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We evaluated how variations in sequencing depth and other parameters influence interpretation of chromatin immunoprecipitation-sequencing (ChIP-seq) experiments. Using Drosophila melanogaster S2 cells, we generated ChIP-seq data sets for a site-specific transcription factor (Suppressor of Hairy-wing) and a histone modification (H3K36me3). We detected a chromatin-state bias: open chromatin regions yielded higher coverage, which led to false positives if not corrected. This bias had a greater effect on detection specificity than any base-composition bias. Paired-end sequencing revealed that single-end data underestimated ChIP-library complexity at high coverage. Removal of reads originating at the same base reduced false-positives but had little effect on detection sensitivity. Even at mappable-genome coverage depth of ∼1 read per base pair, ∼1% of the narrow peaks detected on a tiling array were missed by ChIP-seq. Evaluation of widely used ChIP-seq analysis tools suggests that adjustments or algorithm improvements are required to handle data sets with deep coverage.
Pubmed ID: 22522655
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Software tool that screens DNA sequences for interspersed repeats and low complexity DNA sequences. The output of the program is a detailed annotation of the repeats that are present in the query sequence as well as a modified version of the query sequence in which all the annotated repeats have been masked (default: replaced by Ns). Currently over 56% of human genomic sequence is identified and masked by the program. Sequence comparisons in RepeatMasker are performed by one of several popular search engines including nhmmer, cross_match, ABBlast/WUBlast, RMBlast and Decypher. RepeatMasker makes use of curated libraries of repeats and currently supports Dfam ( profile HMM library ) and RepBase ( consensus sequence library ).
View all literature mentionsA software package that generates a continuous tag sequence density estimation allowing identification of biologically meaningful sites whose output can be displayed directly in the UCSC Genome Browser.
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