paperKB
coga / coga-kb
Help
Sign in

Chunk #8 — 1 INTRODUCTION — 1.3 Related work

Source
SNVMix: predicting single nucleotide variants from next-generation sequencing of tumors.
Embedded
yes

Text

33% of all reads at that site. This should eliminate SNVs with weak supporting evidence, but it categorizes the data into two discrete classes—SNV or not, without explicitly providing confidence estimates on the prediction. Moreover, in transcriptome data, the number of reads representing a given transcript expected to be highly variable across all genes and thus determining a minimum depth can be difficult. We demonstrate (Section 3) that applying depth-based thresholds reduces sensitivity to finding real SNVs.