Basic Introduction



HINT (Hmm-based IdeNtification of Transcription factor footprints) is a framework that uses open chromatin data to identify the active transcription factor binding sites. This method is originally proposed to model the active binding sites by simultaneous analysis of DNase-seq and the ChIP-seq profiles of histone modifications on a genome-wide level (full paper). The HMM has as input a normalised and a slope signal of DNase-seq and one of the histone marks. It can, therefore, detect the increase, top and decrease regions of either histone modification and DNase signals.  And we next modified HINT to allow only DNase-seq data by removing the three histone-level states and the use of bias-corrected DNase-seq signal before normalisation steps (full paper). Recently, we extended HINT to ATAC-seq, a new assay to identify accessible DNA regions, taking the protocol-specificity into consideration.


If you have followed the generic instructions for the RGT suite installation, then you can start using HINT.

If you have any questions, comments, installation problems or bug reports, please access our discussion group.

Note: You must download the genomic data for bias correction.

Basic Usage

Download here. Execute the following commands in order to perform footprints identification from DNaseseq data:

cd HINT_DNaseTest
rgt-hint --dnase-footprints --output-location=./ --output-prefix=test DNase.bam DNasePeaks.bed

The above commands will output a BED file containing the footprints, inside the current folder with test as the prefix. Each footprint, i.e. each line of the BED file, will also contain information regarding the tag-count score of each footprint. This score can be used as a footprint quality assessment (the higher the value, the better). In addition, a file including the details of reads and footprints will also be written in the same folder of BED file.

Complete tutorial and more descriptive examples are found in here.


If you use HINT/HINT-BC in your research, please cite the following publication:

Gusmao EG, Allhoff M, Zenke M and Costa IG. “Analysis of computational footprinting methods for DNase sequencing experiments”. Nature Methods, 13(4):303-309, 2016.[Full Text]

Gusmao EG, Dieterich C, Zenke M and Costa IG. “Detection of active transcription factor binding sites with the combination of DNase hypersensitivity and histone modifications” Bioinformatics, 30(22):3143-3151, 2014. [Full Text]