Hi there, I'm trying to implement grouping of samp...
# multiqc
l
Hi there, I'm trying to implement grouping of samples, but I'm not able to expand the row in the general stats. Likely, because I have the columns duplicated, but also not sure how to solve this. My config file:
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extra_fn_clean_exts:
    - '_R1'
    - '_R2'
    - '.sorted'

fn_clean_exts:
  - ".txt"
  - ".bz"
  - ".gz"
  - ".fastq"
  - ".fastq.gz"

table_sample_merge:
  "Read 1, raw": "_raw_1"
  "Read 1, trim": "_trim_1"
  "Read 2, raw": "_raw_2"
  "Read 2, trim": "_trim_2"
  "Single-end, raw": "_raw"
  "Single-end, trim": "_trim"
I hope you have some input 🙂 Thanks, Lucille
p
What is it that you're expecting here? The two different datasets showing as a single row?
If so then
table_sample_merge
needs to resolve them into a single shared sample name, so handle the
01
and
02
suffixes
Otherwise I wonder if you mean that the rows are showing properly but the underlying data isn't visible? In which case it's likely because you're merging the samples already in
extra_fn_clean_exts
and so by the time it gets to
table_sample_merge
you only have one value
Side note:
extra_fn_clean_exts
and
fn_clean_exts
do the same thing. It's just that the latter clobbers the defaults and the former appends to them.
If it's the second thing then try just removing the
extra_fn_clean_exts
and
fn_clean_exts
config sections
l
Thanks for the reply. After removing
extra_fn_clean_exts
and
fn_clean_exts
the report looks the same. For each dataset I have forward and reverse reads + trimmed version, I was expecting these to show as expanded rows per. dataset and not in multiple columns (eg. 4 x "CG")
p
oh I see, I didn't notice the multiple columns before sorry
weird, are you able to share a minimal reproducible example that I can run myself please?
l
multiqc_test.tar.gz
Maybe you're able to see it from here? 🙂
p
Apologies, ran out of time to look at this on Monday and not much better now. Could you put this into a post on community.seqera.io/multiqc so that others can have a look?
👍 1