What question did this study set out to answer?

To develop a fast and scalable maximum likelihood algorithm for reconstructing bacterial clonal haplotypes and evolutionary dynamics from sparse, noisy time course genomic sequencing data.

January 1, 2024Journal of Bioinformatics and Systems BiologyOpen Access

A Scalable Algorithm for Clonal Reconstruction from Sparse Time Course Genomic Sequencing Data

View Full Paper

Ask AI

Bookmark

Authors

WIWazim Mohammed IsmailMayo Clinic HTHaixu TangIndiana University Bloomington

Discussion

Member takes

Implication

Computational study demonstrates scalable clonal reconstruction in evolving bacterial populations, suggesting improved haplotype inference from sparse genomic time series.

Key Points

To develop a fast and scalable maximum likelihood algorithm for reconstructing bacterial clonal haplotypes and evolutionary dynamics from sparse, noisy time course genomic sequencing data.
Incorporated a statistical variance estimation model for low-coverage variant allele frequencies into a maximum likelihood clonal reconstruction framework.
Formulated scalable computational heuristics to resolve clonal lineages when novel mutations substantially outnumber sampled time points.
Implemented the methodology into ClonalTREE2 and evaluated accuracy and speed on both simulated benchmarks and real experimental genomic datasets.
ClonalTREE2 achieved near-optimal reconstruction accuracy under the maximum likelihood framework on time course data containing hundreds of novel mutations per time point.
Demonstrated computational scalability and efficiency, overcoming the severe runtime bottlenecks of earlier greedy reconstruction algorithms on sparse time series.

Cite This Study

Ismail et al. (2024) studied this question.

synapsesocial.com/papers/6a96450a33d7b00ae7bb6e50 https://doi.org/10.26502/jbsb.5107075

View Full Paper

Ask AI

Bookmark

Implication

Computational study demonstrates scalable clonal reconstruction in evolving bacterial populations, suggesting improved haplotype inference from sparse genomic time series.

A Scalable Algorithm for Clonal Reconstruction from Sparse Time Course Genomic Sequencing Data

Discussion

Member takes

Implication

Key Points

Cite This Study

A Scalable Algorithm for Clonal Reconstruction from Sparse Time Course Genomic Sequencing Data

Discussion

Member takes

Implication

Key Points

Cite This Study

Also Consider

Also Consider