Hi Charles

Thanks for replying and clarifying a few things.

Just so I'm straight, I can use debarcode to add the UMIs from fastq read file #1 into the read header of fastq read file #2.

I would then align to a genome to generate a bam, then use retag to switch the UMI from the read header to the RX position in the bam - then I'd be able to use picard to dedup with the RX barcode_tag. Feasibly, once the UMI is added to the header, I could still use the current je-markdupes to dedupe (it being a fork of picard)?


Previously, I've been using fgbio, but this involved aligning the data in Galaxy, exporting it and annotating with UMI's and then loading back in. Ideally, we'd like to keep the entire workflow within Galaxy (hence the original question).


Tony


From: Charles Girardot <charles.girardot@embl.de>
Sent: 27 March 2018 22:25:57
To: Brooks, Tony
Cc: galaxy-dev@lists.galaxyproject.org; Jelle Scholtalbers
Subject: Re: [galaxy-dev] Best practices for utilising Unique Molecular Indexing (UMI's)
 
Hi Tony,

please see inline answers

> On 27. Mar 2018, at 16:45, Brooks, Tony <a.brooks@ucl.ac.uk> wrote:
>
> Hi Charles
> Thanks for replying. Yes, I'd definitely be interested in the command line version.

we’ll try to push the version we have in conda tomorrow.


> I'm assuming I can use je retag to add the UMI from a separate read to my sample fastq (already demultiplexed by bcl2fastq) then use the de-markdupes already in Galaxy to dedupe? Would this work?

I think you got me wrong (or I got you wrong!): je retag lets you transfer UMI/BARCODE information embedded in the read name of a *bam* file to proper bam BC/RX/QX/OX/BZ/MI tags. Indeed many tools (will) expect this info to be available in BAM tags and not in read names.

The current version of je markedupes expects the UMI info in the read name. We havent updated  je markedupes to get this info from BAM tags yet (even in je-suite2, not fully ready as mentioned before)

> Btw, I did find a small bug in markdupes. On the NextSeq, the fastq header contains a space, e.g.
>
> @NS500195:396:HLMM5BGX5:1:11101:2331:1043 1:N:0:GCCAAT
>
> When I run markdupes, I get an error as it thinks the UMI is "1043", not "GCCAAT”.

read names in BAM files can’t have spaces so the read name in your BAM is likely to be :

@NS500195:396:HLMM5BGX5:1:11101:2331:1043

and by default, the UMI is expected in the last position ; hence '1043'

Please double check how the read names look in your bam file.

Best

Charles

>

> Thanks
> From: Charles Girardot <charles.girardot@embl.de>
> Sent: 26 March 2018 12:05:22
> To: Brooks, Tony
> Cc: galaxy-dev@lists.galaxyproject.org
> Subject: Re: [galaxy-dev] Best practices for utilising Unique Molecular Indexing (UMI's)
> 
> Hi Tony,
>
> sounds like you need is the Je-Suite version 2 which we will release soon-ish.
>
> In this version, the new “je debarcode” module allows you to define an unlimited number of FASTQ input together with their layout (describing BARCODE, UMI and SAMPLE positions). One can define an unlimited number of output FASTQ  layouts  by combining the BARCODE, UMI and SAMPLE slots defined in input layouts (one slot can be written in multiple layouts if need be). For example, you can output the UMI in their own separate file instead of/in addition to keeping them in the read header.
>
> This version also let you keep the demultiplexed reads in a single output file (for single end I mean), map this file to the genome then use the new “je retag”  to transfer the BARCOD/EUMI info embedded in read header to proper BAM tags. This should make it easier to deal with single-cell datasets i.e. manipulate a unique file instead of hundreds/thousands…
>
> The command line version is close to completion (“je retag” needs a bit more testing) and I believe we could push this in conda rather quickly. The bad news is we haven’t started to write/update the Galaxy wrappers yet.
>
> Let me know if you are interested to try the command line version.
>
> Best
>
> Charles
>
>
>
> > On 26. Mar 2018, at 11:45, Brooks, Tony <a.brooks@ucl.ac.uk> wrote:
> >
> > Hi
> > We are currently seeing a number of methods that are utilising the power of unique molecular indexing. Unfortunately, there is no consensus on how libraries should be configured, and therefore no consensus for how to deal with them within Galaxy.
> > 
> > Often libraries that have the UMI placed directly downstream of the first (i7) index, such as ones using the IDT xGen adapter set
> > (https://www.idtdna.com/pages/products/next-generation-sequencing/adapters/xgen-dual-index-umi-adapters-tech-access). Sometimes UMI’s exist in place of the second (i5) index (https://www.neb.com/nebnext-direct/nebnext-direct-for-target-enrichment).
> > 
> > In both cases, the recommended workflows are convoluted and all the necessary tools do not currently exist in the toolshed (so that the datasets need to be taken out of galaxy, processed and reloaded).
> > It is possible to use bcl2fastq to output the UMI as an additional fastq file, but this would then require me to create a dataset triplicate (not pair) which afaik we can’t do (yet).
> > 
> > A quick Google/toolshed search had me find UMI-Tools & Je-Suite which both exist in Galaxy.
> > Both these tools assume the UMI is “in-line” (i.e. at the beginning of the read 1 or read2 – not its own read), extract/remove the UMI and place it in the read header, where it is then used further down the line to dedup the bam file.
> > 
> > Does anyone know of any tools that would take the UMI from a separate fastq and use it to tag the headers of actual read data. Or alternatively, a tool that will paste the UMI tag onto the 5’ end of the read fastq? And whether these steps can be done within Galaxy, or maybe prior to fastq upload?
> > 
> > Anyone have a method/workflow for UMI’s?
> > 
> > Thanks in advance
> > Tony
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> =====================================
> Charles Girardot
> Head of Genome Biology Computational Support (GBCS)
> and Senior Bioinformatician in the Furlong Lab
> European Molecular Biology Laboratory
> Tel: +49 6221 387 -8585
> Fax: +49-(0)6221-387-8166
> Email: charles.girardot@embl.de
> Skype: charles_girardot
> Web : http://gbcs.embl.de
> Room V205
> Meyerhofstraße 1,
> 69117 Heidelberg, Germany
> =====================================

=====================================
Charles Girardot
Head of Genome Biology Computational Support (GBCS)
and Senior Bioinformatician in the Furlong Lab
European Molecular Biology Laboratory
Tel: +49 6221 387 -8585
Fax: +49-(0)6221-387-8166
Email: charles.girardot@embl.de
Skype: charles_girardot
Web : http://gbcs.embl.de
Room V205
Meyerhofstraße 1,
69117 Heidelberg, Germany
=====================================