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-t and -tf parameters #21

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AndreaAguadoM opened this issue Jun 17, 2022 · 4 comments
Open

-t and -tf parameters #21

AndreaAguadoM opened this issue Jun 17, 2022 · 4 comments

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@AndreaAguadoM
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Hello, my name is Andrea and I am a bioinformatician who is currently working with SARS-CoV-2 sequences in order to identify quasispecies within given samples. I have been trying to use CliqueSNV so as to achieve this goal, but I've been having some issues. When selecting the -tf parameter, I do not completely understand its relation with the -t parameter. I have understood it is related with the coverage, meanwhile -t is related to frequency. The issue resides in the fact that have been using this tool with -t value set in 0.01 and the -tf value set in different values (from 20 to 150) but I do not get much better results when changing this last value. Obtained sequences seem not to differ much in the different experiments, so this is been such an issue within my study.

Could someone help me?

Thanks in advance!!

@jpflorido
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Same here, do not understand the purpose of -tf argument when used together with -t
Thanks!
Javier

@Sergey-Knyazev
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Dear Andrea and Javier,

These two parameters work similarly, however, -t is crucial for genome fragments with low coverage and is required for reliability of detection of SNV pairs. The parameter -tf is introduced for some of our users, who asked to restrict the output of rare variants.

Thank you!
Sergey

@AndreaAguadoM
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AndreaAguadoM commented Jul 12, 2022 via email

@Sergey-Knyazev
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Hi Andrea,

To get the mutations, you could use --snv-illumina-vc option. But take in mind that it calls the mutations that appear in the same reads simultaneously by pairs (see the article Picture 1, Step 1). The method gives high reliability of calling such mutations even if their frequencies are bellow the error rate (see Methods). For other mutations, you could use samtools, but if you would like to call them reliably, you could want to use high threshold value. You probably would also like to pay attention for the quality of the alignment because we saw that errors in alignment bring detection of false positive mutations.

Thank you!
Sergey

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