Mining RNA-seq data for infections and contaminations.

ABSTRACT: RNA sequencing (RNA-seq) provides novel opportunities for transcriptomic studies at nucleotide resolution, including transcriptomics of viruses or microbes infecting a cell. However, standard approaches for mapping the resulting sequencing reads generally ignore alternative sources of expression other than the host cell and are little equipped to address the problems arising from redundancies and gaps among sequenced microbe and virus genomes. We show that screening of sequencing reads for contaminations and infections can be performed easily using ContextMap, our recently developed mapping software. Based on mapping-derived statistics, mapping confidence, similarities and misidentifications (e.g. due to missing genome sequences) of species/strains can be assessed. Performance of our appro

SUBMITTER: Bonfert T 

PROVIDER: S-EPMC3760913 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature