occugene

occugene models transposon insertion occupancy and estimates ORF essentiality in prokaryotic random transposon mutagenesis libraries to support interpretation of ORF knockouts and identification of essential genes.

Key Features:

• Occupancy Distribution Management: Models the occupancy distribution of transposon insertions in a multinomial framework across open reading frames (ORFs).
• Estimation of Essential Genes: Estimates the number and per‑ORF probability of essential ORFs from insertion distribution data.
• Statistical Solutions for Key Issues: Computes basic probability results for ORF knockouts, estimates the number of new ORFs expected to be knocked out in subsequent clone sets, estimates the number of essential ORFs within a library, and calculates the probability that an ORF is essential based on insertion distributions.

Scientific Applications:

• Essential gene identification: Supports identification of essential genes critical for cellular viability under various conditions.
• Genetic network and pathway analysis: Enables exploration of genetic networks and pathways by analyzing the effects of ORF knockouts from transposon libraries.
• Antimicrobial target discovery: Aids in pinpointing potential drug targets by identifying essential genes in microbial genomes.
• Functional genomics and systems biology: Applies to microbial genetics, functional genomics, and systems biology studies that use random transposon mutagenesis data.

Methodology:

Multinomial occupancy-distribution modeling and statistical estimation using Efron and Thisted's estimator, Will and Jacobs's parametric bootstrap (resampling with replacement), and Blades and Broman's Gibbs sampler.