These have been reduced to 1% of their original size for this tutorial.Data could also be paired-end reads, and there would be two files per sample.We have single-end reads so one file per sample.Our RNA-seq reads are from 6 samples in FASTQ format.
Perform statistical analysis to obtain a list of differentially expressed genesĪ typical experiment will have 2 conditions each with 3 replicates, for a total of 6 samples.Align RNA-Seq data to a reference genome.Learning ObjectivesĪt the end of this tutorial you should be able to: Usually multiple biological replicates are done for each condition - these are needed to separate variation within the condition from that between the conditions. For example, the conditions could be wildtype versus mutant, or two growth conditions. Backgroundĭifferential Gene Expression (DGE) is the process of determining whether any genes were expressed at a different level between two conditions. This tutorial is about differential gene expression in bacteria, using Galaxy tools and Degust (web). Keywords: differential gene expression, DGE, RNA, RNA-Seq, transcriptomics, Degust, voom, limma, Galaxy, Microbial Genomics Virtual Laboratory. Pangenomes with Roary/Phandango - command lineĭifferential gene expression using Galaxy and DegustĮxpression - Parallel Coordinates and heatmapĭifferential gene expression using Kallisto and Degust
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