Workflows
What is a Workflow?Filters
From the R1 and R2 fastq files of a single samples, make a scRNAseq counts matrix, and perform basic QC with scanpy. Then, do further processing by making a UMAP and clustering. Produces a processed AnnData Depreciated: use individual workflows insead for multiple samples
Takes fastqs and reference data, to produce a single cell counts matrix into and save in annData format - adding a column called sample with the sample name.
Take a scRNAseq counts matrix from a single sample, and perform basic QC with scanpy. Then, do further processing by making a UMAP and clustering. Produces a processed AnnData object.
Depreciated: use individual workflows insead for multiple samples
From the R1 and R2 fastq files of a single samples, make a scRNAseq counts matrix, and perform basic QC with scanpy. Then, do further processing by making a UMAP and clustering. Produces a processed AnnData
Depreciated: use individual workflows insead for multiple samples
Basic processing of a QC-filtered Anndata Object. UMAP, clustering e.t.c
Take an anndata file, and perform basic QC with scanpy. Produces a filtered AnnData object.
Takes fastqs and reference data, to produce a single cell counts matrix into and save in annData format - adding a column called sample with the sample name.
Loads a single cell counts matrix into an annData format - adding a column called sample with the sample name. (Input format - matrix.mtx, features.tsv and barcodes.tsv)
pod5_by_pore
A Snakemake workflow to take the POD5 files produced by an Oxford Nanopore sequencing run and re-batch them by pore (ie. by channel).
This is useful if you want to run duplex basecalling because you can meaningfully run "dorado duplex" on a single (or a subset of) the POD5 files.
Know issues
It is assumed all POD5 input files are from the same sequencing run, but this is not checked.