Blog:Salmon Kallisto HtSeq-count for gene level analysis - Anecdotal evidence
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6.3 years ago
Ido Tamir 5.2k

With the new tools I was again unsure on how to proceed and I could not give my customers 3 different results and tell them to choose the one they like best. So I did an unscientific study based on one dataset to devise a strategy and judge the differences.

I would be glad if other people do similar things more systematically, especially add the two methods to Seqc (this one http://www.bioconductor.org/packages/release/data/experiment/html/seqc.html or that one https://bitbucket.org/soccin/seqc ) or simply post their opinion or experiences.

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RNA-Seq kallisto salmon htseq-count Blog • 2.6k views
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Hi Ido,

  I was wondering if you could mention the versions of these software you used.  In particular, there have been substantial improvements in Salmon v0.4.0, and I wonder if this analysis was performed with an older version (and how difficult it would be to replicate with the new version).

Thanks,

Rob

 

 

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Not good at all. Now the results are very similar ;-).

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Good point, I added some version info.

Salmon (0.3.0) I have from the binary you provided. I have this old system where I cant compile anything new, so I would need a binary.

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Thanks for the update!  Actually, v0.3.0 is a few releases behind.  The development of salmon has moved to it's own repository (sorry; I should announce this on the user-list!).  The binaries for v0.4.0 are available here.  In particular, the "DebianSqueeze" binary is built on a VM of a fairly old version of Debian so, hopefully, it will work on your machine.  I'd be interested to see how this changes the analysis!

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thanks.

I think there is some debug output enabled in the squeeze version. I get megabytes of:

expected = Library format { type:single end, relative orientation:none, strandedness:antisense }
observed = Library format { type:single end, relative orientation:none, strandedness:sense }
expected = Library format { type:single end, relative orientation:none, strandedness:antisense }

....

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Hrmm --- I can certainly take care of this, but what is the library type?  It looks like you're providing `-l SR` (single-end, with the read coming from the antisense strand) and it's expecting either `-l U` (single-end, unstranded) or `-l SF` (signle-end, with the read coming from the sense strand).
 

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The data is single end coming from the antisense strand. i.e. standard UTP protocol as indicated in the plots in the blog post. I provide -I SR. The mapping rate looks ok. One problem is that now I get a core dump for the genes (same input as 0.3.0). I posted in the sailfish-google group.

# salmon (smem-based) v0.4.0
# [ program ] => salmon
# [ command ] => quant
# [ threads ] => { 4 }
# [ libType ] => { SR }
# [ unmatedReads ] => { /groups/csf-ngs/projects/20140428_jurkin_diffexp/data/fasta/henkel/C6A1GANXX_1#23728_TGACCA.1.fastq }
# [ index ] => { /groups/csf-ngs/projects/20140428_jurkin_diffexp/data/salmon/human/Homo_sapiens.GRCh38 }
# [ extraSensitive ] => { }
# [ biasCorrect ] => { }
# [ geneMap ] => { /groups/csf-ngs/projects/20140428_jurkin_diffexp/data/salmon/human/Homo_sapiens.GRCh38.79.chr.gtf }
# [ output ] => { /groups/csf-ngs/projects/20140428_jurkin_diffexp/results/salmon/henkel/C6A1GANXX_1#23728_TGACCA }
# [ mapping rate ] => { 86.8205% }
# Name    Length    TPM    NumReads
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Hi Ido,

  Thanks for reporting this.  I've disabled the "annoying" reporting of the unexpected fragment orientation, and fixed (I believe) the bug you ran into with the post-hoc bias correction.  I've updated the binary on GitHub and responded to your post on the sailfish-google group (thanks for posting there).  Let me know if the new release resolves this issue, and I'll roll those changes into a v0.4.1 bump.

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