KaMRaT

KaMRaT processes large k-mer count tables derived from multi-sample RNA-seq data to identify condition-specific or differentially expressed sequences without relying on gene or transcript annotation.

Key Features:

• K-mer Scoring: Scores k-mers based on count statistics.
• Contig Assembly: Merges overlapping k-mers into contigs.
• Occurrence-based Selection: Selects k-mers based on their occurrence across specific samples.

Scientific Applications:

• Condition-specific Sequence Identification: Identifies sequences specific to particular conditions in large RNA-seq datasets.
• Differential Expression Analysis: Detects differentially expressed sequences independent of gene or transcript annotation.

Methodology:

KaMRaT is implemented in C++ and operates on k-mer count matrices derived from multi-sample RNA-seq data.