Literature DB >> 28177067

GLINT: a user-friendly toolset for the analysis of high-throughput DNA-methylation array data.

Elior Rahmani1, Reut Yedidim1, Liat Shenhav2, Regev Schweiger1, Omer Weissbrod2,3, Noah Zaitlen4, Eran Halperin5,6.   

Abstract

SUMMARY: GLINT is a user-friendly command-line toolset for fast analysis of genome-wide DNA methylation data generated using the Illumina human methylation arrays. GLINT, which does not require any programming proficiency, allows an easy execution of Epigenome-Wide Association Study analysis pipeline under different models while accounting for known confounders in methylation data.
AVAILABILITY AND IMPLEMENTATION: GLINT is a command-line software, freely available at https://github.com/cozygene/glint/releases . It requires Python 2.7 and several freely available Python packages. Further information and documentation as well as a quick start tutorial are available at http://glint-epigenetics.readthedocs.io . CONTACT: elior.rahmani@gmail.com or ehalperin@cs.ucla.edu.
© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

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Year:  2017        PMID: 28177067      PMCID: PMC5870777          DOI: 10.1093/bioinformatics/btx059

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  12 in total

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Authors:  Shaun Purcell; Benjamin Neale; Kathe Todd-Brown; Lori Thomas; Manuel A R Ferreira; David Bender; Julian Maller; Pamela Sklar; Paul I W de Bakker; Mark J Daly; Pak C Sham
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2.  Epigenome-wide association studies without the need for cell-type composition.

Authors:  James Zou; Christoph Lippert; David Heckerman; Martin Aryee; Jennifer Listgarten
Journal:  Nat Methods       Date:  2014-01-26       Impact factor: 28.547

3.  Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays.

Authors:  Martin J Aryee; Andrew E Jaffe; Hector Corrada-Bravo; Christine Ladd-Acosta; Andrew P Feinberg; Kasper D Hansen; Rafael A Irizarry
Journal:  Bioinformatics       Date:  2014-01-28       Impact factor: 6.937

4.  Sparse PCA corrects for cell type heterogeneity in epigenome-wide association studies.

Authors:  Elior Rahmani; Noah Zaitlen; Yael Baran; Celeste Eng; Donglei Hu; Joshua Galanter; Sam Oh; Esteban G Burchard; Eleazar Eskin; James Zou; Eran Halperin
Journal:  Nat Methods       Date:  2016-03-28       Impact factor: 28.547

5.  Comprehensive analysis of DNA methylation data with RnBeads.

Authors:  Yassen Assenov; Fabian Müller; Pavlo Lutsik; Jörn Walter; Thomas Lengauer; Christoph Bock
Journal:  Nat Methods       Date:  2014-09-28       Impact factor: 28.547

6.  Genome-wide methylation data mirror ancestry information.

Authors:  Elior Rahmani; Liat Shenhav; Regev Schweiger; Paul Yousefi; Karen Huen; Brenda Eskenazi; Celeste Eng; Scott Huntsman; Donglei Hu; Joshua Galanter; Sam S Oh; Melanie Waldenberger; Konstantin Strauch; Harald Grallert; Thomas Meitinger; Christian Gieger; Nina Holland; Esteban G Burchard; Noah Zaitlen; Eran Halperin
Journal:  Epigenetics Chromatin       Date:  2017-01-03       Impact factor: 4.954

7.  Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls.

Authors: 
Journal:  Nature       Date:  2007-06-07       Impact factor: 49.962

8.  Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray.

Authors:  Yi-an Chen; Mathieu Lemire; Sanaa Choufani; Darci T Butcher; Daria Grafodatskaya; Brent W Zanke; Steven Gallinger; Thomas J Hudson; Rosanna Weksberg
Journal:  Epigenetics       Date:  2013-01-11       Impact factor: 4.528

9.  A gene-based association method for mapping traits using reference transcriptome data.

Authors:  Eric R Gamazon; Heather E Wheeler; Kaanan P Shah; Sahar V Mozaffari; Keston Aquino-Michaels; Robert J Carroll; Anne E Eyler; Joshua C Denny; Dan L Nicolae; Nancy J Cox; Hae Kyung Im
Journal:  Nat Genet       Date:  2015-08-10       Impact factor: 38.330

10.  Accounting for cellular heterogeneity is critical in epigenome-wide association studies.

Authors:  Andrew E Jaffe; Rafael A Irizarry
Journal:  Genome Biol       Date:  2014-02-04       Impact factor: 13.583

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  21 in total

1.  PyMethylProcess-convenient high-throughput preprocessing workflow for DNA methylation data.

Authors:  Joshua J Levy; Alexander J Titus; Lucas A Salas; Brock C Christensen
Journal:  Bioinformatics       Date:  2019-12-15       Impact factor: 6.937

2.  Maternal fatty acid concentrations and newborn DNA methylation.

Authors:  Sonia L Robinson; Sunni L Mumford; Weihua Guan; Xuehuo Zeng; Keewan Kim; Jeannie G Radoc; Mai-Han Trinh; Kerry Flannagan; Enrique F Schisterman; Edwina Yeung
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3.  Maternal caffeine intake and DNA methylation in newborn cord blood.

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Review 4.  Systems Genetics for Mechanistic Discovery in Heart Diseases.

Authors:  Christoph D Rau; Aldons J Lusis; Yibin Wang
Journal:  Circ Res       Date:  2020-06-04       Impact factor: 17.367

5.  Grandmaternal stress during pregnancy and DNA methylation of the third generation: an epigenome-wide association study.

Authors:  F Serpeloni; K Radtke; S G de Assis; F Henning; D Nätt; T Elbert
Journal:  Transl Psychiatry       Date:  2017-08-15       Impact factor: 6.222

6.  A phenotypic and genomics approach in a multi-ethnic cohort to subtype systemic lupus erythematosus.

Authors:  Cristina M Lanata; Ishan Paranjpe; Joanne Nititham; Kimberly E Taylor; Milena Gianfrancesco; Manish Paranjpe; Shan Andrews; Sharon A Chung; Brooke Rhead; Lisa F Barcellos; Laura Trupin; Patricia Katz; Maria Dall'Era; Jinoos Yazdany; Marina Sirota; Lindsey A Criswell
Journal:  Nat Commun       Date:  2019-08-29       Impact factor: 14.919

7.  TOAST: improving reference-free cell composition estimation by cross-cell type differential analysis.

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Journal:  Genome Biol       Date:  2019-09-04       Impact factor: 13.583

8.  Perfluorooctanoic acid (PFOA) or perfluorooctane sulfonate (PFOS) and DNA methylation in newborn dried blood spots in the Upstate KIDS cohort.

Authors:  Sonia L Robinson; Xuehuo Zeng; Weihua Guan; Rajeshwari Sundaram; Pauline Mendola; Diane L Putnick; Robert A Waterland; Chathura J Gunasekara; Kurunthachalam Kannan; Chongjing Gao; Erin M Bell; Edwina H Yeung
Journal:  Environ Res       Date:  2020-12-30       Impact factor: 6.498

9.  Characterization of cross-tissue genetic-epigenetic effects and their patterns in schizophrenia.

Authors:  Dongdong Lin; Jiayu Chen; Nora Perrone-Bizzozero; Juan R Bustillo; Yuhui Du; Vince D Calhoun; Jingyu Liu
Journal:  Genome Med       Date:  2018-02-26       Impact factor: 11.117

10.  BayesCCE: a Bayesian framework for estimating cell-type composition from DNA methylation without the need for methylation reference.

Authors:  Elior Rahmani; Regev Schweiger; Liat Shenhav; Theodora Wingert; Ira Hofer; Eilon Gabel; Eleazar Eskin; Eran Halperin
Journal:  Genome Biol       Date:  2018-09-21       Impact factor: 13.583

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