PATOPA

PATOPA (Probabilistic Approach for estimating the Temporal Order of Pathway mutations by leveraging functional Annotations of mutations) is a computational tool that infers the temporal order of mutations at the pathway level during cancer progression. Key features of PATOPA include:

1. It accounts for the functional impact of each mutation, giving more weight to mutations that are integral to tumor development.

2. PATOPA uses a probabilistic method to characterize the likelihood of mutational events occurring in a specific order from different pathways.

3. A maximum likelihood method is employed to estimate parameters and infer the probability of one pathway being mutated before another.

4. By focusing on the pathway level rather than individual genes, PATOPA has increased power to detect the temporal order of mutations, as mutation rates in most genes are low.

5. Simulation studies and analysis of whole exome sequencing data from The Cancer Genome Atlas (TCGA) have shown that PATOPA accurately estimates the temporal order of pathway mutations and provides new biological insights into the carcinogenesis of colorectal and lung cancers.