OpenContami

OpenContami detects exogenous microbial species in next-generation sequencing (NGS) datasets to identify and assess microbial contamination that may confound biological and pathological interpretations.

Key Features:

• Microbial Detection Algorithm: Uses a specialized algorithm, described as a refined iteration of previous work, to identify exogenous microbial species within NGS data.
• Comprehensive Database Integration: Integrates analytical results from extensive public datasets with user-uploaded data in a database for comparative evaluation.
• Negative Blank Control 'Blacklist': Maintains a curated list of genera identified from negative blank controls as a blacklist to help distinguish contamination artifacts from true biological signals.
• Impact Assessment: Summarizes exogenous species present in NGS datasets to assess potential influences on biological and pathological traits.

Scientific Applications:

• Microbiology: Identification and mitigation of contaminant microbes in microbiology studies using NGS.
• Genomics: Ensuring data purity in genomics analyses that rely on next-generation sequencing.
• Infectious Disease Research: Distinguishing genuine infectious agents from contaminants in studies of human infectious diseases.

Methodology:

Integrates computational algorithms with extensive public and user-uploaded datasets, comparing user NGS data against the database to identify potential contamination sources and flag exogenous species.