Fig. 1

T-cep algorithm and training results for TCF7L2-omics data. a The workflow of T-cep algorithm. Shown is a schematic summary of the four steps needed for de novo identifying transcription factor associated chromatin state (TF-state). The approach begins with preprocessing the ChIP-seq data into an alphabet of 2ⁿ observations, builds a HMM to generate a best selected model without infrequent state, re-estimate transition and emission probabilities and then annotate biological meaningful TF-states. b Result of T-cep approach. The emission probabilities of each mark are independent of others for the selected 18-state HMM. The mark probability of greater than 0.1 is considered to be associated with a chromatin state. c A screenshot of a genomic region in Chr8 of MCF-7 annotated by T-cep in UCSC genome browser. ChIP-seq of TCF7L2 and histone marks are in the first nine lines, while the tenth track represents the main output of the T-cep, annotated different states represented by different colors. RefSeq gene (HG19) genomic positions are shown in the last line