Analysis Of Transcription Factor Relationship Based On Motif Distribution

Transcription factors(TFs)is important during the process of gene expression.Transcription factors binding to specific motifs on the DNA sequence,are elementary to the regulation of transcription.The gene are not always regulated by a single transcription factor,but by a combination of transcription factors,which are in close proximity.Analysis of co-association transcription factors is an important problem which can help revealing the mechanism of transcriptional regulation.Recently,ChIP-seq in mapping TF provides a large amount of experimental data to analyze co-TFs.Several studies have provide evidence that if two TFs are co-associated then the relative distance between TFs exhibits a peak-like distribution.In order to analyze co-TFs,we develop a novel method to calculate the association between TFs.Based on the ordered differences,we define an adjacency score,and this score can illustrate the binding affinities between co-TFs.For all candidate motifs,we calculate corresponding adjacency scores,and then list descending-order motifs.From these lists,we can find co-TFs for candidate motifs.On ChIP-seq datasets,our method obtains better AUC results than some other methods which are currently common used method for the motif enrichment analysis problem.Especially,our method have great accuracy on some big datasets.And also,on all the testing datasets,our method can obtain the AUC score more than 0.8,which is better than other methods.