How does this work?

[evolgenomology]

Hi guys,

unfortunately I really have some problems understanding how the pipeline can be adapted to our dataset. For some initial tests I wanted to use bc_demultiplex.py, but I don't understand how the sample sheet should look and how the files need to be named. So to start from the beginning.
We have 5 libraries (of ~20 tissue slices each, but I guess this is irrelevant), which were pooled and sequenced all together on a HiSeq. We used barcodes:

Primer_ID | Unique Barcode
1 | AGACTC
2 | AGCTAG
4 | AGCTTC
5 | CATGAG
9 | CAGATC
10 | TCACAG
11 | AGGATC
14 | TCCTAG
17 | TCGAAG
20 | GTACAG
23 | GTCTAG
25 | GTTGCA
26 | GTGACA
28 | ACAGTG
29 | ACCATG
31 | ACTCGA
32 | ACGTAC
35 | CTAGAC
40 | CTTCGA
46 | TGCAGA

and also UMIs of course.
What we got is 5 Illumina datasets, Lib_1 ... Lib-5, and each has two readsets, e.g.
Lib-2_S2_L002_R2_001.fastq.gz Lib-2_S2_L001_R1_001.fastq.gz Lib-2_S2_L001_R2_001.fastq.gz Lib-2_S2_L002_R1_001.fastq.gz.
I cleaned these with trimmomatic (I think this is necessary in this case, since the sequencing quality is not really super. My reads are now named, e.g.
Lib-4_S4_L002_reverse_paired.fq.gz Lib-4_S4_L002_forward_paired.fq.gz Lib-4_S4_L001_reverse_paired.fq.gz Lib-4_S4_L001_forward_paired.fq.gz.
But this can of course be changed.

Now my simple questions are:

• how do I need to layout the bc_index file? (I suspect like the barcode_umis.tab file, right?)
• how do I need to layout the sample sheet?
• would it make sense to just combine all reads into one giant fastq file?

Thanks for your help!

Cheers

Philipp

[evolgenomology]

I realised that at least this "would it make sense to just combine all reads into one giant fastq file?" would not make sense.

[Puriney]

This is to visualize the sample sheet as defined here

A good news is that we are going to release a new version of pipeline next week.