ChromHMM: automating chromatin-state discovery and characterization
TLDR
ChromHMM as mentioned in this paper is an automated computational system for learning chromatin states, characterizing their biological functions and correlations with large-scale functional datasets, and visualizing the resulting genome-wide maps of chromatin state annotations.Abstract:
Chromatin state annotation using combinations of chromatin modification patterns has emerged as a powerful approach for discovering regulatory regions and their cell type specific activity patterns, and for interpreting disease-association studies1-5 However, the computational challenge of learning chromatin state models from large numbers of chromatin modification datasets in multiple cell types still requires extensive bioinformatics expertise making it inaccessible to the wider scientific community To address this challenge, we have developed ChromHMM, an automated computational system for learning chromatin states, characterizing their biological functions and correlations with large-scale functional datasets, and visualizing the resulting genome-wide maps of chromatin state annotationsread more
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Integrative analysis of 111 reference human epigenomes
Anshul Kundaje,Wouter Meuleman,Wouter Meuleman,Jason Ernst,Misha Bilenky,Angela Yen,Angela Yen,Alireza Heravi-Moussavi,Pouya Kheradpour,Pouya Kheradpour,Zhizhuo Zhang,Zhizhuo Zhang,Jianrong Wang,Jianrong Wang,Michael J. Ziller,Viren Amin,John W. Whitaker,Matthew D. Schultz,Lucas D. Ward,Lucas D. Ward,Abhishek Sarkar,Abhishek Sarkar,Gerald Quon,Gerald Quon,Richard Sandstrom,Matthew L. Eaton,Matthew L. Eaton,Yi-Chieh Wu,Yi-Chieh Wu,Andreas R. Pfenning,Andreas R. Pfenning,Xinchen Wang,Xinchen Wang,Melina Claussnitzer,Melina Claussnitzer,Yaping Liu,Yaping Liu,Cristian Coarfa,R. Alan Harris,Noam Shoresh,Charles B. Epstein,Elizabeta Gjoneska,Elizabeta Gjoneska,Danny Leung,Wei Xie,R. David Hawkins,Ryan Lister,Chibo Hong,Philippe Gascard,Andrew J. Mungall,Richard A. Moore,Eric Chuah,Angela Tam,Theresa K. Canfield,R. Scott Hansen,Rajinder Kaul,Peter J. Sabo,Mukul S. Bansal,Mukul S. Bansal,Mukul S. Bansal,Annaick Carles,Jesse R. Dixon,Kai How Farh,Soheil Feizi,Soheil Feizi,Rosa Karlic,Ah Ram Kim,Ah Ram Kim,Ashwinikumar Kulkarni,Daofeng Li,Rebecca F. Lowdon,Ginell Elliott,Tim R. Mercer,Shane Neph,Vitor Onuchic,Paz Polak,Paz Polak,Nisha Rajagopal,Pradipta R. Ray,Richard C Sallari,Richard C Sallari,Kyle Siebenthall,Nicholas A Sinnott-Armstrong,Nicholas A Sinnott-Armstrong,Michael Stevens,Robert E. Thurman,Jie Wu,Bo Zhang,Xin Zhou,Arthur E. Beaudet,Laurie A. Boyer,Philip L. De Jager,Philip L. De Jager,Peggy J. Farnham,Susan J. Fisher,David Haussler,Steven J.M. Jones,Steven J.M. Jones,Wei Li,Marco A. Marra,Michael T. McManus,Shamil R. Sunyaev,Shamil R. Sunyaev,James A. Thomson,Thea D. Tlsty,Li-Huei Tsai,Li-Huei Tsai,Wei Wang,Robert A. Waterland,Michael Q. Zhang,Lisa Helbling Chadwick,Bradley E. Bernstein,Bradley E. Bernstein,Bradley E. Bernstein,Joseph F. Costello,Joseph R. Ecker,Martin Hirst,Alexander Meissner,Aleksandar Milosavljevic,Bing Ren,John A. Stamatoyannopoulos,Ting Wang,Manolis Kellis,Manolis Kellis +123 more
TL;DR: It is shown that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease.
Integrative analysis of 111 reference human epigenomes
Anshul Kundaje,Wouter Meuleman,Jason Ernst,Angela Yen,Pouya Kheradpour,Zhizhuo Zhang,Jianrong Wang,Lucas D. Ward,Abhishek Sarkar,Gerald Quon,Matthew L. Eaton,Yi-Chieh Wu,Andreas R. Pfenning,Xinchen Wang,Melina Claussnitzer,Yaping Liu,Mukul S. Bansal,Soheil Feizi-Khankandi,Ah Ram Kim,Richard C Sallari,Nicholas A Sinnott-Armstrong,Laurie A. Boyer,Elizabeta Gjoneska,Li-Huei Tsai,Manolis Kellis +24 more
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
Journal ArticleDOI
The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells
Cole Trapnell,Davide Cacchiarelli,Davide Cacchiarelli,Jonna Grimsby,Prapti Pokharel,Shuqiang Li,Michael A. Morse,Michael A. Morse,Niall J. Lennon,Kenneth J. Livak,Tarjei S. Mikkelsen,Tarjei S. Mikkelsen,John L. Rinn,John L. Rinn,John L. Rinn +14 more
TL;DR: Monocle is described, an unsupervised algorithm that increases the temporal resolution of transcriptome dynamics using single-cell RNA-Seq data collected at multiple time points that revealed switch-like changes in expression of key regulatory factors, sequential waves of gene regulation, and expression of regulators that were not known to act in differentiation.
Journal ArticleDOI
An atlas of active enhancers across human cell types and tissues
Robin Andersson,Claudia Gebhard,Irene Miguel-Escalada,Ilka Hoof,Jette Bornholdt,Mette Boyd,Yun Chen,Xiaobei Zhao,Xiaobei Zhao,Christian Schmidl,Takahiro Suzuki,Evgenia Ntini,Erik Arner,Eivind Valen,Eivind Valen,Kang Li,Lucia Schwarzfischer,Dagmar Glatz,Johanna Raithel,Berit Lilje,Nicolas Rapin,Frederik Otzen Bagger,Mette Rose Jørgensen,Peter Refsing Andersen,Nicolas Bertin,Owen J. L. Rackham,A. Maxwell Burroughs,J Kenneth Baillie,Yuri Ishizu,Yuri Shimizu,Erina Furuhata,Shiori Maeda,Yutaka Negishi,Christopher J. Mungall,Terrence F. Meehan,Timo Lassmann,Masayoshi Itoh,Hideya Kawaji,Naoto Kondo,Jun Kawai,Andreas Lennartsson,Carsten O. Daub,Peter Heutink,David A. Hume,Torben Heick Jensen,Harukazu Suzuki,Yoshihide Hayashizaki,Ferenc Müller,Alistair R. R. Forrest,Piero Carninci,Michael Rehli,Albin Sandelin +51 more
TL;DR: It is shown that enhancers share properties with CpG-poor messenger RNA promoters but produce bidirectional, exosome-sensitive, relatively short unspliced RNAs, the generation of which is strongly related to enhancer activity.
Journal ArticleDOI
Functional mapping and annotation of genetic associations with FUMA
Kyoko Watanabe,Erdogan Taskesen,Erdogan Taskesen,Arjen van Bochoven,Danielle Posthuma,Danielle Posthuma +5 more
TL;DR: FUMA is a web-based bioinformatics tool that uses a combination of positional, eQTL and chromatin interaction mapping to prioritize likely causal variants and genes and directly aid in generating hypotheses that are testable in functional experiments aimed at proving causal relations.
References
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The Human Genome Browser at UCSC
W. James Kent,Charles W. Sugnet,Terrence S. Furey,Krishna M. Roskin,Tom H. Pringle,Alan M. Zahler,and David Haussler +6 more
TL;DR: A mature web tool for rapid and reliable display of any requested portion of the genome at any scale, together with several dozen aligned annotation tracks, is provided at http://genome.ucsc.edu.
“Bioinformatics” 특집을 내면서
TL;DR: Assessment of medical technology in the context of commercialization with Bioentrepreneur course, which addresses many issues unique to biomedical products.
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Mapping and analysis of chromatin state dynamics in nine human cell types
Jason Ernst,Pouya Kheradpour,Pouya Kheradpour,Tarjei S. Mikkelsen,Noam Shoresh,Lucas D. Ward,Lucas D. Ward,Charles B. Epstein,Xiaolan Zhang,Li Wang,Robbyn Issner,Michael Coyne,Manching Ku,Manching Ku,Manching Ku,Timothy Durham,Manolis Kellis,Manolis Kellis,Bradley E. Bernstein,Bradley E. Bernstein,Bradley E. Bernstein +20 more
TL;DR: This study presents a general framework for deciphering cis-regulatory connections and their roles in disease, and maps nine chromatin marks across nine cell types to systematically characterize regulatory elements, their cell-type specificities and their functional interactions.
Journal ArticleDOI
Identification of Functional Elements and Regulatory Circuits by Drosophila modENCODE
Sushmita Roy,Jason Ernst,Peter V. Kharchenko,Pouya Kheradpour,Nicolas Nègre,Matthew L. Eaton,Jane M. Landolin,Christopher A. Bristow,Lijia Ma,Michael F. Lin,Stefan Washietl,Bradley I. Arshinoff,Ferhat Ay,Patrick E. Meyer,Nicolas Robine,Nicole L. Washington,Luisa Di Stefano,Eugene Berezikov,Christopher D. Brown,Rogerio Candeias,Joseph W. Carlson,Adrian Carr,Irwin Jungreis,Daniel Marbach,Rachel Sealfon,Michael Y. Tolstorukov,Sebastian Will,Artyom A. Alekseyenko,Carlo G. Artieri,Benjamin W. Booth,Angela N. Brooks,Qi Dai,Carrie A. Davis,Michael O. Duff,X. Feng,Andrey A. Gorchakov,Tingting Gu,Jorja G. Henikoff,Philipp Kapranov,Renhua Li,Heather K. MacAlpine,John H. Malone,Aki Minoda,Jared T. Nordman,Katsutomo Okamura,Marc D. Perry,Sara K. Powell,Nicole C. Riddle,Akiko Sakai,Anastasia Samsonova,Jeremy E. Sandler,Yuri B. Schwartz,Noa Sher,Rebecca Spokony,David Sturgill,Marijke J. van Baren,Kenneth H. Wan,Li Yang,Charles Yu,Elise A. Feingold,Peter J. Good,Mark S. Guyer,Rebecca F. Lowdon,Kami Ahmad,Justen Andrews,Bonnie Berger,Steven E. Brenner,Michael R. Brent,Lucy Cherbas,Sarah C. R. Elgin,Thomas R. Gingeras,Robert L. Grossman,Roger A. Hoskins,Thomas C. Kaufman,W. J. Kent,Mitzi I. Kuroda,Terry L. Orr-Weaver,Norbert Perrimon,Vincenzo Pirrotta,James W. Posakony,Bing Ren,Steven Russell,Peter Cherbas,Brenton R. Graveley,Suzanna E. Lewis,Gos Micklem,Brian Oliver,Peter J. Park,Susan E. Celniker,Steven Henikoff,Gary H. Karpen,Eric C. Lai,David M. MacAlpine,Lincoln Stein,Kevin P. White,Manolis Kellis +95 more
TL;DR: The Drosophila Encyclopedia of DNA Elements (modENCODE) project as mentioned in this paper has been used to map transcripts, histone modifications, chromosomal proteins, transcription factors, replication proteins and intermediates, and nucleosome properties across a developmental time course and in multiple cell lines.
Journal Article
Identification of functional elements and regulatory circuits by Drosophila modENCODE
TL;DR: Two studies identified regions of the nematode and fly genomes that show highly occupied targets (or HOT) regions where DNA was bound by more than 15 of the transcription factors analyzed and the expression of related genes were characterized.
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