MtbTnDB

MtbTnDB consolidates approximately 150 standardized transposon sequencing (TnSeq) profiles for Mycobacterium tuberculosis to enable comparative analysis of genome-wide gene essentiality across diverse experimental conditions.

Key Features:

• Consolidated dataset: Aggregates approximately 150 standardized TnSeq screens for Mycobacterium tuberculosis.
• Experimental coverage: Contains screens from in vitro studies, macrophage environments, and model host organisms.
• Genome-wide essentiality profiles: Provides genome-wide essentiality profiles derived from TnSeq data.
• Statistical relationship analysis: Identifies statistical relationships showing that genes in close genomic proximity tend to have similar TnSeq profiles.
• Clustering and functional enrichment: Clusters genes by TnSeq profile similarity and detects enrichment of similar functional categories within clusters.
• Machine learning support: Enables training of machine learning models on TnSeq profiles for prediction of gene function and functional annotation of orphan genes.
• Visualizations and functional predictions: Includes visualizations and functional predictions derived from TnSeq profile analyses.

Scientific Applications:

• Comparative essentiality analysis: Compare genome-wide gene essentiality across diverse experimental conditions.
• Functional annotation prediction: Predict functional annotations for orphan genes using machine learning trained on TnSeq profiles.
• Conditional genetic essentiality: Investigate conditional essentiality of genes under different environmental and host-related conditions.
• Genetic and functional organization studies: Study relationships between genomic proximity, profile similarity, and functional category organization in Mtb.

Methodology:

Consolidation and standardization of approximately 150 TnSeq screens, statistical analysis of TnSeq profile similarity and clustering, and training of machine learning models on TnSeq profiles for functional prediction.