RNA-Seq Blog Transcriptome Research & Industry News
- 1 Experimental design
- 2 Investigating and preprocessing raw RNA-seq data
- 2.1 Galaxy
- 2.2 Store your data
- 2.3 Check the quality of the data and process it
- 2.4 The steps to perform
- 2.4.1 Get your data in a Galaxy history
- 2.4.2 Run Groomer on your data to check the format of the fastq files
- 2.4.3 Run FastQC on your data and examine the results
- 2.4.4 Fastq Quality trimmer to remove low quality regions
- 2.4.5 Fastqmcf to remove adaptors
- 2.4.6 Get sequences of possible contaminating sources
- 2.4.7 Filter out reads that match to contaminating sequences
- 2.4.8 Summarize the matched contaminating sequences
- 2.4.9 Subtract the sequences matching to contaminant databases with ‘Filter sequences by ID’
- 2.4.10 Run FastQC on the cleaned reads
- 2.4.11 Create a workflow of all preprocessing steps
- 2.4.12 Gather the cleaned reads in one history
- 2.5 Questions
- 3 Mapping processed data
- 4 Extracting counts and investigating experimental factors
- 5 Detecting differential expression from a count table
- 6 Exploring the biology behind observed changes
Tagged with: BITS bioinformatics Wiki BITS Wiki differential expression
