Quantification of histone modification ChIP-seq enrichment for data mining and machine learning applications.

ABSTRACT:

Background

The advent of ChIP-seq technology has made the investigation of epigenetic regulatory networks a computationally tractable problem. Several groups have applied statistical computing methods to ChIP-seq datasets to gain insight into the epigenetic regulation of transcription. However, methods for estimating enrichment levels in ChIP-seq data for these computational studies are understudied and variable. Since the conclusions drawn from these data mining and machine learning applications strongly depend on the enrichment level inputs, a comparison of estimation methods with respect to the performance of statistical models should be made.

Results

Various methods were used to estimate the gene-wise ChIP-seq enrichment levels for 20 histone methylations and the histone

SUBMITTER: Hoang SA 

PROVIDER: S-EPMC3170335 | biostudies-literature | 2011 Aug

REPOSITORIES: biostudies-literature