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GeneNetWeaver: in silico benchmark generation and performance profiling of network inference methods

Thomas Schaffter, Daniel Marbach, Dario Floreano
2011 Computer applications in the biosciences : CABIOS  
Motivation: Over the last decade, numerous methods have been developed for inference of regulatory networks from gene expression data.  ...  However, accurate and systematic evaluation of these methods is hampered by the difficulty of constructing adequate benchmarks and the lack of tools for a differentiated analysis of network predictions  ...  ACKNOWLEDGEMENT The authors would like to express their thanks to Gilles Roulet for his collaboration in software development, and Steffen Wischmann, Peter Dürr and Pradeep Fernando for their careful reading  ... 
doi:10.1093/bioinformatics/btr373 pmid:21697125 fatcat:ee6sjhtukzcg5dkaom36wr5sqy

Toward a gold standard for benchmarking gene set enrichment analysis

2019 Briefings in Bioinformatics  
Although gene set enrichment analysis has become an integral part of high-throughput gene expression data analysis, the assessment of enrichment methods remains rudimentary and ad hoc.  ...  We develop an extensible framework for reproducible benchmarking of enrichment methods based on defined criteria for applicability, gene set prioritization and detection of relevant processes.  ...  The two predominantly used enrichment methods are (i) overrepresentation analysis (ORA), testing whether a gene set contains disproportionately many genes of significant expression change, and (ii) gene  ... 
doi:10.1093/bib/bbz158 pmid:32026945 pmcid:PMC7820859 fatcat:dhx7i7xqkrcezbl7vodioltvnm

Towards a gold standard for benchmarking gene set enrichment analysis [article]

Ludwig Geistlinger, Gergely Csaba, Mara Santarelli, Marcel Ramos, Lucas Schiffer, Charity W Law, Nitesh Turaga, Sean Davis, Vincent Carey, Martin Morgan, Ralf Zimmer, Levi Waldron
2019 bioRxiv   pre-print
Although gene set enrichment analysis has become an integral part of high-throughput gene expression data analysis, the assessment of enrichment methods remains rudimentary and ad hoc.  ...  Conclusion: We carried out a systematic assessment of existing enrichment methods, and identified best performing methods, but also general shortcomings in how gene set analysis is currently conducted.  ...  LW was supported by grant U24CA18099 from the National Cancer Institute of the National Institutes of Health.  ... 
doi:10.1101/674267 fatcat:2prjptvjlbh6pgjjp7spqtj7mi

A framework of integrating gene relations from heterogeneous data sources: an experiment on Arabidopsis thaliana

J. Li, X. Li, H. Su, H. Chen, D. W. Galbraith
2006 Bioinformatics  
In this study we propose a framework for extraction and integration of gene functional relations from diverse biological data sources, including gene expression data, biological literature and genomic  ...  Evaluation of the integrated network demonstrated that relation integration could improve the reliability of relations by combining evidence from different data sources.  ...  ACKNOWLEDGEMENTS Conflict of Interest: none declared.  ... 
doi:10.1093/bioinformatics/btl345 pmid:16820427 fatcat:frdzodghy5foxclute3qib42yi

Revealing strengths and weaknesses of methods for gene network inference

D. Marbach, R. J. Prill, T. Schaffter, C. Mattiussi, D. Floreano, G. Stolovitzky
2010 Proceedings of the National Academy of Sciences of the United States of America  
G.S. and R.P. acknowledge support of the NIH Roadmap Initiative, the Columbia University Center for Multiscale Analysis Genomic and Cellular Networks (MAGNet), and the IBM Computational Biology Center.  ...  We thank all participants of the challenge for their contribution. Three anonymous reviewers provided valuable feedback on the original manuscript.  ...  We used these in silico gene networks to produce different types of steady-state and time-series gene expression data that are commonly used for gene network inference (8, 12) : steadystate expression  ... 
doi:10.1073/pnas.0913357107 pmid:20308593 pmcid:PMC2851985 fatcat:ws6lt7zybzbrpmmxspjiqztt6a

A benchmark for RNA-seq deconvolution analysis under dynamic testing environments

Haijing Jin, Zhandong Liu
2021 Genome Biology  
Background Deconvolution analyses have been widely used to track compositional alterations of cell types in gene expression data.  ...  These frameworks cover comparative analysis of 11 popular deconvolution methods under 1766 conditions.  ...  Peer review information Barbara Cheifet and Alison Cuff were the primary editors of this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.  ... 
doi:10.1186/s13059-021-02290-6 pmid:33845875 pmcid:PMC8042713 fatcat:kdqd4s6ddvfk3fnprguytoidy4

Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: a comparative review

L. Lahti, M. Schafer, H.-U. Klein, S. Bicciato, M. Dugas
2012 Briefings in Bioinformatics  
A standard integration task in cancer studies is to identify altered genomic regions that induce changes in the expression of the associated genes based on joint analysis of genome-wide gene expression  ...  A transparent benchmarking procedure is introduced to quantitatively compare the cancer gene prioritization performance of the alternative methods.  ...  Figure 1 : 1 AUC values in ROC analysis quantify cancer gene prioritization performance of the methods for the five benchmarking data sets.  ... 
doi:10.1093/bib/bbs005 pmid:22441573 pmcid:PMC3548603 fatcat:f4f2dmgydzewzepiah6iob2tcy

A systematic approach to infer biological relevance and biases of gene network structures

A. V. Antonov
2006 Nucleic Acids Research  
By the analyses of real data we demonstrate that the potential application of BIOREL ranges from various benchmarking purposes to systematic analysis of the network biology.  ...  Although several tools have been proposed for analysing the enrichment of functional categories in a set of genes, none of them is suitable for evaluating the biological relevance of the gene network.  ...  Thus, it can be used for systematic benchmarking purposes to evaluate the potential of various data sources to reveal biological relations between genes as well as to detect systematic biases related to  ... 
doi:10.1093/nar/gnj002 pmid:16407322 pmcid:PMC1326251 fatcat:mn5f7my2crbmlmipdnfftlxgxi

Differential expression analysis of log-ratio transformed counts: benchmarking methods for RNA-Seq data [article]

Thomas Quinn, Tamsyn Crowley, Mark Richardson
2017 bioRxiv   pre-print
The latter was previously used to benchmark dozens of conventional RNA-Seq differential expression methods, enabling us to directly compare transformation-based approaches.  ...  expression methods.  ...  Results Benchmark using simulated data In order to evaluate the performance of ALDEx2 as a differential expression (DE) method for RNA-Seq data, we tested its performance on three data sets using several  ... 
doi:10.1101/231175 fatcat:6gr5ck2xurbvrd2rowe2g5qg7e

Benchmarking UMI-based single cell RNA-sequencing preprocessing workflows [article]

Yue You, Luyi Tian, Shian Su, Xueyi Dong, Jafar Sheikh Jabbari, Peter F Hickey, Matthew E Ritchie
2021 bioRxiv   pre-print
This includes methods for data preprocessing, which assign sequencing reads to genes to create count matrices for downstream analysis.  ...  Here, we systematically benchmark the performance of 9 end-to-end preprocessing workflows (Cell Ranger, Optimus, salmon alevin, kallisto bustools, dropSeqPipe, scPipe, zUMIs, celseq2 and scruff) using  ...  We next investigated the concordance of gene expression across workflows and compared the correlation of gene expression between scPipe and other methods using common cells and genes ( Figure 3C ).  ... 
doi:10.1101/2021.06.17.448895 fatcat:5254sfwlbngifabgb5xpnbz4zu

scCODE: an R package for personalized differentially expressed gene detection on single-cell RNA-sequencing data [article]

jiawei Zou, miaochen Wang, zhen Zhang, zheqi Liu, xiaobin Zhang, rong Hua, ke Chen, xin Zou, Jie Hao
2021 bioRxiv   pre-print
Differential expression (DE) gene detection in single-cell RNA-seq (scRNA-seq) data is a key step to understand the biological question investigated.  ...  Existing tools don't take gene filtering into consideration, and couldn't evaluate DE performance on real datasets without prior knowledge of true results.  ...  Acknowledgements We thank Li Xuejing for her help of Figure . 2. preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.  ... 
doi:10.1101/2021.11.18.469072 fatcat:i5wjhq7ayfegrd7oa64ega226y

Classification across gene expression microarray studies

Andreas Buness, Markus Ruschhaupt, Ruprecht Kuner, Achim Tresch
2009 BMC Bioinformatics  
We assessed the potential benefit of data integration on the classification accuracy and systematically evaluated the generalization performance of selected methods on four breast cancer studies comprising  ...  In particular, the better predictive results of DV in across platform classification indicate higher robustness of the classifier when trained on single channel data and applied to gene expression ratios  ...  In addition, the work was supported by a grant of the German National Genome Research Network (NGFN) founded by the German Federal Ministry for Education and Research (RK by NGFN grant 01GR0101 and MR  ... 
doi:10.1186/1471-2105-10-453 pmid:20042109 pmcid:PMC2811711 fatcat:yreubhimwjgbtoi7qfcn7jbny4

Cyclebase.org a comprehensive multi-organism online database of cell-cycle experiments

N. P. Gauthier, M. E. Larsen, R. Wernersson, U. de Lichtenberg, L. J. Jensen, S. Brunak, T. S. Jensen
2007 Nucleic Acids Research  
However, data from these experiments are not easy to access, combine and evaluate.  ...  We have developed a centralized database with an easy-to-use interface, Cyclebase.org, for viewing and downloading these data.  ...  In all four organisms, the combined analysis of all data within an organism presented by Cyclebase outperforms all existing methods or suggested sets of periodically expressed genes.  ... 
doi:10.1093/nar/gkm729 pmid:17940094 pmcid:PMC2238932 fatcat:xyrpqjpnfrd4zi4sompkl75tei

Benchmark and integration of resources for the estimation of human transcription factor activities

Luz Garcia-Alonso, Christian H. Holland, Mahmoud M. Ibrahim, Denes Turei, Julio Saez-Rodriguez
2019 Genome Research  
regulons from large gene expression data sets.  ...  The prediction of transcription factor (TF) activities from the gene expression of their targets (i.e., TF regulon) is becoming a widely used approach to characterize the functional status of transcriptional  ...  Acknowledgments We thank Anthony Mathelier and Manu Kumar for useful feedback on the manuscript.  ... 
doi:10.1101/gr.240663.118 pmid:31340985 pmcid:PMC6673718 fatcat:oc2fyvmaf5et5gubbqgr35syae

Systematic benchmarking of omics computational tools

Serghei Mangul, Lana S. Martin, Brian L. Hill, Angela Ka-Mei Lam, Margaret G. Distler, Alex Zelikovsky, Eleazar Eskin, Jonathan Flint
2019 Nature Communications  
The increasing dependence of scientists on these powerful software tools creates a need for systematic assessment of these methods, known as benchmarking.  ...  Adopting a standardized benchmarking practice could help researchers who use omics data to better leverage recent technological innovations.  ...  For example, surveyed benchmarking studies in the domain of microbiome analysis exclusively used mock community, and the domain of flow cytometry analysis used only expert manual evaluation.  ... 
doi:10.1038/s41467-019-09406-4 pmid:30918265 pmcid:PMC6437167 fatcat:lh4gyl237jhxvlcwnoovgeeefi
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