This is a test version of Biostars. For the public version, visit https://www.biostars.org.
How should analyze if a Transcription factor significant in one condition vs. another using centipede footprints?

Hi, My ATAC-seq data (unstimulation vs. stimulation) has been peak called, differential analyzed using DESeq2. Then all the peaks were put in Centipede for TF footprint analysis. The 402 motifs were input and around 360 motifs yield the output file of post probability. Now I want to compare the Post probability of each TF in two conditions, in order to decide if any TF binding is significant change in stimulation vs. stimulation. The null hypothesis is P1,N1=P2,N2. P is the Post probability , N is the number of binding site (>10 K). I wonder if any R package work with the the null hypothesis? Any suggestions are welcomed. Thank you.

atac-seq footprints tf binding postpr

0 answers

No answers yet.

Log in to answer this question.