assessing data quality of matched samples from RNA-seq and WGS
HI,
how to assess data quality of a cohort of samples with matched RNA-seq and WGS data (with different sequencing depths)??
I found NGSCheckMate software but I could not get if this tool only the defines outliers or what.
Thanking you in advance
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Why not use FastQC/MultiQC? Quality in what terms? Raw data/alignments/DE results?
Thank you, I was ask this question. I think they mean assessing quality of data in matched samples in RNA-seq and WGS to eliminate platform-spesific biases from raw data
If you have matched RNA-seq and WGS you could do variant calling on both and see how well the variants correspond, but keep in mind that RNA-seq is not really the most optimal tool for variant calling due to the VERY uneven expressionpatterns.
[I edited your title to make it more specific]
Thank you, the goal is exploring transcriptional patterns underlying genomic alterations.
In that case, I don't think it makes a lot of sense to assess their quality together, but just per dataset. Doing variant calling could tell you no swapping/contamination has happened.
I found NGSCheckMate to check the samples being matched between WGS and platforms.