TY  - JOUR
A1  - Bischler, Thorsten
A1  - Kopf, Matthias
A1  - Voss, Bjoern
T1  - Transcript mapping based on dRNA-seq data
JF  - BMC Bioinformatics
N2  - Background: RNA-seq and its variant differential RNA-seq (dRNA-seq) are today routine methods for transcriptome analysis in bacteria. While expression profiling and transcriptional start site prediction are standard tasks today, the problem of identifying transcriptional units in a genome-wide fashion is still not solved for prokaryotic systems. 
Results: We present RNASEG, an algorithm for the prediction of transcriptional units based on dRNA-seq data. A key feature of the algorithm is that, based on the data, it distinguishes between transcribed and un-transcribed genomic segments. Furthermore, the program provides many different predictions in a single run, which can be used to infer the significance of transcriptional units in a consensus procedure. We show the performance of our method based on a well-studied dRNA-seq data set for Helicobacter pylori. 
Conclusions: With our algorithm it is possible to identify operons and 5'- and 3'-UTRs in an automated fashion. This alleviates the need for labour intensive manual inspection and enables large-scale studies in the area of comparative transcriptomics.
KW  - transcriptional start site
KW  - dynamic programming
KW  - RNA-seq
KW  - differential
KW  - segmentation
KW  - transcriptional uni
KW  - transcriptome
KW  - reveals
KW  - model
Y1  - 2014
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-116663
SN  - 1471-2105
VL  - 15
IS  - 122
ER  -