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TACO produces robust multisample transcriptome assemblies from RNA-seq
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DOI：10.1038/NMETH.4078.png)
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Abstract
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O 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.
Keywords:
LONG NONCODING RNAS
REVEALS
RECONSTRUCTION
ANNOTATION
STRINGTIE
LANDSCAPE
CATALOG
GENCODE
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