Expression analysis of RNA sequencing data from human neural and glial cell lines depends on technical replication and normalization methods

Table 1 Steps in the RNA-Seq workflow and potential contributions to experimental variance. At each step in an RNA-Seq experiment, different parameters can introduce unwanted variance that obscure the results of gene expression analyses. Detailed discussions of these parameters are given by the sources in the References column

Step in RNA-Seq Workflow	Potential Contributions to Variance	Reference(s)
1. Experimental Design	number of replicate samples; genetic background of samples	[9]
2. RNA Isolation	RNA integrity number (RIN) value (RNA quality); isolation method	[1, 34]
3. Library Preparation	initial quantity of RNA template; RNA processing: polyA⁺ (mRNA enrichment), rRNA⁻ (rRNA depletion); preliminary amplification steps	[1, 34]
4. Sequencing	sequencing platform; depth of coverage; software for base-calls	[42]
5. Preprocessing	trimming adapter sequences and/ or low quality reads	[1]
6. Mapping	quality of reference genome, stringency	[1, 34]
7. Normalization	method	[8, 35, 37]
8. Statistical Analysis	method; stringency	[1, 7]

ISSN: 1471-2105