Enhancing RNA-seq analysis by addressing all co-existing biases using a self-benchmarking approach with 2D structural insights.

ABSTRACT: We introduce a groundbreaking approach: the minimum free energy-based Gaussian Self-Benchmarking (MFE-GSB) framework, designed to combat the myriad of biases inherent in RNA-seq data. Central to our methodology is the MFE concept, facilitating the adoption of a Gaussian distribution model tailored to effectively mitigate all co-existing biases within a k-mer counting scheme. The MFE-GSB framework operates on a sophisticated dual-model system, juxtaposing modeling data of uniform k-mer distribution against the real, observed sequencing data characterized by nonuniform k-mer distributions. The framework applies a Gaussian function, guided by the predetermined parameters-mean and SD-derived from modeling data, to fit unknown sequencing data. This dual comparison allows for the accurate predic

SUBMITTER: Su Q 

PROVIDER: S-EPMC11491153 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature