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2015 ; 16
(6
): 932-40
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A comparative study of RNA-seq analysis strategies
#MMPMID25788326
Jänes J
; Hu F
; Lewin A
; Turro E
Brief Bioinform
2015[Nov]; 16
(6
): 932-40
PMID25788326
show ga
Three principal approaches have been proposed for inferring the set of
transcripts expressed in RNA samples using RNA-seq. The simplest approach uses
curated annotations, which assumes the transcripts in a sample are a subset of
the transcripts listed in a curated database. A more ambitious method involves
aligning reads to a reference genome and using the alignments to infer the
transcript structures, possibly with the aid of a curated transcript database.
The most challenging approach is to assemble reads into putative transcripts de
novo without the aid of reference data. We have systematically assessed the
properties of these three approaches through a simulation study. We have found
that the sensitivity of computational transcript set estimation is severely
limited. Computational approaches (both genome-guided and de novo assembly)
produce a large number of artefacts, which are assigned large expression
estimates and absorb a substantial proportion of the signal when performing
expression analysis. The approach using curated annotations shows good expression
correlation even when the annotations are incomplete. Furthermore, any incorrect
transcripts present in a curated set do not absorb much signal, so it is
preferable to have a curation set with high sensitivity than high precision.
Software to simulate transcript sets, expression values and sequence reads under
a wider range of parameter values and to compare sensitivity, precision and
signal-to-noise ratios of different methods is freely available online
(https://github.com/boboppie/RSSS) and can be expanded by interested parties to
include methods other than the exemplars presented in this article.
free
free
free
