strengthen the paper. I'm not understanding the need to match participants in a regression analysis. The Greedy matching algorithm with may be a bit new to most readers. Please explain how and why participants were matched. Additionally, removing extremes from the sample can add bias. The Greedy method is said to reduce bias and Parsons explains this, but more information is needed in this paper to avoid reader confusion.
ANSWER: We thanks the reviewer for the comment. The matching procedure was performed in order to remove possible confounders as age and gender. It’s known that these factors can influence biomarker’s levels. In particular, this is a cross-sectional study and it can be influenced by the selection bias being a convenience sample. In order to improve readability, we modified the methods section.
RE-REVIEW: Please state this response in the manuscript.
Validity of the findings: 1. There may be a bit of a misunderstanding here. The authors state, "In this study, office employment seems to be a protective factor against the increase in serum markers of alcohol consumption compared to unemployed participants." However, based on how it is explained, I thought the analysis was a multivariable logistic regression with 5 bio markers predicting 1=employed 0=unemployed. If this is indeed true, I'm not sure it makes sense to state employment protects against alcohol use. Rather, alcohol use bio markers predict employment status. If I am incorrect in my assumption, perhaps more explanation in required. Alternatively, the authors interpretation should be adjusted to represent the data.
ANSWER: As previously stated, the logistic regression was performed considering the dichotomized values of each biomarkers (pathological vs normal) as a dependent variable and working status (office workers vs unemployed) as an independent variable. The aim of the study was to assess the association between working status and pathological biomarker levels and not vice-versa, so in the light of this clarification, our statement is correct. However, we clarify this point in the paper.
RE-REVIEW: Perhaps this is just stylistic, but when the authors use the term “association” when referencing a regression analysis, it suggests a mutual relationship.  They are not wrong for using this term, but it is not entirely accurate. However, if they were to say “working status predicts biomarker levels,” it would be clear that the biomarkers are the dependent variables.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: ALCOHOL CONSUMPTION AND EMPLOYMENT: A CROSS-SECTIONAL STUDY OF OFFICE WORKERS AND UNEMPLOYED PEOPLE
Review round: 3
Reviewer: 1

Output:
Basic reporting: no further comment
Experimental design: no further comment
Validity of the findings: no further comment
Additional comments: The authors have done a good deal of work addressing feedback, which I believe has improved the paper.  I am very satisfied with their edits and responses to the feedback.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: META-SOURCETRACKER: APPLICATION OF BAYESIAN SOURCE TRACKING TO SHOTGUN METAGENOMICS
Review round: 1
Reviewer: 1

Output:
Basic reporting: The language could be edited to be more understandable by non-experts and those unfamiliar with using SourceTracker.
Experimental design: SourceTracker is highly dependent on the dataset used for training – the study design here is lacking in adequate number of samples across the different source and sink environments for evaluating the algorithm’s performance.

One of the main advantages of using shotgun metagenomics over 16S rRNA gene sequencing is identification of organisms at the species level - however, this manuscript primarily used Kingdom-level and Genus-level information.

The authors used 1000 sequences per sample – this is the sequencing depth used in the Sourcetracker tutorial, but is not appropriate for use with shotgun metagenomics (or necessarily real 16S rRNA gene sequencing datasets). In shotgun metagenomics, the number of reads that are required for accurately identifying organisms is much higher since the data is more complex.

There is very little detail regarding the processing of the metagenomics data prior to use with SourceTracker.
Validity of the findings: More robust evaluation of SourceTracker parameters (sequencing depth, draws, etc.) would strengthen this work. 10 and 100 draws were compared, but more draws may lead to more convergence. The sampling depth also will likely alter the stability of the SourceTracker results.
Additional comments: This manuscript does not seem to extend the existing SourceTracker program, which was expected based on the name, abstract, and introduction.  A benchmarking study on using SourceTracker with shotgun metagenomics may be a useful contribution to the field, but this should not be presented as a new or development of a software package. Further, more parameterization evaluation should be performed for a benchmarking study.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: META-SOURCETRACKER: APPLICATION OF BAYESIAN SOURCE TRACKING TO SHOTGUN METAGENOMICS
Review round: 1
Reviewer: 2

Output:
Basic reporting: McGhee et al. in their paper “META-SOURCETRACKER: APPLICATION OF BAYESIAN SOURCE TRACKING TO SHOTGUN METAGENOMICS” present an original method to track the origin of contaminating bacteria and other domains, separately or in all together, using shotgun metagenomic datasets.
They used mostly clear, unambiguous, professional English language. Some terms need more clarification and they are listed below. The Intro and background describe well the context with literature well referenced.

Major modifications:
•	They need to describe the word “sink” and “sources” to the readers (L148-00149) as well “draws” and “chains” (L152). They could change the order between the two sections  (“Simulation data for mSourceTracker analysis” and mSourceTracker: diagnostic add-on feature) if it help them to present these words.
•	Which Gibbs sampling data are they talking in L158? It is from SourceTracker or mSourceTracker?
•	List of 14 samples among the 110 downloaded coast marine data used for simulation data (L147 and L196)
•	L202 do they talk about mSourceTracker or SourceTracker (Knights et al 2011)?
•	Do the 14 sources are 14 sinks that they used in the simulation?
•	They need to provide which single coastal marine sink they used in L233.
•	Replace the color in confusion matrix by the values or combine both of them. They need to list the samples used in each environment as “sink” and as “sources”
•	Figure 1 need further adjustment to help the readers to understand it. Need to provide the name of coastal marine sample used in Fig 1. A, B, D and “source” used too.
•	Fig 1. C should be separated to Fig 1. A, B, D as it is done on more datasets and the choice of datasets for this figure need to be described in the result section and listed in the legend as well.
•	Fig. 1 D need more description in the result section to help the readers to interpret this figure and values provided.

Minor modifications:
•	Remove “_” line 60
•	Move paper “Knights et al, 2011) L80-81 to the end of the first sentence L75
•	Figure 3. Do they talk SourceTracker or mSourceTracker?
•	Legend of Table 1 put “(OOB)” after “out-of-bag error” and add the meaning of this.
•	List the 4 environments in the legend of Figure 5.
Experimental design: This paper is an original primary research within scope of the journal “PeerJ”.
The research question is well defined and stated how they fill an identified knowledge gap.
The Method and data are partially described and need additional information before any publication:
1)	the authors should provide a descriptive about their software and the Bayesian method as they put in the title as they never describe the method implemented in their software
2)	the authors should provide a link to for webpage or github link that should contain:
a.	bin script of mSourceTracker as well as the programming script talking L122
b.	user manual with
i.	examples how to run their software and programming script with data presenting in this manuscript to allow users to reproduce their findings (related to “Simulation data for mSourceTracker analysis” and mSourceTracker:diagnostic add-on feature) and then figures
ii.	format of input data to provide to run the software and output data
iii.	how to create and update a dictionary (related to “Taxonomic separation of metagenomics”)
c.	installation manual
3)	The authors should provide more information about storage, memory usage, computing usage, and wall-time consuming to help the users to check and use their software in the best conditions. They can provide these pieces of information based on their data used in their manuscript.
4)	They need to provide the parameter values used in their analysis and how they make this choose (L 223-225)
5)	They need to provide the parameter values used (L231)
6)	They put in the script “gibbs.py” a comment “Gibb's sampler for Bayesian estimation of microbial sample sources. For details, see the project README file.” However, we don’t have access to such README file
Validity of the findings: Although the data are described in the Supplementary Table 1, it needs further information.
1)	add information what they are these accession number and where we can download them
2)	add some meta-data such as geographic location of data or put an earth map with dot where data come from

The data appear to be robust, statistically sound, and controlled, but better description of their method will help to confirm it. Conclusions are well stated, linked to original research question & limited to supporting results
Additional comments: This paper presents a method for tracking contaminations using metagenomic data. Before publication, further pieces of information are needed to add in order to allow users to use it and reproduce their findings.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: META-SOURCETRACKER: APPLICATION OF BAYESIAN SOURCE TRACKING TO SHOTGUN METAGENOMICS
Review round: 1
Reviewer: 3

Output:
Basic reporting: The authors did a good job to explain background and need to use metagenomic data for microbial source tracking.

Overall the manuscript is well written. All the figures and tables are easy to read.

Citation of SourceTracker should be added in line 75 after its first introduction, instead of line 80.

I would suggest that the authors also discuss 1) if there are other softwares that can be used for microbial source tracking using metagenomic data and 2) if so, what are the pros and cons of existing softwares and the unique features of mSourceTracker.

There are some formatting and language issues that should be addressed.

Line 60, "_ _" before "ecosystem function" should be deleted.
Line 77, a comma should be added before "which". Actually, please check the usage of "which" throughout the whole manuscript.
Line 93, change "allows" to "allow"
Line 94, change "eukaryotes" to "eukaryota"
Line 115, change the comma after "this study" to something like "this study, which includes"
Line 150, change "which" to "that" after "Samples"
Experimental design: Enough samples were included in the analysis.

Different types of samples were included.

Domain-specific analysis is especially interesting and provided interesting results.

The selection of 10 draws and 100 draws clearly showed the impact of draws on proportion estimates. Please justify why these two numbers were selected and potential issues of using high number of draws. Will calculation time be significantly increased with 100 draws? How about 200 draws? Ideally, three number of draws can be tested and results can be compared to identified the optimal number of draws.
Validity of the findings: I like the domain-specific results very much. The authors did a good job to show how the mSourceTracker can be used to analyze domain-specific information. When a microbial risk assessment is conducted, the domain-specific information will be very useful.

Is it possible to identify group-specific, family-specific, or even species-specific information from mSourceTracker? It would be a nice feature.

The limitation of current study is well explained. I agree with the authors on the challenges of using limited databases and algorithms. However, the "pure" environmental databases will be impossible to collect because environment is an open system and will always be affected from all different types of samples. Please further explain the meaning of "pure" or elaborate the idea.
Additional comments: Overall this is a well written manuscript. The authors expanded their existing work on the popular software SourceTracker to analyze metagenomic datasets. The results could provide interesting insights on microbial source tracking.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: META-SOURCETRACKER: APPLICATION OF BAYESIAN SOURCE TRACKING TO SHOTGUN METAGENOMICS
Review round: 2
Reviewer: 1

Output:
Basic reporting: The authors were responsive to all the reviewers’ comments and have made edits to address concerns that were raised. Despite this, the manuscript can use improvement.

The language is still very technical and could be made more accessible.

The contribution of the presented work should be more accurately stated - evaluating/benchmarking Sourcetracker for use with shotgun metagenomic data, not expanding or building on Sourcetracker.  Referring to the analysis performed as meta-Sourcetracker or mSourcetracker makes it sound as though new software was created, when it does not appear that this is the case based on the sourcetracker code presented in the corresponding github repo, which is identical to the sourcetracker code on Dan Knights' lab github.

The code to reproduce the presented analyses should be made available to readers wishing to attempt this on their own (the corresponding github lacks this key component) with metagenomic data.

From the Github page, it is not clear what is from the original Sourcetracker and what the contribution is. The Github page needs more development such as the scripts, sample test data, an instruction manual, and supplementary analysis results referred to on line 207.
Experimental design: The addition of diagnostic plots is nice, but the plots need axis labels and the reader/ user should be given some orientation as to how to interpret the plots.
Validity of the findings: In the rebuttal, it is stated that a more comprehensive evaluation of parameters was performed, but these results are not presented.

The differences between Sourcetracker run on each type of kingdom independently and on the overall metagenomic data are likely different due to sampling depths, to actually compare both of these approaches, the test tests would have to have 1,000 species from each kingdom or 4,000 species across all kingdoms.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: META-SOURCETRACKER: APPLICATION OF BAYESIAN SOURCE TRACKING TO SHOTGUN METAGENOMICS
Review round: 2
Reviewer: 2

Output:
Basic reporting: They answer to the different comments mentioned to them. Although they increase the size of image to improve the reading, the image after printing are blurry and it is difficult to read correct the text. The authors need to improve the resolution of image to avoid this issue for the published version.

Please in the GitHub README, replace "meta data" by "metagenomic data"
Experimental design: 1) in the comment of  the function "ConditionalProbability", they put "The formula used to calculate the conditional joint probability is described in the project readme file." However, no such file available in the file "sourcetracker.py". Could they clarify where this file could be found?

2) Line 165, the authors should link to an example of output table that mSourceTracker need. Moreover, they should provide in the name of their programming script that allow to produce this output file in Line 143 and put an example how to use this script in their GitHub

3) The author need to remind the readers in the beginning of the section "mSourceTracker: diagnostic add-on feature" that mSourceTracker is a new option of sourceTracker2 called "--diagnostics" where data, script, instruction are available in their GitHub (as they put in their last sentence of this section). Moreover, they need to put in the beginning of this section a sentence to explain the aim of this option.

4) It needs to be clarify also in the section "mSourceTracker: diagnostic add-on feature" if the option "--diagnostics" is available in the original GitHub folder of sourceTracker2 (https://github.com/biota/sourcetracker2) and if the other options of sourceTracker2 could already deal metagenomic data.

5) It will be great if they could provide an template script for at least one dataset how they perform their random forest analysis and confusion matrices to help in the reproduction of their findings.
Validity of the findings: no comment
Additional comments: The authors has overall well written the manuscript to explain the new option they developed on the software SourceTracker to analyze metagenomic dataset and provide two examples how this new option could provide an interesting insights on microbial source tracking based on the reference metagenomic datasets proposed to be the sources. This highlights also the needs to work to improve the characterization of unknown reads. In this idea, could msourceTracker annotate which source the reads of sink samples belong to and then allow extracting, for example, only the unknown reads to work on this sub-dataset? If this option is already available, please highlight it in your paper.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: META-SOURCETRACKER: APPLICATION OF BAYESIAN SOURCE TRACKING TO SHOTGUN METAGENOMICS
Review round: 2
Reviewer: 3

Output:
Basic reporting: Overall the study is well written and the authors' responses are satisfactory.
Experimental design: The number of draws is important and maybe the default value can be changed to 100 based on the current study.
Validity of the findings: The revised statement is accurate and reflected the challenges of environmental samples.
Additional comments: The authors have addressed my comments.