RNA-seq data analyss with different approachs.
RNA-Seq (RNA sequencing ) also called whole transcriptome sequncing use next-generation sequeincing (NGS) to reveal the presence and quantity of RNA in a biolgical sample at a given moment. As we discuss during the talk we can use different approach and different tools. Here we present the DEseq2 vignette it wwas composed using STAR and HTseqcount and then Deseq2. The other part we show kallisto Unfortunately our computer not allow the work some stap was only for demonstration purpose.
In this example we will use a downsampled version of simulated Drosophila melanogaster RNA-seq data used by Trapnell et al. 2012. These include two conditions (C1 and C2), each containing three replicates (R1, R2, and R3) sequenced as a paired end library. Thus in total there are 12 fastq datasets.
[Galaxy version] (https://galaxyproject.org/tutorials/rb_rnaseq/#lets-try-it)
Here we use the snakemake version of rna-seq pipeline with STAR and htseqcount and DESEq2:
git clone https://github.com/bioinfo-dirty-jobs/rna-seq-star-deseq2
cd rna-seq-star-deseq2
conda create -n rnaseq
conda activate rnaseq
conda install snakemake