1. Background
  2. Data Collection Methods
  3. Data Quality Control
  4. Summary

Adapted from Martin and Wang (2011). bp = base pairs

Quality Control: Sample preparation methods

In general, RNA-Seq data are highly accurate and reproducible for both technical and biological replicates (Wang et al., 2009). Thus given a well-documented protocol, RNA-Seq results should be of high quality. However, choices in some of the sample preparation steps may introduce biases for certain transcripts or transcript regions as summarized below.

  1. mRNA enrichment by polyA selection will miss non-coding RNAs and mRNAs that lack a polyA tail. Quantification of highly abundant transcripts will be biased (Martin and Wang, 2011).
  2. Fragmentation methods (Wang et al., 2009)
    1. RNA fragmentation depletes transcripts ends compared to other methods.
    2. cDNA fragmentation causes a biased identification of sequences from the 3' ends of transcripts.
  3. PCR amplification results in low sequencing coverage for transcript regions that have a high GC content, which can cause gaps in the assembled transcript (Martin and Wang, 2011).