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@TomSmithCGAT TomSmithCGAT released this 18 Aug 15:38
· 349 commits to master since this release

Version 0.5.0 introduces new commands to support single-cell RNA-Seq and reduces run-time. The underlying methods have not changed hence the minor release number uptick.

UMI-tools goes single cell

New commands for single cell RNA-Seq (scRNA-Seq):

  • whitelist - Extract cell barcodes (CB) from droplet-based scRNA-Seq fastqs and estimate the number of "true"
    CBs. Outputs a flatfile listing the true cell barcodes and 'error' barcodes within a set distance. See #97 for a motivating example. Thanks to @Hoohm for input and patience in testing. Thanks to @k3yavi for input in discussions about implementing a 'knee' method.

  • count - Count the number of reads per cell per gene after de-duplication. This tool uses the same underlying methods as group and dedup and acts to simplify scRNA-Seq read-counting with umi_tools. See #114, #131

  • count_tab - As per count but works from a flatfile input from e.g featureCounts - See #44, #121, #125

In the process of creating these commands, the options for dealing with UMIs on a "per-gene" basis have been re-jigged to make their purpose clearer. See e.g #127 for a motvating example.

To perform group, dedup or count on a per-gene, basis, the --per-gene option should be provided. This must be combined with either --gene-tag if the BAM contains gene assignments in a tag, or --per-contig if the reads have been aligned to a transcriptome. In the later case, if the reads have been aligned to a transcriptome where each contig is a transcript, the option --gene-transcript-map can be used to operate at the gene level. These options are standardised across all tools such that one can easily change e.g a count command into a dedup command.

Updated options:

  • extract - Can now accept regex patterns to describe UMI +/- CB encoding in read(s). See --extract-method=regex option.

We have written a guide for how to use UMI-tools for scRNA-Seq analysis including estimation of the number of true CBs, flexible extraction of cell barcodes and UMIs and per-cell read-counting as well as common workflow variations.

Reduced run-time (#156)

Introduced a hashing step to limit the scope of the edit-distance comparisons required to build the networks. Big thanks to @mparker2 for this!

Simplified installation ( #145 )

Previously extensions were cythonized and compiled on the fly using 'pyximport, requiring users to have access to the install directory the first time the extension was required. Now the cythonized extension is provided, and is compiled at install-time.