RNASeq Analysis | Differential Expressed Genes (DEGs) from FastQ
Currently, the second most viewed video on the channel is the identification of DEGs using the Galaxy Platform. With the recent deprecation of TopHat, it is not longer advisable to use the previous method, or rely on any online platform that you do not have complete control in.
With that, this project was set out to discover a way to accomplish similar goal of isolating the DEGs from online database using all open source tools that does not necessary relies on all-in-one platform like Galaxy, R language as well as the packages used here are all open source, and could be downloaded and stored on a local computer relatively easily and recovered when needed. Even if Bioconductor no longer support the downloading of dataset/libraries.
Thus, this video presented a way to start completely from scratch (Fastq), and how you can isolate the DEGs from your own experimental data using Rsubread and DeSEQ2. The first part is a way to convert the fastq file into a count table using featurecount, and how they can be merged into a se object. The second part of the video details how you can isolate the DEGs using an se object based on your experimental design.
Adapted from
http://www.sthda.com/english/wiki/rna...
ttps://bioconductor.org/packages/release/bioc/html/Rsubread.html
Slides
https://docs.google.com/presentation/...
Scripts Used
https://github.com/brandonyph/RSubRea...
Package Documentation
https://www.bioconductor.org/packages...
https://bioconductor.org/packages/rel...
Email: [email protected]
Github: https://github.com/brandonyph
Twitter: / brandon_yeoph
More information
bit.ly/Brandon_Yeo