TIP: a probabilistic method for identifying transcription factor target genes from ChIP-seq binding profiles.
BACKGROUND
ChIP-seq and ChIP-chip experiments have been widely used to identify transcription factor (TF) binding sites and target genes. Conventionally, a fairly 'simple' approach is employed for target gene identification e.g. finding genes with binding sites within 2 kb of a transcription start site (TSS). However, this does not take into account the number of sites upstream of the TSS, their exact positioning or the fact that different TFs appear to act at different characteristic distances from the TSS.


RESULTS
Here we propose a probabilistic model called target identification from profiles (TIP) that quantitatively measures the regulatory relationships between TFs and target genes. For each TF, our model builds a characteristic, averaged profile of binding around the TSS and then uses this to weight the sites associated with a given gene, providing a continuous-valued 'regulatory' score relating each TF and potential target. Moreover, the score can readily be turned into a ranked list of target genes and an estimate of significance, which is useful for case-dependent downstream analysis.


CONCLUSIONS
We show the advantages of TIP by comparing it to the 'simple' approach on several representative datasets, using motif occurrence and relationship to knock-out experiments as metrics of validation. Moreover, we show that the probabilistic model is not as sensitive to various experimental parameters (including sequencing depth and peak-calling method) as the simple approach; in fact, the lesser dependence on sequencing depth potentially utilizes the result of a ChIP-seq experiment in a more 'cost-effective' manner.


BACKGROUND
mark.gerstein@yale.edu


BACKGROUND
Supplementary data are available at Bioinformatics online.
Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA.
Chao
C
Cheng
Renqiang
R
Min
Mark
M
Gerstein
D020816:Amino Acid Motifs; D000818:Animals; D001665:Binding Sites; D047369:Chromatin Immunoprecipitation; D047628:Estrogen Receptor alpha / Q000378:metabolism; D005786:Gene Expression Regulation; D051379:Mice; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis; D011485:Protein Binding; D050797:STAT4 Transcription Factor / Q000378:metabolism; D017422:Sequence Analysis, DNA; D014157:Transcription Factors / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*; D024363:Transcription Initiation Site
D047628:Estrogen Receptor alpha; D050797:STAT4 Transcription Factor; C494091:Stat4 protein, mouse; D014157:Transcription Factors