Trimmomatic - To trim the low quality reads
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10 months ago

I am using trimmomatic to improve the quality of my sequenced reads, I used the following code.

java -jar $EBROOTTRIMMOMATIC/trimmomatic-0.39.jar PE Chester-cf_S1_L001_R1_001.fastq.gz Chester-cf_S1_L001_R2_001.fastq.gz Chester-cf-paired-R1_001.fastq.gz Chester-cf-unpaired_S1_L001_R1_001.fastq.gz Chester-cf-paired-R2_001.fastq.gz Chester-cf-unpaired_S1_L001_R2_001.fastq.gz LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:46

Even after using this, the per base sequence content and per base GC content did not improve it showed a failed sign in QC report. Can some please help with how to improve the sequence content , GC content and sequence length distribution (warning sign) of my reads.

Trimmomatic • 735 views
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it showed a failed sign in QC report

Failed tests in FastQC need to be considered in context of the experiment. A "failure" does not necessarily mean the data is bad. Post screenshots and tell us about that kind of data this is.

Good blog posts about various test in FastQC from the authors here: https://sequencing.qcfail.com/software/fastqc/

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Screen shot of my report

Per tile sequence quality

I am performing next generation sequencing analysis of DNA of dogs, I am comparing cell free DNA with tumor DNA and gnomic DNA (de novo sequencing). Could you please guide with this results.

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I don't see anything of immediate concern in these plots. You were referring to GC differences but I guess you did not include that plot. I would say go ahead with the rest of your analysis. If there is a problem with the data it would become obvious with alignment.

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Thanks for the advice. I am performing denovo genome assembly with this reads using ABySS, is that okay to run these reads without any further processing?

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As long as you are sure that there is no "extraneous" sequence (not belonging to your sample of interest) it should be fine to proceed. By trying to normalize "GC" distribution you may end up throwing sequence away that actually belongs in your sample.

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Thank you very much. I will proceed with this data.

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