PacBio raw data trimming and cleaning
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5.9 years ago
misterie ▴ 110

Hi,

I have done analysis of QC using FastQC for my PacBio data. I am wondering whether should I clean my data by quality criterion or minimum length of read. Those data are very poor (PacBio). Do you know any recommendation how to clean those data? For Illumina I used to use Trimmomatic, CutAdapt and TrimGalore, but I have no idea how to pre-process PacBio data. I think I should remove reads shorter than 50 bp, but if you have any other recommendation for those purposes, let me know.

pacbio trimming cleaning qc • 5.0k views
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Things like this usually depend on the application you want to do after cleaning. Do you want (structural) variant calling, de novo assembly,...?

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I want to do de novo assembly using different pipelines. But I think I should at least trimm my data using minimum length =50bp

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Since you are working with PacBio data I personally think it's a bit silly to use a lower bound of only 50 nucleotides. Depending on your read length distribution I would go for at least 10fold of your 50n threshold.

On the other hand most PacBio processing pipelines will already apply an internal min length filtering (mostly around few Kbp).

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Thank you. I mean mainly, that I have some samples after demultiplexing using lima and standard (default) threshold for minimum length was set to 50 Bp. I have also samples that do not require demultiplexing so there are reads that have minimum length = 1bp. I want to uniform those samples. If it could be better to change threshold to 500bp let me know which software will be appropriate.

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it all depends on what the analyses are you want to do with the data.

eg. assembly: most assemblers will either do 'cleaning' themselves or do no quality cleaning at all

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