Informatics for RNA Sequencing: A Web Resource for Analysis on the Cloud
Fig 5
An example RNA-seq analysis workflow is depicted for a typical gene expression and differential expression analysis. Such workflows have several common themes across different tool sets and RNA-seq analysis goals. RNA-seq analysis typically relies on inputs such as reference genome sequences, gene annotations, and raw sequence data. Working with these inputs requires familiarity with several standardized file formats such as FASTA (.fa), FASTQ, and gene transfer format (GTF). Typical RNA-seq analysis workflows start with raw data quality control (QC), then perform read trimming, alignment or assembly of reads, apply customized algorithms for a particular analysis goal (e.g., Cufflinks and Cuffdiff for gene expression analysis), and end with summarization and visualization of the results. For each step, alternative and representative tools and strategies are shown. There are many others. Each of the workflow steps depicted here and additional analysis vignettes are implemented in the Supplementary Tutorials accompanying this work and available online at www.rnaseq.wiki. Refer to S1–S3 Tables and S7 Table for more details on many of the concepts depicted in this figure as well as alternative tools for each step.