maxATAC Data

This repo contains the data in relation to the maxATAC project. For complete installation directions of maxATAC please refer to the maxATAC repo, https://github.com/MiraldiLab/maxATAC

./hg38

This directory contains:

1. hg38_maxatac_blacklist.bed: bed file of maxATAC blacklist regions
2. hg38_maxatac_blacklist.bw: bed file of maxATAC blacklist regions
3. hg38.chrom.sizes: hg38 chromosome sizes file

Curation of the maxATAC black list is described in the maxATAC preprint

./models

Information for the 127 TF models available through maxATAC. Each directory is a TF name. Each directory contains a .h5 of the best TF model, a .tsv file of threshold statistics, and a .png of the statistics.

Example directory structure:

|____ATF2
| |____ATF2_validationPerformance_vs_thresholdCalibration.png
| |____ATF2_binary_revcomp99_fullModel_RR0_73.h5
| |____ATF2_validationPerformance_vs_thresholdCalibration.tsv

By default, the threshold for calling TFBS is set to maximize the validation F1-score of the TF model. The threshold statistics file and image enables users to see the trade-offs between precision and recall for each model, information that could guide their parameter choices for maxatac predict

Example threshold statistics file

This is an example of the first 6 lines of the threshold statistics file used to call peaks. The first column is the threshold. Every column after is the average performance reported for different metrics on validation chromosome 2.

Standard_Thresh	Monotonic_Avg_Precision	Monotonic_Avg_Recall	Monotonic_Avg_log2FC	Avg_F1
0.0	0.0035793736711456103	0.9910269020975186	0.4617435633366975	0.0071224011910284366
0.001	0.018103716393149	0.9242690259191988	2.996816276717381	0.03517534734171995
0.002	0.027523721672056148	0.92192080328679	3.5979115724538913	0.05275399945034204
0.003	0.03384312047545328	0.9123870842533509	3.8788363137406194	0.06429293366464785
0.004	0.03872007478681639	0.9030209327592842	4.055800482157333	0.07305708818396862
0.005	0.04270041191717275	0.9017292649083462	4.199724330597559	0.0801251221410759

Example threshold statistics image

./scripts

A directory of scripts that are used to process the ATAC-seq, DHS, and ChIP-seq data analyzed by our publication. The scripts ATAC_bowtie2_pipeline.sh and scatac_generate_bigwig.sh are required for running maxatac prepare.

.
|____ATAC
| |____align_reads_STAR.sh
| |____infer_insertion_sites.sh
| |____ATAC_bowtie2_nodedup_pipeline.sh
| |____RPM_normalize_Tn5_counts.sh
| |____shift_reads.sh
| |____trim_reads.sh
| |____infer_Tn5_sites.sh
| |____scatac_generate_bigwig.sh
| |____ATAC_bowtie2_pipeline.sh
| |____sra2fastq_PE.sh
| |____filter_BAM_STAR.sh
| |____ATAC_post_alignment.sf
|____DHS
| |____infer_DHS_cut_sites.sh
| |____generate_DHS_coverage_bigwig.sh
| |____filter_DHS_SE_ENCODE.sh
|____CHIP
| |____infer_5prime_BAM.sh
| |____filter_chroms_from_bam.sh
| |____slop_5prime.sh
| |____RPM_normalize_5prime_counts.sh

Example_TF_META.tsv

This .tsv file shows an example meta file required to train your own models.

./motifs

The directory of motif information from CISBP. There are two meta files, (1) a list of all TF motifs that have been curated and (2) metadata about family source, etc... from CISBP.

.
|____20201001_all_motifs_meta.tsv
|____CISBP_2_TF_Information_all_motifs_plus.txt
|____all_motifs
| |____M00008_2.00.pfm
| |____M00009_2.00.pfm
| |____...

Publication

The maxATAC pre-print is currently available on bioRxiv.

maxATAC: genome-scale transcription-factor binding prediction from ATAC-seq with deep neural networks
Tareian Cazares, Faiz W. Rizvi, Balaji Iyer, Xiaoting Chen, Michael Kotliar, Joseph A. Wayman, Anthony Bejjani, Omer Donmez, Benjamin Wronowski, Sreeja Parameswaran, Leah C. Kottyan, Artem Barski, Matthew T. Weirauch, VB Surya Prasath, Emily R. Miraldi
bioRxiv 2022.01.28.478235; doi: https://doi.org/10.1101/2022.01.28.478235