This repository provides code for the following two analyses.

• Differential peak analysis

Reads were first normalized using S3Norm (https://github.com/guanjue/S3norm), then normalized scores for each peak is calculated using DeepTools. Result is provided in scores_per_bed.tsv. Next, run python run_edgeR.py.

• Motif analysis

The idea of this in silico motif mutation analysis is to all the sequences with one mismatch to the reference sequence, e.g., TGACCAATAGCC. Then use FIMO to calculate motif mapping p-value.

To generate one mismatch, run

python create_one_mismatch_seq.py TGACCAATAGCC > TGACCAATAGCC.mis.fa

Run FIMO, and then parse its output:

python get_score.py

Pandas

For ATAC-seq, ChIP-seq, and HiC analyses, please go to https://github.com/YichaoOU/HemTools.