A weighted exact test for mutually exclusive mutations in cancer

Area of Science:

• Computational Biology
• Genomics
• Cancer Research

Background:

• Somatic mutations driving cancer can be mutually exclusive, aiding driver vs. passenger mutation identification.
• High and variable mutation rates across samples can confound exclusivity signals.
• Existing statistical tests for exclusivity are computationally intensive and lack precision.

Purpose of the Study:

• To develop a computationally efficient and precise statistical test for assessing mutual exclusivity of mutations.
• To improve the identification of cancer driver mutations by overcoming limitations of existing methods.

Main Methods:

• Formulated a weighted exact test for arbitrary numbers of mutational events.
• Developed a recursive formula for exact P-value computation and a saddlepoint approximation.
• The Weighted Exclusivity Test (WExT) conditions on mutation counts and per-event, per-sample probabilities.

Main Results:

• The weighted test is more efficient and recovers more significant results than traditional permutation tests.
• Applied WExT to colorectal and endometrial cancer data from The Cancer Genome Atlas.
• Identified sets of mutually exclusive mutations in cancer genes with reduced false positives compared to prior methods.

Conclusions:

• The Weighted Exclusivity Test (WExT) provides a more accurate and efficient approach for analyzing mutation exclusivity in cancer.
• This method is particularly valuable for cancer types with high mutation rates, improving the discovery of driver mutations.