File:Fig2 Xie BMCBioinfo21 22.png

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Summary

Description

Figure 2. Screenshots of our tools for popularity and performance analysis of the GSA field. a GSARefDB: A screenshot of the R/shiny interface to GSARefDB, showing the options of searching by year, tool name, paper’s first author, title, type of GSA, and programming language. b GSA BenchmarKING: One jupyter notebook containing an R workflow for benchmarking single-sample GSA methods, and one shiny app with the same purpose. Both tools display sensitivity, specificity, and precision plots for all the methods under study.

Source

Xie, C.; Jauhari, S.; Mora, A. (2021). "Popularity and performance of bioinformatics software: The case of gene set analysis". BMC Bioinformatics 22: 191. doi:10.1186/s12859-021-04124-5. 

Date

2021

Author

Xie, C.; Jauhari, S.; Mora, A.

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Creative Commons Attribution 4.0 International

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current23:08, 21 April 2021Thumbnail for version as of 23:08, 21 April 20211,416 × 946 (385 KB)Shawndouglas (talk | contribs)