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Old 08-22-2017, 03:03 AM   #1
sudders
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Location: Sheffield, UK

Join Date: Dec 2011
Posts: 32
Default UMI-Tools version 0.5: now with tools for cell barcoded scRNA-seq

We are proud to announce the release of UMI-Tools 0.5.

UMI-tools provides error aware tools for dealing with short random oligos (Unique Molecular Identifiers/Random Molecular Tags).

The novel, error corrected UMI deduplication algorithm was published here. We provide tools to group, deduplicate or count reads by the UMIs.

Find us on PyPI, conda or here: https://github.com/CGATOxford/UMI-tools

General walk-through

Droplet-barcoded single cell RNA-seq walk-through

Version 0.5

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.. 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.

count_tab - As per count but works from a flatfile input from e.g featureCounts
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.

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

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

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.

Drop us a line here, on twitter (@IanSudbery) or on Github if you need further help or advice.
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