May 26, 2014

Alternative splicing detection workflow needs a careful combination of sample prep and bioinformatics analysis

BioRxiv : the Preprint Server for Biology
Matteo CarraraFrancesca Zolezzi


Background RNAseq provides remarkable power in the area of biomarkers discovery and disease stratification. The main technical steps affecting the results of RNAseq experiments are Library Sample Preparation (LSP) and Bioinformatics Analysis (BA). At the best of our knowledge, a comparative evaluation of the combined effect of LSP and BA was never considered and it might represent a valuable knowledge to optimize alternative splicing detection, which is a challenging task due to moderate fold change differences to be detected within a complex isoforms background. Results Different LSPs (TruSeq unstranded/stranded, ScriptSeq, NuGEN) allow the detection of a large common set of isoforms. However, each LSP also detects a smaller set of isoforms, which are characterized both by lower coverage and lower FPKM than that observed for the common ones among LSPs. This characteristic is particularly critical in case of low input RNA NuGEN v2 LSP. The effect on statistical detection of alternative splicing considering low input LSP (NuGEN v2) with respect to high input LSP (TruSeq) on statistical detection of alternative splicing was studied using a benchmark dataset, in which both synthetic reads and reads generated from high (TruSeq) a...Continue Reading

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Mentioned in this Paper

Biological Markers
Sequence Determinations, RNA
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NBS1 protein, human
Poly(N-acryloyl-L-phenylalanyl-L-phenylalanine methyl ester)

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