TY  - JOUR
AU  - Davidson, NM
AU  - Oshlack, A
Y2  - 2020/12/17
Y1  - 2014/01/01
SN  - 1474-760X
UR  - http://hdl.handle.net/11343/254717
AB  - Next generation sequencing has made it possible to perform differential gene expression studies in non-model organisms. For these studies, the need for a reference genome is circumvented by performing de novo assembly on the RNA-seq data. However, transcriptome assembly produces a multitude of contigs, which must be clustered into genes prior to differential gene expression detection. Here we present Corset, a method that hierarchically clusters contigs using shared reads and expression, then summarizes read counts to clusters, ready for statistical testing. Using a range of metrics, we demonstrate that Corset out-performs alternative methods. Corset is available from https://code.google.com/p/corset-project/.
LA  - English
PB  - BMC
T1  - Corset: enabling differential gene expression analysis for de novo assembled transcriptomes
DO  - 10.1186/s13059-014-0410-6
IS  - Genome Biology
VL  - 15
IS  - 7
L1  - /bitstream/handle/11343/254717/PMC4165373.pdf?sequence=1&isAllowed=y
ER  -