I have noticed that a fair number of people who actually work with Next-Gen Sequence data read this blog, so perhaps we can use it for a collaborative project.
I want to write a paper about uneven coverage in exome sequencing leading to incorrect SNP calls. Our data is from tumor-normal pairs, and we see a lot of false negatives - failure to detect a SNP in a sample due to low coverage at that spot. Exome capture methods seem to have more than their fair share of low coverage spots (even with an average coverage over 100x), and these low coverage spots do differ somewhat from sample to sample. I'd like some other people to share data with us and/or do some similar analysis on other data sets so that we can make a stronger paper.
TRUmiCount – Correctly counting absolute numbers of molecules using unique molecular identifiers - Counting molecules using next-generation sequencing (NGS) suffers from PCR amplification bias, which reduces the accuracy of many quantitative NGS-based ex...
11 hours ago