Literature DB >> 34415529

Methods to Assess the Reproducibility and Similarity of Hi-C Data.

Tao Yang1, Xi He1, Lin An1, Qunhua Li2.   

Abstract

Hi-C experiments are costly to perform and involve multiple complex experimental steps. Reproducibility of Hi-C data is essential for ensuring the validity of the scientific conclusions drawn from the data. In this chapter, we describe several recently developed computational methods for assessing reproducibility of Hi-C replicate experiments. These methods can also be used to assess the similarity between any two Hi-C samples.
© 2022. Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  GenomeDISCO; Hi-C data; HiC-spector; HiCRep; Quality control; Reproducibility; Similarity

Mesh：

Year:  2022        PMID： 34415529     DOI： 10.1007/978-1-0716-1390-0_2

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN： 1064-3745


  13 in total

1.  HiCNorm: removing biases in Hi-C data via Poisson regression.

Authors:  Ming Hu; Ke Deng; Siddarth Selvaraj; Zhaohui Qin; Bing Ren; Jun S Liu
Journal:  Bioinformatics       Date:  2012-09-27       Impact factor: 6.937

2.  Virulence of Bordetella bronchiseptica in the porcine respiratory tract.

Authors:  L A Collings; J M Rutter
Journal:  J Med Microbiol       Date:  1985-04       Impact factor: 2.472

3.  GenomeDISCO: a concordance score for chromosome conformation capture experiments using random walks on contact map graphs.

Authors:  Oana Ursu; Nathan Boley; Maryna Taranova; Y X Rachel Wang; Galip Gurkan Yardimci; William Stafford Noble; Anshul Kundaje
Journal:  Bioinformatics       Date:  2018-08-15       Impact factor: 6.937

Review 4.  The 3D genome in transcriptional regulation and pluripotency.

Authors:  David U Gorkin; Danny Leung; Bing Ren
Journal:  Cell Stem Cell       Date:  2014-06-05       Impact factor: 24.633

5.  Chromatin architecture reorganization during stem cell differentiation.

Authors:  Jesse R Dixon; Inkyung Jung; Siddarth Selvaraj; Yin Shen; Jessica E Antosiewicz-Bourget; Ah Young Lee; Zhen Ye; Audrey Kim; Nisha Rajagopal; Wei Xie; Yarui Diao; Jing Liang; Huimin Zhao; Victor V Lobanenkov; Joseph R Ecker; James A Thomson; Bing Ren
Journal:  Nature       Date:  2015-02-19       Impact factor: 49.962

6.  Physical tethering and volume exclusion determine higher-order genome organization in budding yeast.

Authors:  Harianto Tjong; Ke Gong; Lin Chen; Frank Alber
Journal:  Genome Res       Date:  2012-05-22       Impact factor: 9.043

7.  HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient.

Authors:  Tao Yang; Feipeng Zhang; Galip Gürkan Yardımcı; Fan Song; Ross C Hardison; William Stafford Noble; Feng Yue; Qunhua Li
Journal:  Genome Res       Date:  2017-08-30       Impact factor: 9.043

8.  HiC-spector: a matrix library for spectral and reproducibility analysis of Hi-C contact maps.

Authors:  Koon-Kiu Yan; Galip Gürkan Yardimci; Chengfei Yan; William S Noble; Mark Gerstein
Journal:  Bioinformatics       Date:  2017-07-15       Impact factor: 6.937

9.  Unsupervised embedding of single-cell Hi-C data.

Authors:  Jie Liu; Dejun Lin; Galip Gürkan Yardimci; William Stafford Noble
Journal:  Bioinformatics       Date:  2018-07-01       Impact factor: 6.937

10.  Measuring the reproducibility and quality of Hi-C data.

Authors:  Galip Gürkan Yardımcı; Hakan Ozadam; Michael E G Sauria; Oana Ursu; Koon-Kiu Yan; Tao Yang; Abhijit Chakraborty; Arya Kaul; Bryan R Lajoie; Fan Song; Ye Zhan; Ferhat Ay; Mark Gerstein; Anshul Kundaje; Qunhua Li; James Taylor; Feng Yue; Job Dekker; William S Noble
Journal:  Genome Biol       Date:  2019-03-19       Impact factor: 13.583
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