The Bowtie tool [ 17] was used to map ChIP-seq reads to the GM12878 diploid genome to select perfect match and unique mapping tags, which later were fed toChIP-seq processing pipeline [ 30] to discover narrow peaks with FDR < 0.01.
Mapped ChIP tags were analyzed using peak finder methods, which identify regions enriched for ChIP tags.
To assign genes to mapped ChIP peaks, we used intersectBed and closestBed and subsequently manually pruned the gene lists.
The genome-wide binding profiles of hundreds of proteins have been mapped using ChIP-chip and ChIP-seq in organisms ranging from bacteria to humans.
For histone methylation maps, ChIP-chip experiments were carried according to Robyr and Grunstein (2003) [32].
Transcriptome analysis using SAGE and microarrays has been performed in various tissues [8], [9], recently in combination with chromatin immunoprecipitation based mapping (ChIP-chip) of genomewide GR occupancy [10].
For mapping ChIP-Seq data to genomic scaffolds, we considered only unique hits (-m 1 option).
We define a list of uniquely mapped ChIP-seq DNA sequences observed in a given ChIP-seq experiment as the Chip-seq library.
In the absence of a reference genome, we mapped ChIP-seq data to the clusters of the C. aquatica HG genome for cluster-based repeat identification.
Two replicate Bowtie-mapped ChIP-seq datasets were downloaded for GM12878, K562, A549, HepG2, HCT116, and SK-N-SH from the UCSC browser.
In order to control for such errors, we used only uniquely mapped ChIP-seq reads, thus excluding fragments exhibiting dual genomic/mtDNA localization.
