S3V2_IDEAS_ESMP: a package for normalizing, denoising and integrating epigenomic datasets across different cell types

The S3V2-IDEAS package first normalizes average read counts by S3V2 and then uses IDEAS to either do genome segmentations or call master peaks list across multiple datasets. This package uses bigWig files as the inputs.

Overview of S3V2-IDEAS pipeline. (A) Module 1 normalizes and denoises input data using the S3V2 method. Examples of normalized epigenetic signals from the Hba locus in G1E-ER4 cells (ER4) are shown. (B and C) In Module 2, the normalized data is integrated by IDEAS in one of two modes. (B) The epigenetic state mode integrates multiple epigenetic features into an epigenetic states model. (C) The signal intensity state mode finds frequently occurring signal intensity states for a single epigenetic feature, along with a master peak list derived from those states (D). AVE = average, LSK, MEP, ER4, ERY = abbreviations for cell types

#####################################################################################

Table of Contents

(1) Prerequisites and S3V2_IDEAS_ESMP Installation

(2) Inputs-ParameterSettings-RunningSteps-Outputs for S3V2_IDEAS_ESMP

(3) Running S3V2-IDEAS in operating system set in AWS

(4) Running S3V2-IDEAS in operating system set in Docker

#####################################################################################

Contacts and References

Contacts:

rch8@psu.edu, gxiang@ds.dfci.harvard.edu, guanjuexiang@gmail.com

(1) S3V2-IDEAS

Guanjue Xiang, Belinda M Giardine, Shaun Mahony, Yu Zhang, Ross C Hardison, S3V2-IDEAS: a package for normalizing, denoising and integrating epigenomic datasets across different cell types, Bioinformatics, 2021;, btab148, https://doi.org/10.1093/bioinformatics/btab148

(2) IDEAS genome segmentation

Yu Zhang, Lin An, Feng Yue, Ross C Hardison, Jointly characterizing epigenetic dynamics across multiple human cell types, Nucleic Acids Research, Volume 44, Issue 14, 19 August 2016, Pages 6721–6731, https://doi.org/10.1093/nar/gkw278

Yu Zhang, Shaun Mahony. Direct prediction of regulatory elements from partial data without imputation. PLoS computational biology. 2019 Nov 4;15(11):e1007399, https://doi.org/10.1371/journal.pcbi.1007399

(3) S3norm

Guanjue Xiang, Cheryl A Keller, Belinda Giardine, Lin An, Qunhua Li, Yu Zhang, Ross C Hardison, S3norm: simultaneous normalization of sequencing depth and signal-to-noise ratio in epigenomic data, Nucleic Acids Research, Volume 48, Issue 8, 07 May 2020, Page e43, https://doi.org/10.1093/nar/gkaa105

(4) IDEAS genome segmentation Resource

a. IDEAS genome segmentation analysis for VISION project (http://usevision.org/): IDEAS Updates and the corresponding genome segmentation analysis with 8 epigenetic features in 20 mouse hematopoietic cell types.

Guanjue, Xiang, Cheryl A. Keller, ..., Yu Zhang, Ross C. Hardison. "An integrative view of the regulatory and transcriptional landscapes in mouse hematopoiesis." Genome research. 2020 Mar 1;30(3):472-84, https://doi.org/10.1101/gr.255760.119

The Genome segmentation tracks is in the "IDEAS..." tab: https://main.genome-browser.bx.psu.edu/cgi-bin/hgTracks?db=mm10

b. IDEAS genome segmentation analysis for ROADMAP project

Yu Zhang, Ross C Hardison. Accurate and reproducible functional maps in 127 human cell types via 2D genome segmentation. Nucleic acids research. 2017 Sep 29;45(17):9823-36, https://doi.org/10.1093/nar/gkx659

Genome segmentation tracks: http://bx.psu.edu/~yuzhang/Roadmap_ideas/