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Updated: Apr 17, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Phylogenetic profiling: how much input data is enough?

Nives Škunca¹, Christophe Dessimoz²

¹ETH Zürich, Department of Computer Science, Universitätstr. 19, 8092 Zürich, Switzerland; Swiss Institute of Bioinformatics, Universitätstr. 6, 8092 Zürich, Switzerland; University College London, Gower St, London WC1E 6BT, UK.

|February 14, 2015

Summary

This summary is machine-generated.

Phylogenetic profiling for gene function prediction benefits from more data, but adding over ~100 genomes yields diminishing returns. Increasing functional annotations remains highly beneficial for accurate gene function predictions.

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Area of Science:

Computational Biology
Bioinformatics
Genomics

Background:

Phylogenetic profiling predicts gene function using gene presence/absence patterns across species.
Recent research emphasizes methodological improvements, with less focus on input data size effects.

Purpose of the Study:

To determine the optimal number of genomes and functional annotations for effective phylogenetic profiling.
To investigate the impact of data size on prediction accuracy.

Main Methods:

Decomposition analysis of predictive accuracy improvement based on added genomes and annotations.
Evaluation of phylogenetic diversity's effect on prediction quality.

Main Results:

Predictive accuracy generally increases with more data, but diminishing returns are observed beyond ~100 genomes.
Increasing the number of functional annotations consistently improves accuracy.
Maximizing phylogenetic diversity offers minor improvements compared to increasing genome numbers.

Conclusions:

The number of genomes is a critical factor, with a plateau around 100 for phylogenetic profiling effectiveness.
Functional annotation quantity is crucial and remains beneficial with increasing numbers.
Findings align with the Open World Assumption regarding incomplete functional annotation databases.