Fig. 1

The components of FindIT2. A sketch of FindIT2 components is shown. FindIT2 supports a complete framework for annotating ChIP-seq/ATAC-seq peaks, identifying TF targets by the combination of ChIP-seq and RNA-seq datasets, and inferring influential TFs based on different types of data input. The mmAnno module accepts the bed or bed-like format file like narrowPeak, broadPeak which contains coordinates of interesting region. mmAnno can build peak-gene links to annotate peak according to the genomic coordinates of features. The peakGeneCor module can use the genomic coordinates and count matrix to calculate correlation between features, which can build more robust peak-gene link. The caclRP module can accept the peak count matrix and Granges object produced by mm_geneScan function in mmAnno module to calculate regulatory potential (RP). Or it can also accept bigwig file or TF ChIP-seq peak to calculate RP. The data frame containing RP calculated by calcRP_TFHit in calcRP module can be integrated with differential gene expression to calculate TF target rank using integrate_ChIP_RNA function in find_influential_Target module. The find_influential_TF provides many methods to infer influential TF based on different analysis purpose and annotation. For example, findIT_regionRP can accepts the Granges object from calcRP_region to infer influential TF of interesting gene set. findIT_enrichFisher can accept public TF ChIP-seq database to find influential TF of interesting peak set