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TACO produces robust multisample transcriptome assemblies from RNA-seq.

ABSTRACT: Accurate transcript structure and abundance inference from RNA sequencing (RNA-seq) data is foundational for molecular discovery. Here we present TACO, a computational method to reconstruct a consensus transcriptome from multiple RNA-seq data sets. TACO employs novel change-point detection to demarcate transcript start and end sites, leading to improved reconstruction accuracy compared with other tools in its class. The tool is available at http://tacorna.github.io and can be readily incorporated into RNA-seq analysis workflows.

SUBMITTER: Niknafs YS

PROVIDER: S-EPMC5199618 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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TACO produces robust multisample transcriptome assemblies from RNA-seq.

Niknafs Yashar S YS Pandian Balaji B Iyer Hariharan K HK Chinnaiyan Arul M AM Iyer Matthew K MK

Nature methods 20161121 1

Accurate transcript structure and abundance inference from RNA sequencing (RNA-seq) data is foundational for molecular discovery. Here we present TACO, a computational method to reconstruct a consensus transcriptome from multiple RNA-seq data sets. TACO employs novel change-point detection to demarcate transcript start and end sites, leading to improved reconstruction accuracy compared with other tools in its class. The tool is available at http://tacorna.github.io and can be readily incorporate ...[more]

PMID: 27869815

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