{'fraction_non_alphanumeric': 0.023957409050576754, 'fraction_numerical': 0.0044365572315882874, 'mean_word_length': 4.811855670103093, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Assigning B cell Maturity in Pediatric Leukemia

One method for analyzing pediatric B cell leukemia is to categorize each malignant cell based on its resemblance to one of 7 stages in B cell development. Researchers hand label (“gate”) B cell maturity by drawing separate gates per patient. However, this process is both time consuming and must be done patient-by-patient due to the heterogeneity of each cancer. We aimed to automate this gating process with one classification algorithm for all patients. We found that a Crammer SVM algorithm classifies cells with 97% accuracy, indicating that information from other dimensions of the data can compensate for patient specific differences. This revealed that we can reliably apply a consistent framework to a diverse set of patients. Background A struggle in cancer cell biology is the heterogeneity of the disease: each cell in a cancer sample is different, as is each patient. Therefore amidst this chaos of cancer it is challenging to define a structure that could provide insight into cancer development, progression, and outcome. B cell acute lymphoblastic leukemia (ALL) is a hematologic cancer where B cells (the antibodyproducing cells of the immune system) become mutated and excessively proliferative during development. Current work in Dr. Garry Nolan’s lab involves looking at protein expression on single cells from bone marrow from B cell ALL patients. Cells in a given sample are stained with metal-conjugated antibodies specific for certain antigens or proteins. Using a technique called mass cytometry (or CyTOF), the time of flight of the ions conjugated to those antibodies provides a readout of the levels of each protein on each cell. This outputs a matrix of ~10^6 cells by ~40 parameters (proteins) that we have measured. Work in our lab has found a potential structure for understanding B cell ALL. Kara Davis and Sean Bendall found that healthy B cell development can be broken down into a progression of seven stages based on the expression of certain sets of markers (proteins) on each B cell (figure 1a). Using this definition of healthy development, Dr. Davis imposed this framework onto the Figure 1: a. The stages of normal B cell development. b. A sample hand-gate of the