Single nucleotide variants detection using RNA-Seq is subject to high false positive rates

High throughput sequencing technology enables the both the human genome and transcriptome to be screened at the single nucleotide resolution. Tools have been developed to infer single nucleotide variants (SNVs) from both DNA and RNA sequencing data. To evaluate how much difference can be expected between DNA and RNA sequencing data, and among tissue sources, Vanderbilt University researchers designed a study to examine the single nucleotide difference among five sources of high throughput sequencing data generated from the same individual, including exome sequencing from blood, tumor and adjacent normal tissue, and RNAseq from tumor and adjacent normal tissue.

Through careful quality control and analysis of the SNVs, they found little difference between DNA-DNA pairs (1%-2%). However, between DNA-RNA pairs, SNV differences ranged anywhere from 10% to 20%.

 Genotype consistencies between any two pairs of sequencing data


Only a small portion of these differences can be explained by RNA editing. Instead, the majority of the DNA-RNA differences should be attributed to technical errors from sequencing and post-processing of RNAseq data. Our analysis results suggest that SNV detection using RNAseq is subject to high false positive rates.

Guo Y, Zhao S, Sheng Q, Samuels DC, Shyr Y. (2017) The discrepancy among single nucleotide variants detected by DNA and RNA high throughput sequencing data. BMC Genomics 18(Suppl 6):690. [article]

One comment

  1. This paper provides a very detailed comparative analysis of differences between variants found from DNAseq and RNAseq data however the conclusion is disputable at best. Without any wet lab validation there is no biological evidence porvided to supports authors conclusion i.e.”that SNV detection using RNAseq is subject to high false positive rates.”

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