AFCMHeatMap: A shiny web tool for heatmap generation of genetic expression datasets using R packages

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1 Bioinformatics Department, Armed Forces College of Medicine (AFCM), Cairo, Egypt
2 Biomedical sciences Department, Armed Forces College of Medicine (AFCM), Cairo, Egypt
3 Microbiology Department, Armed Forces College of Medicine (AFCM), Cairo, Egypt
DOI
10.7287/peerj.preprints.2961v2
Published
Accepted
Subject Areas
Bioinformatics, Computational Biology, Genetics, Genomics, Computational Science
Keywords
Bioinformatics, Genomics, Shiny, R Packages, AFCMHeatMap
Copyright
© 2017 Tarek et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Tarek M, Shafei AS, Ali MA. 2017. AFCMHeatMap: A shiny web tool for heatmap generation of genetic expression datasets using R packages. PeerJ Preprints 5:e2961v2

Abstract

Generating heatmaps of genetic datasets is a 2D graphical visualization of data where the individual expression values contained in a matrix are represented as colors. Herein, we describe AFCMHeatMap a shiny web App that integrates quantitative interaction of genomics data and results from microarrays or RNA-Seq to highlight expression levels of various genetic datasets with a *.CSV input file. The application also facilitates downloading heatmaps as a supplementary material for user's publications. Written in R using Shiny framework, it is a user-friendly framework for interactive expression data visualization that can be easily deployed without any restrictions to any operating system used by any online user.

Author Comment

The updated version of the preprint have addressed citation issues regarding open-source code provided with AFCMHeatMap, It also addressed previous literature content to be properly cited and paraphrased in the preprint. The source code repository on github have been documented with changes regarding used functions of R packages that have been inspired by MicroScope shiny App for proper citation and documentation of modified codes and functions of required R packages.