HI all, this is my first post so apologies if its inappropriate - its a pretty simple question but I need a little help. I promise I've googled far and wide to try and figure it out myself.
I use short reads from a Miseq to make clinical variant calls using GATK. I use various panels (trusight cancer etc). Some exons/genes always have low coverage (due to GC content etc) and others just fail in one sample, which is often clinically relevant.
I would like to compare the mean coverage of each exon/gene in each sample to the same from a 'gold standard' derived of what my lab scientist tell me is a 'good run'. Currently I am doing a ttest with the mean of the gold compared to the read depths at each base in the exon/gene that I am doing variant calling on. Basically, I only want to know if the mean read depth is low if it is significantly different to the mean of the gold.
It made sense at first because I am comparing 2 means. Is that right? It seems wrong because I'm really only comparing two samples. So I though I should do a Z test...
Has anyone done anything similar? How did you implement it?
I use short reads from a Miseq to make clinical variant calls using GATK. I use various panels (trusight cancer etc). Some exons/genes always have low coverage (due to GC content etc) and others just fail in one sample, which is often clinically relevant.
I would like to compare the mean coverage of each exon/gene in each sample to the same from a 'gold standard' derived of what my lab scientist tell me is a 'good run'. Currently I am doing a ttest with the mean of the gold compared to the read depths at each base in the exon/gene that I am doing variant calling on. Basically, I only want to know if the mean read depth is low if it is significantly different to the mean of the gold.
It made sense at first because I am comparing 2 means. Is that right? It seems wrong because I'm really only comparing two samples. So I though I should do a Z test...
Has anyone done anything similar? How did you implement it?
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