Update README.md

README.md

@@ -11,4 +11,108 @@ tags:
 - life sciences
 size_categories:
 - 10K<n<100K
----
+---
+
+# ComputAge Bench Dataset
+
+## Introduction
+
+**DNA methylation** is a chemical modification of DNA molecules that is present in many biological species, including humans. 
+Specifically, methylation most often occurs at the cytosine nucleotides in a so-called **CpG context** (cytosine followed by a guanine). 
+This modification is engaged in a variety of cellular events, ranging from nutrient starvation responses to X-chromosome inactivation to transgenerational inheritance. 
+As it turns out, methylation levels per CpG site change systemically in aging, which can be captured by various machine learning (ML) models called **aging clocks** 
+and used to predict an individual’s age. Moreover, it has been hypothesized that the aging clocks not only predict chronological age, but can also estimate 
+**biological age**, that is, an overall degree of an individual’s health represented as an increase or decrease of predicted age relative to the general population. 
+However, comparing aging clock performance is no trivial task, as there is no gold standard measure of one’s biological age, so using MAE, Pearson’s *r*, or other 
+common correlation metrics is not sufficient.
+
+To foster greater advances in the aging clock field, [we developed a methodology and a dataset]() for aging clock benchmarking, ComputAge Bench, which relies on measuring 
+model ability to predict increased ages in samples from patients with *pre-defined* **aging-accelerating conditions** (AACs) relative to samples from 
+healthy controls (HC). We highly recommend consulting the Methods and Discussion sections of our paper before proceeding to use this dataset and build 
+any conclusions upon it.
+
+## Dataset description
+
+This dataset was collected by combining publicly available datasets of DNA methylation in human blood and saliva samples from the 
+[NCBI Gene Expression Omnibus](https://www.ncbi.nlm.nih.gov/geo/) (GEO) data repository according to the criteria described in [our publication](), 
+and it comprises samples from patients with aging-accelerating conditions and healthy controls. From all these public datasets, we selected only samples that had 
+annotated ages and conditions (some disease vs. healthy control).
+
+All methylation profiling platforms in this dataset represent different generations of Illumina Infinium BeadChip human methylation arrays. 
+Detailed documentation for these platforms can be accessed at the [manufacturer’s website](https://support.illumina.com/?tab=microarrays) 
+(Methylation → Select One → Infinium Human Methylation 450K BeadChip or Infinium MethylationEPIC BeadChip).
+
+The dataset consists of two main parts: data and meta. Data is stored with parquet in the “\~/data” folder and contains methylation profiles across samples, 
+and meta contains additional information, such as subject’s age, gender, condition, etc., and is stored as “\~/computage_bench_meta.tsv”. 
+Both parts are described further below in more details.
+
+In total, the dataset comprises **10,404 samples** and **900,449 features** (DNA methylation sites) coming from 65 separate studies 
+(some features are missing in some files). It is uncommon for ML datasets to have N << P, so we had to put samples as columns and features as rows 
+in order to save the dataset in the parquet format. We recommend transposing data upon loading in order to match with meta rows, 
+as mentioned further below in the Guidelines section.
+
+Its main purpose is to be used in clock benchmarking (for more details on that, again, proceed to the Guidelines section and don’t hesitate to visit 
+[our paper]()). Nevertheless, you are free to use it for any other well-minded purpose you find suitable.
+
+## Data description
+
+DNA methylation per site can be reported in two ways: as **beta values**, or as **M values**. Briefly, beta values represent the ratio of methylated signal 
+(probe intensity or sequencing read counts) to total signal per site (methylation signal is measured as probe intensity or sequencing read counts), 
+while M value is the log2 ratio of the methylated signal versus an unmethylated signal. A more thorough explanation can be found in 
+[Du et al., 2010](https://doi.org/10.1186/1471-2105-11-587).
+
+In the original datasets deposited on GEO, therefore, DNA methylation values were represented either as a beta fraction (ranging from 0 to 1), 
+beta percentages (ranging from 0 to 100), or M-values (can be both negative and positive, equals 0 when beta equals 0.5). We converted all data 
+to the beta-value fractions ranging from 0 to 1. The values outside this range were treated as missing values (NaNs), as they are not biological.
+
+In each dataset, only samples that appeared in the cleaned meta table were retained.
+
+### Row names
+
+DNA methylation site IDs according to the output from a methylation profiling platform. 
+
+### Column names
+
+GEO sample IDs.
+
+## Meta description
+
+### Row names
+
+GEO sample IDs, as in data columns
+
+### Column names
+
+**DatasetID**: GEO ID of a dataset that contains a respective sample.
+
+**PlatformID**: GEO ID of a platform that was used to obtain a respective sample. 
+Platform IDs can be mapped to the common platform names (that represent an approximate number of profiled methylation sites) as follows:
+GPL8490 = 27K, GPL13534 = 450K, GPL16304 = 450K, GPL21145 = 850K/EPIC, GPL23976 = 850K/EPIC, GPL29753 = 850K/EPIC.
+
+**Tissue**: sample source tissue. “*Blood*” stands for peripheral blood samples, “*Saliva*” stands for saliva spit samples, and “*Buccal*” stands for buccal swab samples.
+
+**CellType**: sample cell type. Either a specific cell population (mostly immune cell subtypes with cell type-specific molecular markers) 
+or broader sample categories such as whole blood, buffy coat, peripheral blood mononuclear cells (PBMC), or peripheral blood leukocytes (PBL). 
+Some samples lack cell type annotation.
+
+**Gender**: abbreviated sample donor gender. *M* = Male, *F* = Female, *O* = Other, *U* = Unknown.
+
+**Age**: sample donor chronological age in years (“float” data type). In the original datasets deposited on GEO, 
+it can be either rounded by the researchers to full years, or converted from months, weeks, or days. Where available, we calculated years from the smaller units.
+
+**Condition**: health or disease state of a sample donor.
+
+**Class**:  class of the respective sample condition. Healthy control samples (HC) are included in a separate healthy control class with the same abbreviation (HC).
+
+
+## Additional Information
+
+### Licensing Information
+
+The dataset is released under the Creative Commons Attribution-ShareAlike License (CC BY-SA) v4.0 license.
+
+### Citation Information
+
+[Citation to be published]
+
+