Insights into organ-specific pathogen defense responses in plants: RNA-seq ... 7thSpace Interactive (press release) A total of 483 million paired end Illumina RNA-seq reads were generated, representing the transcription of around 30,000 potato genes.
(This article was first published on Wiekvoet, and kindly contributed to R-bloggers) Last week I looked at two-way cross-over studies and followed the example of Schütz (http://bebac.at/) in the analysis.
Update: I am aware the table of contents are being displayed in bullet form as I intended. The web template I'm using seems to be buggy. It also seems to think this page is in Indonesian...Working on it!
This is a combined course in RNA-seq and functional annotation aimed at scientists working in next generation sequencing transcriptomics who want to extract the best possible information from their data.
The first part of the course is a practical tutorial on Blast2GO, the most popular framework for functional annotation of sequences. Participants will also learn how to generate de novo functional labels, such as GO terms and KEGG pathways, for their sequence data and how to extract relevant information from these annotations, i.e. visualization and enrichment analysis using the Gene Ontology. The second part of the course covers many relevant aspects of RNA-seq analysis, form quality control, to mapping, reconstruction of transcripts and differential expression. Participants will learn how to deal with RNAseq data both in the presence and absence of a reference genome.
At the end of the course, participants can expect to have acquired skills to use multiple software tools to analise RNA-seq data and use Blast2GO.
The course will be based on the use of Blast2GO application and will mainly comprise exercises and practical cases. Participants may bring their own data.
Who should attend? Experimentalists and bioinformaticians working on EST, NextGeneration Sequencing and microarray design projects, specially (but not exclusively) of non-model species. No programming knowledge is required.
Basic knowledge in Molecular Biology and Statistics.
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