NURD

NURD estimates isoform expression levels from RNA-Seq data by correcting global and local sequencing biases using nonparametric models.

Key Features:

• Bias Correction: Adjusts for both global and gene-specific (local) sequencing biases in RNA-Seq data to improve isoform expression estimates.
• Nonparametric Models: Implements nonparametric models (as proposed by Wu et al.) to accommodate diverse read distributions without parametric distributional assumptions.
• Binary Interval Search Algorithm: Uses a binary interval search algorithm to reduce memory usage and processing time during computation.
• Scalability: Optimized for speed and resource utilization to process large-scale RNA-Seq datasets.

Scientific Applications:

• Transcriptomics: Provides isoform-level expression estimates for transcriptome studies.
• Alternative Splicing Analysis: Supports investigation of alternative splicing events by resolving isoform-level expression.
• Gene Regulation Studies: Enables analysis of gene regulation mechanisms through refined isoform expression measurements.
• Differential Expression Analysis: Facilitates differential expression analyses across conditions or tissues at the isoform level.

Methodology:

NURD takes reads mapping results and a gene annotation file as input, corrects global and local sequencing biases using nonparametric models, applies a binary interval search algorithm for computational efficiency, and outputs refined isoform expression estimates.