PopAlign_Data

Single-cell RNA-seq datasets and tutorial for PopAlign paper<br><br>############## DATASETS ##############<br>Each data folder includes:barcodes.tsv : cell barcodes<br>genes.tsv : genes[ Name ].mtx : sparse matrix file of transcript counts<br><br>Subfolders: <br>MM1-MM4: 22,294 Peripheral Blood Mononuclear Cells (PBMCs) from four multiple myeloma patients. Data collected using 10x 3' Gene Expression v2 kit. <br>healthy1/healthy2: 12,865 PBMCs from two healthy donors. Data collected using 10x 3' Gene Expression v2 kit. <br>drugscreen:<br>33,482 cells42 drugs applied at 1uM for 24 hours onto PBMCs collected from a single healthy donor. Data collected using 10x 3' Gene Expression v3 kit. Includes a metadata file (meta.csv) with each row corresponding to each cell in the gene expression matrix. <br>Drugs tested:Meprednisone, Dexrazoxane HCl (ICRF-187, ADR-529), Etodolac, Phenylbutazone, Pomalidomide, Budesonide, Loteprednol etabonate, CTRL, Betamethasone Valerate, Febuxostat, Sulfasalazine, Flurbiprofen, Mianserin HCl, Naproxen Sodium, Triamcinolone Acetonide, Acetylcysteine, Everolimus (RAD001), Isotretinoin, Ibuprofen, Doramapimod (BIRB 796), Allopurinol Sodium, Tranilast, Cyclosporine, Adapalene, Thalidomide, Celecoxib, Ketoprofen, Loratadine, Tazarotene, Bimatoprost, Cetirizine DiHCl, Mesalamine, Mercaptopurine (6-MP), Busulfan, Zafirlukast, Zileuton, Latrepirdine 2HCl, Rapamycin (Sirolimus), Alprostadil, Masitinib (AB1010), Methotrexate<br>############## TUTORIAL ##############<br>The tutorial includes 5 files for rerunning the analysis in figure 5 of the PopAlign paper: <br>PopAlign_access_instructions: read this first to get access to github repo<br>PopAlign_drugscreen_tutorial.ipynb : iPython notebook of analysis for the drug screen<br>Popalign_tutorial - PDF: Detailed walkthrough of PopAlign tutorial code<br>output_drugscreen: output folder for plots generated from drug screen analysis<br>drugscreen_data.pickle: stored data structures (pop) after running analysis. Can be loaded instead of loading directly from mtx files (raw gene count matrices)<br>