Systematic bias in high-throughput sequencing data and its correction by BEADS.

ABSTRACT: Genomic sequences obtained through high-throughput sequencing are not uniformly distributed across the genome. For example, sequencing data of total genomic DNA show significant, yet unexpected enrichments on promoters and exons. This systematic bias is a particular problem for techniques such as chromatin immunoprecipitation, where the signal for a target factor is plotted across genomic features. We have focused on data obtained from Illumina's Genome Analyser platform, where at least three factors contribute to sequence bias: GC content, mappability of sequencing reads, and regional biases that might be generated by local structure. We show that relying on input control as a normalizer is not generally appropriate due to sample to sample variation in bias. To correct sequence bias, we p

SUBMITTER: Cheung MS 

PROVIDER: S-EPMC3159482 | biostudies-literature | 2011 Aug

REPOSITORIES: biostudies-literature