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Content type: Method
| 21 March 2019

Melissa: Bayesian clustering and imputation of single-cell methylomes

Authors: Chantriolnt-Andreas Kapourani and Guido Sanguinetti
Content type: Method
| 21 March 2019

TAD fusion score: discovery and ranking the contribution of deletions to genome structure

Authors: Linh Huynh and Fereydoun Hormozdiari
Content type: Method
| 19 March 2019

PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells

Authors: F. Alexander Wolf, Fiona K. Hamey, Mireya Plass, Jordi Solana, Joakim S. Dahlin, Berthold Göttgens, Nikolaus Rajewsky, Lukas Simon and Fabian J. Theis
Content type: Method
| 19 March 2019

Tandem-genotypes: robust detection of tandem repeat expansions from long DNA reads

Authors: Satomi Mitsuhashi, Martin C. Frith, Takeshi Mizuguchi, Satoko Miyatake, Tomoko Toyota, Hiroaki Adachi, Yoko Oma, Yoshihiro Kino, Hiroaki Mitsuhashi and Naomichi Matsumoto
Content type: Research
| 19 March 2019

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…

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Content type: Comment
| 30 July 2014

The Kardashian index: a measure of discrepant social media profile for scientists

Authors: Neil Hall
Content type: Review
| 26 January 2016

A survey of best practices for RNA-seq data analysis

Authors: Ana Conesa, Pedro Madrigal, Sonia Tarazona, David Gomez-Cabrero, Alejandra Cervera, Andrew McPherson, Michał Wojciech Szcześniak, Daniel J. Gaffney, Laura L. Elo, Xuegong Zhang and Ali Mortazavi

The Erratum to this article has been published in Genome Biology 2016 17:181
Content type: Method
| 27 October 2010

Differential expression analysis for sequence count data

Authors: Simon Anders and Wolfgang Huber
Content type: METHOD
| 5 December 2014

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Authors: Michael I Love, Wolfgang Huber and Simon Anders
Content type: Research
| 10 December 2013

DNA methylation age of human tissues and cell types

Authors: Steve Horvath

The Erratum to this article has been published in Genome Biology 2015 16:96

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Genome Biology

Featured Article: Improving the usability and archival stability of bioinformatics software

Call for papers: benchmarking studies

Articles

Melissa: Bayesian clustering and imputation of single-cell methylomes

TAD fusion score: discovery and ranking the contribution of deletions to genome structure

PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells

Tandem-genotypes: robust detection of tandem repeat expansions from long DNA reads

Measuring the reproducibility and quality of Hi-C data

The Kardashian index: a measure of discrepant social media profile for scientists

A survey of best practices for RNA-seq data analysis

Differential expression analysis for sequence count data

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

DNA methylation age of human tissues and cell types

Latest articles from Genome Medicine

Circular RNAs as promising biomarkers in cancer: detection, function, and beyond

Correction to: NSAID use and somatic exomic mutations in Barrett’s esophagus

A decade of Genome Medicine: toward precision medicine

Focus: Cancer

Reviews, Research highlights and commentaries

Latest article collections

Latest Tweets

From the blog

Genome Biology at Genome Informatics

Bigger CRISPR- Cas12a toolbox, wider genomic coverage and higher targeting efficiencies

Our insights from engineering genomes

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