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Salmon strand inference is often wrong #1185
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Hi there, I'm seeing behaviour, which could be similar to your issue, in data I received from several collaborators. The logs show for example: When I look in detail at the
Results like these are not covered by the examples in the rseqc docs on infer_experiment.py. I was wondering:
Regards |
Hi, thank you for posting these questions! I would love to hear from either of you, if you have any further thoughts on the issue! I too am getting similar warnings across the board. In all cases, salmon marks the experiment samples as "reverse" and infer_experiment.py identifies something like 28% reverse and 75% undetermined. Do you think I should be concerned, or proceed ahead trusting the salmon identification? Thank you! |
The reason this comes up is because the auto strand setting comes from Salmon based on its pseudo-alignment against transcript sequences, while the final strandedness check is based on genomic alignments and RSeQC's assessment. The main source of the discrepancy is the reads of undetermined strand in RSeQC which play a part in the the assessment the pipeline makes bases on those statistics, and (possibly) shouldn't. I've opened the above PR to discuss and/ or address this. |
Tackled in #1306 |
Wanted to revive this thread for a moment if possible. I have recently ran the rnaseq pipeline on some publicly available data, and based off of the change in #1306 it seems to me that my data likely has a large amount of potentially genomic DNA contamination. I expect antisense strandedness but am seeing 15-24% sense, 65-70% antisense, and 15-20% undetermined. Based on that distribution I expect that the samples are likely of poor quality? If that is the new understanding from the fix then is there any way to continue working with this data? Or is that simply too low of quality? Also since the inferred strandedness is unstranded (likely due to the high sense and undetermined combined percentage) would the alignment be off, meaning that I need to re-run the pipeline changin auto strandedness to unstranded? Thanks for any help on this! |
Description of feature
Hi,
Thanks for all the work on this pipeline.
I have had to analyse several public datasets, and I plan to analyse more. Since the strandedness on such datasets is usually not provided, I use the
"strandedness: auto"
option in the pipeline to guess it.Quite often (apologies for not having statistics about that, I could try to get some if needed) I get
"WARNING: Fail Strand Check"
messages, and I find that Salmon had set the strandedness to "reverse" wheninfer_experiment.py
founds it to be "unstranded".When this happens, I set the strandedness to "unstranded" and rerun the pipeline.
Would it make sense for the pipeline to just reset the strandedness and rerun automatically?
Thanks again
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