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Benchmarking Studies

Benchmarking

Guest Editors: Olga Vitek and Mark D. Robinson

Tools and methods are essential for all kinds of genomic and post-genomic studies. As increasing numbers of methods are published in certain fields, it can be difficult to keep track of best practices for their use. Large scale studies that benchmark these methods on a wide range of datasets can be extremely useful to the scientific community. Genome Biology has launched the special issue on Benchmarking Studies to provide a snapshot of methodological challenges of different methods and tools.


  1. Elucidation of regulatory networks, including identification of regulatory mechanisms specific to a given biological context, is a key aim in systems biology. This has motivated the move from co-expression to ...

    Authors: Dharmesh D. Bhuva, Joseph Cursons, Gordon K. Smyth and Melissa J. Davis

    Citation: Genome Biology 2019 20:236

    Content type: Research

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  2. A large number of analysis strategies are available for DNA methylation (DNAm) array and RNA-seq datasets, but it is unclear which strategies are best to use. We compare commonly used strategies and report how...

    Authors: Jeroen van Rooij, Pooja R. Mandaviya, Annique Claringbould, Janine F. Felix, Jenny van Dongen, Rick Jansen, Lude Franke, Peter A. C. ’t Hoen, Bas Heijmans and Joyce B. J. van Meurs

    Citation: Genome Biology 2019 20:235

    Content type: Research

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  3. Human tissue is increasingly being whole genome sequenced as we transition into an era of genomic medicine. With this arises the potential to detect sequences originating from microorganisms, including pathoge...

    Authors: Abraham Gihawi, Ghanasyam Rallapalli, Rachel Hurst, Colin S. Cooper, Richard M. Leggett and Daniel S. Brewer

    Citation: Genome Biology 2019 20:208

    Content type: Research

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  4. Accurate fusion transcript detection is essential for comprehensive characterization of cancer transcriptomes. Over the last decade, multiple bioinformatic tools have been developed to predict fusions from RNA...

    Authors: Brian J. Haas, Alexander Dobin, Bo Li, Nicolas Stransky, Nathalie Pochet and Aviv Regev

    Citation: Genome Biology 2019 20:213

    Content type: Research

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  5. Single-cell RNA sequencing (scRNA-seq) is a powerful tool for studying complex biological systems, such as tumor heterogeneity and tissue microenvironments. However, the sources of technical and biological var...

    Authors: Ciara H. O’Flanagan, Kieran R. Campbell, Allen W. Zhang, Farhia Kabeer, Jamie L. P. Lim, Justina Biele, Peter Eirew, Daniel Lai, Andrew McPherson, Esther Kong, Cherie Bates, Kelly Borkowski, Matt Wiens, Brittany Hewitson, James Hopkins, Jenifer Pham…

    Citation: Genome Biology 2019 20:210

    Content type: Research

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  6. Many high-throughput experiments compare two phenotypes such as disease vs. healthy, with the goal of understanding the underlying biological phenomena characterizing the given phenotype. Because of the import...

    Authors: Tuan-Minh Nguyen, Adib Shafi, Tin Nguyen and Sorin Draghici

    Citation: Genome Biology 2019 20:203

    Content type: Research

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    The Correction to this article has been published in Genome Biology 2019 20:234

  7. A series of miRNA-disease association prediction methods have been proposed to prioritize potential disease-associated miRNAs. Independent benchmarking of these methods is warranted to assess their effectivene...

    Authors: Zhou Huang, Leibo Liu, Yuanxu Gao, Jiangcheng Shi, Qinghua Cui, Jianwei Li and Yuan Zhou

    Citation: Genome Biology 2019 20:202

    Content type: Research

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  8. Challenges are achieving broad acceptance for addressing many biomedical questions and enabling tool assessment. But ensuring that the methods evaluated are reproducible and reusable is complicated by the dive...

    Authors: Kyle Ellrott, Alex Buchanan, Allison Creason, Michael Mason, Thomas Schaffter, Bruce Hoff, James Eddy, John M. Chilton, Thomas Yu, Joshua M. Stuart, Julio Saez-Rodriguez, Gustavo Stolovitzky, Paul C. Boutros and Justin Guinney

    Citation: Genome Biology 2019 20:195

    Content type: Open Letter

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  9. Single-cell transcriptomics is rapidly advancing our understanding of the cellular composition of complex tissues and organisms. A major limitation in most analysis pipelines is the reliance on manual annotati...

    Authors: Tamim Abdelaal, Lieke Michielsen, Davy Cats, Dylan Hoogduin, Hailiang Mei, Marcel J. T. Reinders and Ahmed Mahfouz

    Citation: Genome Biology 2019 20:194

    Content type: Research

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  10. The combination of experimental evolution with whole-genome resequencing of pooled individuals, also called evolve and resequence (E&R) is a powerful approach to study the selection processes and to infer the ...

    Authors: Christos Vlachos, Claire Burny, Marta Pelizzola, Rui Borges, Andreas Futschik, Robert Kofler and Christian Schlötterer

    Citation: Genome Biology 2019 20:169

    Content type: Research

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  11. Alignment-free (AF) sequence comparison is attracting persistent interest driven by data-intensive applications. Hence, many AF procedures have been proposed in recent years, but a lack of a clearly defined be...

    Authors: Andrzej Zielezinski, Hani Z. Girgis, Guillaume Bernard, Chris-Andre Leimeister, Kujin Tang, Thomas Dencker, Anna Katharina Lau, Sophie Röhling, Jae Jin Choi, Michael S. Waterman, Matteo Comin, Sung-Hou Kim, Susana Vinga, Jonas S. Almeida, Cheong Xin Chan, Benjamin T. James…

    Citation: Genome Biology 2019 20:144

    Content type: Research

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  12. In computational biology and other sciences, researchers are frequently faced with a choice between several computational methods for performing data analyses. Benchmarking studies aim to rigorously compare th...

    Authors: Lukas M. Weber, Wouter Saelens, Robrecht Cannoodt, Charlotte Soneson, Alexander Hapfelmeier, Paul P. Gardner, Anne-Laure Boulesteix, Yvan Saeys and Mark D. Robinson

    Citation: Genome Biology 2019 20:125

    Content type: Review

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  13. In high-throughput studies, hundreds to millions of hypotheses are typically tested. Statistical methods that control the false discovery rate (FDR) have emerged as popular and powerful tools for error rate co...

    Authors: Keegan Korthauer, Patrick K. Kimes, Claire Duvallet, Alejandro Reyes, Ayshwarya Subramanian, Mingxiang Teng, Chinmay Shukla, Eric J. Alm and Stephanie C. Hicks

    Citation: Genome Biology 2019 20:118

    Content type: Research

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  14. Structural variations (SVs) or copy number variations (CNVs) greatly impact the functions of the genes encoded in the genome and are responsible for diverse human diseases. Although a number of existing SV det...

    Authors: Shunichi Kosugi, Yukihide Momozawa, Xiaoxi Liu, Chikashi Terao, Michiaki Kubo and Yoichiro Kamatani

    Citation: Genome Biology 2019 20:117

    Content type: Research

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