SMAGEXP: a galaxy tool suite for transcriptomics data meta-analysis. Blanck, S. & Marot, G. GigaScience, February, 2019.
SMAGEXP: a galaxy tool suite for transcriptomics data meta-analysis [link]Paper  doi  abstract   bibtex   
With the proliferation of available microarray and high-throughput sequencing experiments in the public domain, the use of meta-analysis methods increases. In these experiments, where the sample size is often limited, meta-analysis offers the possibility to considerably enhance the statistical power and give more accurate results. For those purposes, it combines either effect sizes or results of single studies in an appropriate manner. R packages metaMA and metaRNASeq perform meta-analysis on microarray and next generation sequencing (NGS) data, respectively. They are not interchangeable as they rely on statistical modeling specific to each technology.
@article{blanck_smagexp:_2019,
	title = {{SMAGEXP}: a galaxy tool suite for transcriptomics data meta-analysis},
	volume = {8},
	copyright = {All rights reserved},
	shorttitle = {{SMAGEXP}},
	url = {https://academic.oup.com/gigascience/article/8/2/giy167/5304063},
	doi = {10.1093/gigascience/giy167},
	abstract = {With the proliferation of available microarray and high-throughput sequencing experiments in the public domain, the use of meta-analysis methods increases. In these experiments, where the sample size is often limited, meta-analysis offers the possibility to considerably enhance the statistical power and give more accurate results. For those purposes, it combines either effect sizes or results of single studies in an appropriate manner. R packages metaMA and metaRNASeq perform meta-analysis on microarray and next generation sequencing (NGS) data, respectively. They are not interchangeable as they rely on statistical modeling specific to each technology.},
	language = {en},
	number = {2},
	urldate = {2019-03-07},
	journal = {GigaScience},
	author = {Blanck, Samuel and Marot, Guillemette},
	month = feb,
	year = {2019},
}

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