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Differential expression at transcript level #235
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Hey Fernando, you should definitely be able to run the pipeline on rnaseq output, but unless you share some information about your command and the input files you used as well as the error message you received, I'm afraid I won't be able to help... |
I am also interested in this. with Now if you try to plug in this table + the lengths into differentialabundance it fails on validation:
because the feature_id_col should not be 'gene_id', but 'tx' for this input table Is there a way to set this parameter? |
Okay, so setting
made the validation succeed because features_id_col is used:
the following filter step seems to work, yielding such a table:
but it still dies on the DESeq2 process, likely because that still looks for a 'gene_id' column in the table,
Ideas? |
Got it to work by renaming the column names in the counts table, lengths table AND annotation, such that the column containing the transcript_id is (wrongly) called 'gene_id' renaming:
running:
Output obviously has 'Gene ID' column name even though they are transcript ids. Ideally there would be a way to properly parameterize which columns to use (in validation, filtering, and DESeqing) AND how to generate the annotation from the gtf Please consider implementing it - would be a cool feature to be able to directly use transcript abundances from nf-core/rnaseq Best |
Hey there!
Yep...I noticed that as well some time ago, that's a silly little bug. It's already fixed on the dev branch, so if you run that code it should work. The necessary id_col parameters should already be in the pipeline :) (There's quite a few of them unfortunately, but all of them are described on https://nf-co.re/differentialabundance/1.4.0/parameters) |
Description of feature
Hello,
First of all, congratulations on your pipeline for differential abundance. I'm trying to perform a differential expression analysis at the transcript level, but I can't seem to get it to work. I've tried different parameters and input files, but I'm not succeeding. The data comes from the output of the nf-core/rnaseq pipeline. Is it possible to carry out such an analysis?
Thanks,
Regards.
Fernando
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