Tool:Web interface applications for performance comparison of R/ Bioconductor DE tools in RNA-seq
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8.8 years ago
Ming Jie ▴ 10

Hi all, I have created a set of web interface applications ("Call Sense", "Depth Sense" and "Run Sense") under the collective term "Deep Sense", that supports the following R/ Bioconductor DE tools: edgeR, DESeq, DESeq2, NOISeq, baySeq, EBSeq and SAMseq using R package: "shiny", which allows users to evaluate their DE test results, investigate and compare their key performance indicators (sensitivity, precision etc) and to identify their common DE genes more conveniently and efficiently from their RNA-seq data (the raw gene counts from HTSeq-count) by adjusting FDR values and normalization procedures.

This begun as part of my junior year research project to investigate performances of some R/ Bioconductor DE tools when the trouble of working on different nomenclatures of each DE pipeline due to their distinct protocols and functions becomes pronounced. Furthermore in most cases, the process of identifying and comparing the appropriate DE pipeline in literature for one's experimental needs could be improved and shortened efficiently by reducing to a few key interests that would obviously influence the choice: their DE results, their performance indicators and their common DE genes while allowing one to retain the control of adjusting FDR values and choosing the intended normalization option.

The source codes and supporting materials can be viewed in: https://github.com/mingjiewong/Deep-Sense with the instructions given for installation. For convenience of users, the installation procedures simply begins by installing the R package "shiny" and the 7 fore-mentioned R/ Bioconductor pipelines. Then download the three folders "Call Sense", "Depth Sense" and "Run Sense" which can found in: http://sourceforge.net/projects/deepsense/ under Files and place them into your own R's working directory. To run any one of these web interface application, simply type as follows into R:

E.g. To run Call Sense

library(shiny)
runApp("Call Sense")

E.g. To run Depth Sense

library(shiny)
runApp("Depth Sense")

E.g. To run Run Sense

library(shiny)
runApp("Run Sense")

I have used it quite extensively for my own project and I hope at least someone else can find it useful as well. Thanks for the support and suggestions!

RNA-Seq R • 2.0k views
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