fastqc - Multiplex barcodes or other adaptors polluting reads?

[jimineep]

Hi all,

This is my first post and potentially a very obvious question so please be gentle!

I have had 12 samples sequenced, on an Illumina GA machine, using triplexing.

I ran fastqc and notice exactly the same pattern in the per-base sequence content and per-base gc content for the first 12 or 13 bases for each sample.

At first I thought it could be the barcodes used to identify the different samples in the multiplexing but then that wouldn't explain why the pattern is identical for all samples, even though the samples would have different barcode sequences.

Any idea what could be causing this? my guess is something to do with the adaptor sequences. And is the best way to look for overrepresentation of reads with a given sequence at the beginning in the fastq file and delete this?

Many thanks in advance for any advice you can give on the matter.

J

[kmcarr]

Hi all,

This is my first post and potentially a very obvious question so please be gentle!

I have had 12 samples sequenced, on an Illumina GA machine, using triplexing.

I ran fastqc and notice exactly the same pattern in the per-base sequence content and per-base gc content for the first 12 or 13 bases for each sample.

At first I thought it could be the barcodes used to identify the different samples in the multiplexing but then that wouldn't explain why the pattern is identical for all samples, even though the samples would have different barcode sequences.

Any idea what could be causing this? my guess is something to do with the adaptor sequences. And is the best way to look for overrepresentation of reads with a given sequence at the beginning in the fastq file and delete this?

Many thanks in advance for any advice you can give on the matter.

J

J.

You are obviously running RNASeq libraries which have been prepared using the standard Illumina RNASeq (TruSeq) kit. This pattern is entirely normal for Illumina RNASeq. Search this form some more and you will find a number of threads discussing it.

[mnkyboy]

This is completely normal, it is also advisable to trim the first read from these random hexamer primed RNA-seq libraries due to its high error.

[BAMseek]

I have also noticed similar distributions in various datasets I have seen. I did as the previous posters suggested and searched for "hexamer" in SeqAnswers and found some good threads.

This is completely normal, it is also advisable to trim the first read from these random hexamer primed RNA-seq libraries due to its high error.

mnkyboy - could you explain a little more about what you think needs to be trimmed? Are there higher error rates at the 5' end of the read that need to be addressed?

thanks!

[mnkyboy]

With the random hexamer priming with Illumina TruSeq RNA kits the first base is high error and their simple recommendation to fix this is to trim it. This was something they presented recently at a users group meeting.