RNAseq Analysis

Overview:

The RNAseq analysis block will be divided in three sections:

    1. RNAseq experimental design and read preprocessing
    2. Read mapping and differential expression.
    3. Data mining.

1. RNAseq Experimental Design:

In this section will be discussed the different sequencing platforms and the associated problems related with heterosygosity and polyploidy, what can be used as a reference or estimated number of reads per replicate.

To download the presentation: RNASeq_ExpDesign2013

Exercises: RNASeq_ExpDesign_exercises

Solutions: RNASeq_ExpDesign_solutions

2. RNA-seq Mapping and Differential Expression:

In this section we will take a look at how to use Tophat2 and Cufflinks for read mapping and differential expression detection.

Presentation and Exercises Download: Bioinfo_2013_rnaseq

3. RNA-seq SNP calling

In this section we will take a look at how to use Samtools mpileup for SNP calling, and SnpEff for effect prediction

Presentation and Exercises Download:
SNP calling

4. RNA-seq Data Mining

In this section we will take a look to the data mining for RNAseq data, specifically to the clustering and classification methods (GOterms analysis).

Lecture: BTIBioinfo2013_DataMining

Exercises: BTIBioinfo2013_DataMining_Exercises

Data: cuffdata_at_bioinfo2013.zip
cuffdata_at_bioinfo2013_v2.zip

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