More Accurate Transcript Assembly via Parameter Advising.

ABSTRACT: Computational tools used for genomic analyses are becoming more accurate but also increasingly sophisticated and complex. This introduces a new problem in that these pieces of software have a large number of tunable parameters that often have a large influence on the results that are reported. We quantify the impact of parameter choice on transcript assembly and take some first steps toward generating a truly automated genomic analysis pipeline by developing a method for automatically choosing input-specific parameter values for reference-based transcript assembly using the Scallop tool. By choosing parameter values for each input, the area under the receiver operator characteristic curve (AUC) when comparing assembled transcripts to a reference transcriptome is increased by an average

SUBMITTER: Deblasio D 

PROVIDER: S-EPMC7415876 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature