RCoS

RCoS computes a Rank Consistency Score to identify genes or microRNAs (miRNAs) that exhibit consistent differential expression across matched tumor/normal datasets, enabling detection of biologically relevant expression changes despite inter-patient and tissue-type variability.

Key Features:

• Data Analysis Approach: Uses matched tumor/normal samples from the same individuals to minimize confounding effects of tissue type and patient-related variability.
• Rank Consistency Score (RCoS): Computes a score per miRNA derived from a characterization of the distribution of order statistics over a discrete state set, providing exact p-values for assessing differential expression.
• Comparative Analysis: Includes direct comparisons with paired t-tests and the Wilcoxon Signed Rank test to evaluate robustness in identifying differential expression across matched samples.
• Applicability: Applicable to identification of consistent differential expression for genes or miRNAs across multiple tumor types and other contexts with high inter-sample variability.

Scientific Applications:

• Cancer Research: Applied to profile over 700 miRNAs across 28 matched tumor/normal samples from eight tumor types (breast, colon, liver, lung, lymphoma, ovary, prostate, and testis) to identify miRNAs consistently under- or over-expressed in cancer.
• Identification of OncomiRs: Used to identify known and candidate oncomiRs, including miR-96, and miRNAs reported as consistently downregulated (miR-133b, miR-486-5p) or upregulated (miR-629*) across cancer types.

Methodology:

Computes the Rank Consistency Score by exact characterization of the distribution of order statistics over a discrete state set to obtain exact p-values, and compares results with paired t-test and Wilcoxon Signed Rank test using matched tumor/normal samples.