Unknown

Dataset Information

0

Comprehensive comparative analysis of strand-specific RNA sequencing methods.


ABSTRACT: Strand-specific, massively parallel cDNA sequencing (RNA-seq) is a powerful tool for transcript discovery, genome annotation and expression profiling. There are multiple published methods for strand-specific RNA-seq, but no consensus exists as to how to choose between them. Here we developed a comprehensive computational pipeline to compare library quality metrics from any RNA-seq method. Using the well-annotated Saccharomyces cerevisiae transcriptome as a benchmark, we compared seven library-construction protocols, including both published and our own methods. We found marked differences in strand specificity, library complexity, evenness and continuity of coverage, agreement with known annotations and accuracy for expression profiling. Weighing each method's performance and ease, we identified the dUTP second-strand marking and the Illumina RNA ligation methods as the leading protocols, with the former benefitting from the current availability of paired-end sequencing. Our analysis provides a comprehensive benchmark, and our computational pipeline is applicable for assessment of future protocols in other organisms.

SUBMITTER: Levin JZ 

PROVIDER: S-EPMC3005310 | biostudies-literature | 2010 Sep

REPOSITORIES: biostudies-literature

altmetric image

Publications

Comprehensive comparative analysis of strand-specific RNA sequencing methods.

Levin Joshua Z JZ   Yassour Moran M   Adiconis Xian X   Nusbaum Chad C   Thompson Dawn Anne DA   Friedman Nir N   Gnirke Andreas A   Regev Aviv A  

Nature methods 20100815 9


Strand-specific, massively parallel cDNA sequencing (RNA-seq) is a powerful tool for transcript discovery, genome annotation and expression profiling. There are multiple published methods for strand-specific RNA-seq, but no consensus exists as to how to choose between them. Here we developed a comprehensive computational pipeline to compare library quality metrics from any RNA-seq method. Using the well-annotated Saccharomyces cerevisiae transcriptome as a benchmark, we compared seven library-co  ...[more]

Similar Datasets

2010-08-15 | E-GEOD-21739 | biostudies-arrayexpress
2010-08-15 | GSE21739 | GEO
| S-EPMC6075671 | biostudies-literature
2018-03-21 | GSE103486 | GEO
2013-05-15 | E-GEOD-40705 | biostudies-arrayexpress
2013-05-15 | GSE40705 | GEO
| S-EPMC4148352 | biostudies-literature
| S-EPMC4247151 | biostudies-literature
| S-EPMC8527493 | biostudies-literature
| S-EPMC3821180 | biostudies-literature