RNA-Seq analysis for differential expression

We first perform quality control of the sequence reads to detect biases or leftover adaptors.
We then map the reads to the reference genome with use of a transcript database model.
We perform a detailed QC analysis of the mapping results to again detect potential problems.
The mapping data is adjusted to compensate for artifacts like duplicates.
The mappings are used to obtain transcript counts usable for differential expression.
The count tables are merged and used to compute differential expression using several programs.
We START a typical functional analysis of the obtained results similar to what is done for microarray data in order to exemplify handy tools and commercial alternatives.

The code pieces used during the training are made available through our Wiki as well as detailed results and can be copied and adapted for own user needs with minimal edits. Key results have been saved to our server and can be downloaded to fully reproduce the training.

Scientific topics: RNA-Seq, Gene expression

Target audience: Life Science Researchers, PhD students, beginner bioinformaticians, post-docs

Authors: St├®phane Plaisance

Remote created date: 2016-04-22

Remote updated date: 2017-10-09

RNA-Seq analysis for differential expression https://tess.elixir-europe.org/materials/rna-seq-analysis-for-differential-expression We first perform quality control of the sequence reads to detect biases or leftover adaptors. We then map the reads to the reference genome with use of a transcript database model. We perform a detailed QC analysis of the mapping results to again detect potential problems. The mapping data is adjusted to compensate for artifacts like duplicates. The mappings are used to obtain transcript counts usable for differential expression. The count tables are merged and used to compute differential expression using several programs. We START a typical functional analysis of the obtained results similar to what is done for microarray data in order to exemplify handy tools and commercial alternatives. The code pieces used during the training are made available through our Wiki as well as detailed results and can be copied and adapted for own user needs with minimal edits. Key results have been saved to our server and can be downloaded to fully reproduce the training. RNA-Seq Gene expression Life Science Researchers PhD students beginner bioinformaticians post-docs 2016-04-22 2017-10-09