seq2science

Automated preprocessing of Next-Generation Sequencing data, including full (sc)ATAC-seq, ChIP-seq, and (sc)RNA-seq workflows.

• idr call is configurable (idr_options)
• single-cell DESeq2 (currently only via deseq2science with user-specified groups per cell)
• scRNA quality control workflow with singleCellTK
  • cell calling/filtering with DropletUtils
  • mitochondrial gene set detection/filtering
  • doublet identification/filtering with scDblFinder
  • processing of alternative experiments, such as spike-in expression
  • qc report generation for cell/droplet based experiments
• added Seurat and FlatFile format export to scRNA qc workflow
• added parameter to select velocity matrix for qc and export

• raw/processed scRNA count tables are now stored and exported to SingleCellExperiment S4 objects instead of Seurat S4 objects
• moved scRNA post processing to separate module
• export unspliced velocity counts to separate sce object
• seq2science should be less susceptible to poor programming environment management by using the conda-ecosystem-user-package-isolation package
• seq2science will now demand all requirements exactly the way it likes it
  • this will make the workflows more stable.
• local fastq files are no longer renamed (and should just work)
• scRNA-seq trimming code simplified

• removed scRNA merging rule due to memory issues with large and sparse samples
• removed deprecated scRNA post-processing workflow (superseded by singleCellTK qc workflow)

• fixed bug causing incorrect genome string in read_kb_counts.R
• bams generated with(out) filtering on size and tn5 shifting weren't removed when not necessary anymore

• rna-seq creates a TPM table for each quantification method