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A multi-sample approach increases the accuracy of transcript assembly.


ABSTRACT: Transcript assembly from RNA-seq reads is a critical step in gene expression and subsequent functional analyses. Here we present PsiCLASS, an accurate and efficient transcript assembler based on an approach that simultaneously analyzes multiple RNA-seq samples. PsiCLASS combines mixture statistical models for exonic feature selection across multiple samples with splice graph based dynamic programming algorithms and a weighted voting scheme for transcript selection. PsiCLASS achieves significantly better sensitivity-precision tradeoff, and renders precision up to 2-3 fold higher than the StringTie system and Scallop plus TACO, the two best current approaches. PsiCLASS is efficient and scalable, assembling 667 GEUVADIS samples in 9?h, and has robust accuracy with large numbers of samples.

SUBMITTER: Song L 

PROVIDER: S-EPMC6825223 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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A multi-sample approach increases the accuracy of transcript assembly.

Song Li L   Sabunciyan Sarven S   Yang Guangyu G   Florea Liliana L  

Nature communications 20191101 1


Transcript assembly from RNA-seq reads is a critical step in gene expression and subsequent functional analyses. Here we present PsiCLASS, an accurate and efficient transcript assembler based on an approach that simultaneously analyzes multiple RNA-seq samples. PsiCLASS combines mixture statistical models for exonic feature selection across multiple samples with splice graph based dynamic programming algorithms and a weighted voting scheme for transcript selection. PsiCLASS achieves significantl  ...[more]

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