In the library preparation for a NGS experiment, it is customary to bind adapter sequences. Ironically, these addendum may contribute to the contamination in the data that is headed for computational analysis, and might often present deceptive outcomes.
In an exceptional case of a paired-end data, I found no overrepresented or repeated sequences. Even more tantalizing was the fact that in a corresponding sample(again paired-end), there were overrepresented sequences in each reads, that were differently sourced. The scenario is as follows:
One of the reads I4_R1.fastq has the following attribute,
>>Overrepresented sequences warn
#Sequence Count Percentage Possible Source
AGATCGGAAGAGCACACGTCTGAACTCCAGTCACGCCAATATCTCGTATG 36771 0.14170337546219017 TruSeq Adapter, Index 6 (100% over 49bp)
GATCGGAAGAGCACACGTCTGAACTCCAGTCACGCCAATATCTCGTATGC 36534 0.14079005518304247 TruSeq Adapter, Index 6 (100% over 50bp)
>>END_MODULE
while the other, I4_R2.fastq has the following:
>>Overrepresented sequences warn
#Sequence Count Percentage Possible Source
AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGATCTCGGTGGTCGCC 37938 0.14620061076077806 Illumina Single End PCR Primer 1 (100% over 50bp)
GATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGATCTCGGTGGTCGCCG 35122 0.1353486702287956 Illumina Single End PCR Primer 1 (100% over 50bp)
>>END_MODULE
I would like to hear some opinions.
Thanks.
Dear Dr. Shaurya Jauhari,
Generally speaking, after a NGS sequencing, the core facility usually treats the samples and depletes the adapters. As the process is imperfect, they strongly recommend an ad hoc bioinformatic trimming of those sequences by the researcher.
Chances are that usually there are adapters in the sample, an they should be trimmed (p.e. with Trimmomatic). It might be possible a case such as yours, with no adapters.
A part, I recommend to check it with another program, or to trim the adapter sequences with Trimmomatic (adding those adapters in the built-in list, in case they are not listed yet) and check if there are mayor differences between the pre-treated sample and the post-treated sample.
In any case, it is good to mistrust any unexpected result, specially with sequencing and bioinformatics.
Let us know how it advances.
Cheers
JMC
http://www.usadellab.org/cms/index.php?page=trimmomatic
According to me, that should not be the case. I mean it's not usual at least. I recommend to try different programs to check QC. If it helps, you can go through this book chapter of mine for different tools.
https://link.springer.com/chapter/10.1007/978-94-024-1045-7_10
https://link.springer.com/chapter/10.1007/978-94-024-1045-7_10
I agree with Pallavi, it is totally okay, but if you're unsure, try out a few different RNA-Sequence Programs to check QC
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