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HiChIP: a high-throughput pipeline for integrative analysis of ChIP-Seq data

Huihuang Yan, Jared Evans, Mike Kalmbach, Raymond Moore, Sumit Middha, Stanislav Luban, Liguo Wang, Aditya Bhagwate, Ying Li, Zhifu Sun, Xianfeng Chen, Jean-Pierre A Kocher
2014 BMC Bioinformatics  
We have developed a highly integrative pipeline, termed HiChIP for systematic analysis of ChIP-Seq data.  ...  Using public ChIP-Seq data we demonstrate that HiChIP is a fast and reliable pipeline for processing large amounts of ChIP-Seq data.  ...  Acknowledgements We thank Mona Branstad for editing the manuscript. This work was supported by the Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905.  ... 
doi:10.1186/1471-2105-15-280 pmid:25128017 pmcid:PMC4152589 fatcat:u3woq66u3vaszcfubk3ezkdt7q

HiC-DC+ enables systematic 3D interaction calls and differential analysis for Hi-C and HiChIP

Merve Sahin, Wilfred Wong, Yingqian Zhan, Kinsey Van Deynze, Richard Koche, Christina S. Leslie
2021 Nature Communications  
Here, we present HiC-DC+, a software tool for Hi-C/HiChIP interaction calling and differential analysis using an efficient implementation of the HiC-DC statistical framework.  ...  HiC-DC+ therefore provides a principled statistical analysis tool to empower genome-wide studies of 3D chromatin architecture and function.  ...  Still, such analyses depend on statistical analysis of high-throughput 3C-based experiments and are therefore not entirely orthogonal to HiChIP.  ... 
doi:10.1038/s41467-021-23749-x pmid:34099725 pmcid:PMC8184932 fatcat:luifzry3kbc6nnd6q64wn747ei

Predicting unrecognized enhancer-mediated genome topology by an ensemble machine learning model [article]

Li Tang, Matthew Craig Hill, Jun Wang, Jianxin Wang, James F. Martin, Min Li
2020 bioRxiv   pre-print
To enrich for functional enhancer-promoter loops over common structural genomic contacts, we trained LoopPredictor with both H3K27ac and YY1 HiChIP data.  ...  Furthermore, to explore the cross-species prediction capability of LoopPredictor, we fed mouse multi-omics features into a model trained on human data and found that the predicted enhancer loops outputs  ...  A total of 880 super enhancers were found, which accounted for 5.6% of all enhancers. 775 Super enhancer signal derived from H2K27ac ChIP-seq data. 776 ( 776 C) GO analysis for super enhancer anchors  ... 
doi:10.1101/2020.04.10.036145 fatcat:w5ob7zs7uzet5a5ibngvzhmyhu

ChIA-PIPE: A fully automated pipeline for comprehensive ChIA-PET data analysis and visualization

Byoungkoo Lee, Jiahui Wang, Liuyang Cai, Minji Kim, Sandeep Namburi, Harianto Tjong, Yuliang Feng, Ping Wang, Zhonghui Tang, Ahmed Abbas, Chia-Lin Wei, Yijun Ruan (+1 others)
2020 Science Advances  
Interpretation of ChIA-PET data requires a robust analytic pipeline.  ...  Here, we introduce ChIA-PIPE, a fully automated pipeline for ChIA-PET data processing, quality assessment, visualization, and analysis.  ...  Gabdank (Stanford University) for the helpful discussions; Z. Reifsnyder for artistic improvement of the figures; and the legacy  ... 
doi:10.1126/sciadv.aay2078 pmid:32832596 pmcid:PMC7439456 fatcat:zo2jnuxap5csnlfypsyapnpare

Recent advancement in Next Generation Sequencing techniques and its computational analysis [article]

Khalid Raza, Sabahuddin Ahmad
2017 arXiv   pre-print
This technology results into huge amount of data, which need to be analysed to conclude valuable information. Specific data analysis algorithms are written for specific task to be performed.  ...  Analysis of NGS data unravels important clues in quest for the treatment of various life-threatening diseases; improved crop varieties and other related scientific problems related to human welfare.  ...  List of Abbreviations  ... 
arXiv:1606.05254v2 fatcat:ruu3lkfca5fetkzfg5vywzx2su

Enhancer connectome in primary human cells identifies target genes of disease-associated DNA elements

Maxwell R Mumbach, Ansuman T Satpathy, Evan A Boyle, Chao Dai, Benjamin G Gowen, Seung Woo Cho, Michelle L Nguyen, Adam J Rubin, Jeffrey M Granja, Katelynn R Kazane, Yuning Wei, Trieu Nguyen (+15 others)
2017 Nature Genetics  
We thank Agilent Technologies for generating oligonucleotide pools for cloning of the CRISPRa gRNAs. We thank the UC Berkeley High-Throughput Screening Facility and Flow Cytometry Facility.  ...  Miller for assistance interpreting their published data sets. We thank X. Ji and J. Coller at the Stanford Functional Genomics Facility.  ...  We asked whether the integration of reference cell line Hi-C data with primary T cell H3K27ac ChIP-seq data could recapitulate HiChIP EIS in primary T cells.  ... 
doi:10.1038/ng.3963 pmid:28945252 pmcid:PMC5805393 fatcat:t2gutwaenzdejmuxpoysqxe3cy

ChiLin: a comprehensive ChIP-seq and DNase-seq quality control and analysis pipeline

Qian Qin, Shenglin Mei, Qiu Wu, Hanfei Sun, Lewyn Li, Len Taing, Sujun Chen, Fugen Li, Tao Liu, Chongzhi Zang, Han Xu, Yiwen Chen (+5 others)
2016 BMC Bioinformatics  
Acknowledgements We thank Bo Qin for thoughtful suggestions on the design of ChiLin, Xueqiu Lin for testing ChiLin and Xikun Duan, Qixuan Wang, Yulin Yang, Chengchen Zhao for preparing initial ChiLin QC  ...  The project was funded by National Science Foundation of China grant 31329003, National Institute of Health grants U01 CA180980 and R01 HG4069 and support from the Dana-Farber Cancer Institute.  ...  Here, we present ChiLin, an integrated command line quality control and analysis pipeline for ChIP-seq or DNase-seq data.  ... 
doi:10.1186/s12859-016-1274-4 pmid:27716038 pmcid:PMC5048594 fatcat:4wxxsfeiybesvix3ru3riv3bqu

Chromatin architecture reveals cell type-specific target genes for kidney disease risk variants

Aiping Duan, Hong Wang, Yan Zhu, Qi Wang, Jing Zhang, Qing Hou, Yuexian Xing, Jinsong Shi, Jinhua Hou, Zhaohui Qin, Zhaohong Chen, Zhihong Liu (+1 others)
2021 BMC Biology  
organization, histone modifications distribution and transcriptome with HiChIP, ChIP-seq and RNA-seq.  ...  Conclusions Our results provide a valuable multi-omics resource on the chromatin landscape of human kidney tubule cells and establish a bioinformatic pipeline in dissecting functions of kidney disease-associated  ...  Acknowledgements We thank Yinghui Lu for preparation of cell culture medium.  ... 
doi:10.1186/s12915-021-00977-7 pmid:33627123 fatcat:hgsyjasoujeo7nz75topa6rnz4

Biomedical Data Commons (BMDC) prioritizes B-lymphocyte non-coding genetic variants in Type 1 Diabetes

Samantha N. Piekos, Sadhana Gaddam, Pranav Bhardwaj, Prashanth Radhakrishnan, Ramanathan V. Guha, Anthony E. Oro, Ilya Ioshikhes
2021 PLoS Computational Biology  
We have addressed this issue through the creation of Biomedical Data Commons (BMDC), a knowledge graph that integrates data from multiple sources into a single queryable format.  ...  We develop a pipeline using B-lymphocyte multi-dimensional epigenome and connectome data and deploy BMDC to assess genetic variants in the context of Type 1 Diabetes (T1D).  ...  Acknowledgments We thank the Google Data Commons team for developing the underlying infrastructure used to build BMDC. We are also grateful for their help in developing the schema for BMDC.  ... 
doi:10.1371/journal.pcbi.1009382 pmid:34543288 pmcid:PMC8483327 fatcat:76h55gtz3jghlnfn5lx6j4vj2i

Enhancer connectome in primary human cells reveals target genes of disease-associated DNA elements [article]

Maxwell R. Mumbach, Ansuman T. Satpathy, Evan A. Boyle, Chao Dai, Benjamin G. Gowen, Seung Woo Cho, Michelle L. Nguyen, Adam J. Rubin, Jeffrey M. Granja, Katelynn R. Kazane, Yuning Wei, Trieu Nguyen (+15 others)
2017 bioRxiv   pre-print
These data provide a principled means of assigning molecular functions to autoimmune and cardiovascular disease risk variants, linking hundreds of noncoding variants to putative gene targets.  ...  The majority of disease-associated enhancers contact genes beyond the nearest gene in the linear genome, leading to a four-fold increase of potential target genes for autoimmune and cardiovascular diseases  ...  3D, suggesting EIS bias is in part driven by 3D changes (Supplementary 237 Fig. 10b ). 238 We asked whether the integration of reference cell line Hi-C data with primary T 239 cell H3K27ac ChIP-seq  ... 
doi:10.1101/178269 fatcat:4qhrtma3b5euhlebcac5eitxre

Molecular and computational approaches to map regulatory elements in 3D chromatin structure

Beoung Hun Lee, Suhn K. Rhie
2021 Epigenetics & Chromatin  
Moreover, we list currently available three-dimensional epigenomic data sets that are generated in various human cell types and tissues to assist in the design and analysis of research projects.  ...  AbstractEpigenetic marks do not change the sequence of DNA but affect gene expression in a cell-type specific manner by altering the activities of regulatory elements.  ...  Acknowledgements We thank the lab members for helpful discussions. Authors' contributions BL and SKR wrote the article. All authors read and approved the final manuscript.  ... 
doi:10.1186/s13072-021-00390-y pmid:33741028 pmcid:PMC7980343 fatcat:dgtydqgyhjgxdni34kedgzw3wy

diffloop: a computational framework for identifying and analyzing differential DNA loops from sequencing data

Caleb A Lareau, Martin J Aryee, Bonnie Berger
2017 Bioinformatics  
Your story matters Citation Lareau, Caleb A., and Martin J Aryee. 2017. "diffloop: a computational framework for identifying and analyzing differential DNA loops from sequencing data."  ...  To systematically assess changes in DNA looping architecture between samples, we introduce diffloop, an R/ Bioconductor package that provides a suite of functions for the quality control, statistical testing  ...  Hnisz and members of the R. Young Lab for their useful discussion and insight. Funding This work has been supported by the NSF (Graduate Fellowship no.  ... 
doi:10.1093/bioinformatics/btx623 pmid:29028898 pmcid:PMC5860605 fatcat:p5m3u7v3izfbzjyyonql35lwmm

A Mutation in the Transcription Factor Foxp3 Drives T Helper 2 Effector Function in Regulatory T Cells

Frédéric Van Gool, Michelle L.T. Nguyen, Maxwell R. Mumbach, Ansuman T. Satpathy, Wendy L. Rosenthal, Simone Giacometti, Duy T. Le, Weihong Liu, Todd M. Brusko, Mark S. Anderson, Alexander Y. Rudensky, Alexander Marson (+2 others)
2019 Immunity  
Genomic analysis of Treg cells by RNA-sequencing, Foxp3 chromatin immunoprecipitation followed by high-throughput DNA sequencing (ChIP-sequencing), and H3K27ac-HiChIP revealed a specific de-repression  ...  These findings identify a direct role for Foxp3 in suppressing Th2-like Treg cells and implicate additional pathways that could be targeted to restrain Th2 trans-differentiated Treg cells.  ...  Eckalbar of the UCSF Sandler Center Functional Genomics Core for assistance with RNAseq data; Jennifer Bolen and the UCSF immunohistochemistry core facility, M. Lee, V.  ... 
doi:10.1016/j.immuni.2018.12.016 pmid:30709738 pmcid:PMC6476426 fatcat:nuttb7pts5cvpk3m7ggwsqcive

Integrating distal and proximal information to predict gene expression via a densely con-nected convolutional neural network [article]

Wanwen Zeng, Yong Wang, Rui Jiang
2018 bioRxiv   pre-print
Recently, a novel high-throughput experimental approach named HiChIP has been developed and generating compre-hensive data on high-resolution interactions between promoters and distal enhancers.  ...  We expect to see a wide spectrum of appli-cations using HiChIP data in deciphering the mechanism of gene regulation.  ...  Rui Jiang is a RONG professor at the Institute for Data Science, Tsinghua University.  ... 
doi:10.1101/341214 fatcat:4ta3ar4purgofmt36dvwqlqfca

Model-based analysis of chromatin interactions from dCas9-Based CAPTURE-3C-seq

Yong Chen, Yunfei Wang, Xin Liu, Jian Xu, Michael Q. Zhang, Roberto Mantovani
2020 PLoS ONE  
Here we present the statistical model and a flexible pipeline, C3S, for analysing CAPTURE-3C-seq or similar experimental data from raw sequencing reads to significantly interacting chromatin loci.  ...  Furthermore, it supports the analysis of intra- and inter-chromosomal interactions for different mammalian cell types.  ...  Carone for the helpful discussions and critical reading. Software: Yunfei Wang. Supervision: Jian Xu, Michael Q. Zhang. Validation: Yunfei Wang. Writing -original draft: Yong Chen.  ... 
doi:10.1371/journal.pone.0236666 pmid:32735574 fatcat:fkt7hun3p5e3zfh6444hlshj4u
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