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This is a collection of scripts I use (or have used in the past) to process scRNASeq data. They are free to use by anyone else for any purpose, but come with no assurances or guarantees of correctness or functionality. The general workflow is as follows: 0 : Create the appropriate genome for the dataset, and obtain the read files & initial QC - Building mapping indexes generally requires ~30Gb of memory for a mouse-sized genome 1 : Split the files by well (cell), Trim reads as appropriate based on QC 2 : Map the reads to the genome 3 : Clean up mapping output & remove duplicates 4 : Mapping QC 5 : Quantify expression 6 : Assemble expression matrix Finished Pipelines: 00_Kallisto_For_SmartSeq.readme = Smartseq2 + Kallisto (no UMIs) Brief Descriptions of Useful files: 0_Extract_barcodes_from_BAM.sh : open the first line of each BAM file and find the barcode (tagged with BC:) - for matching up metadata.
M3Drop
LiverMap2.0
F1000Imputation
M3D
PoissonUMIs
Liver_sc_sn_paper_scripts
LiverAnnotation
scTarNet
LiverTumouroidsScripts
R-Scripts
CycleMix
KellerLab_Macrophages
LiverTumouroids
CourseData
cellphonedb_visualization
ExternalLiverData
Chromium_Processing_Pipeline
EllipsePseudotime
MultiPath
TreeOfCells_Work
TreeOfCells
scDatasets
SpatialAnalysis
LiverMapSpatialTranscriptShiny
The Shiny widget for the 20 LiverMap Spatial Transcriptomics dataMalariaCAScripts
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