Introduction

Recent advances in high-throughput sequencing (HTS) have made it possible to monitor genomes in great detail. New experiments not only use HTS to measure genomic features at one time point but also monitor them changing over time with the aim of identifying significant changes in their abundance. In population genetics, for example, allele frequencies are monitored over time to detect significant frequency changes that indicate selection pressures. Previous attempts at analyzing data from HTS experiments have been limited as they could not simultaneously include data at intermediate time points, replicate experiments and sources of uncertainty specific to HTS such as sequencing depth.We present the beta-binomial Gaussian process model for ranking features with significant non-random variation in abundance over time. The features are assumed to represent proportions, such as proportion of an alternative allele in a population. We use the beta-binomial model to capture the uncertainty arising from finite sequencing depth and combine it with a Gaussian process model over the time series. In simulations that mimic the features of experimental evolution data, the proposed method clearly outperforms classical testing in average precision of finding selected alleles. We also present simulations exploring different experimental design choices and results on real data from Drosophila experimental evolution experiment in temperature adaptation.R software implementing the test is available at https://github.com/handetopa/BBGP.

Publications

  1. Gaussian process test for high-throughput sequencing time series: application to experimental evolution.
    Cite this
    Topa H, Jónás Á, Kofler R, Kosiol C, Honkela A, 2015-06-01 - Bioinformatics (Oxford, England)

Credits

  1. Hande Topa
    Developer

    Helsinki Institute for Information Technology (HIIT), Department of Information and Computer Science, Finland

  2. Ágnes Jónás
    Developer

    Helsinki Institute for Information Technology (HIIT), Department of Information and Computer Science, Finland

  3. Robert Kofler
    Developer

    Helsinki Institute for Information Technology (HIIT), Department of Information and Computer Science, Finland

  4. Carolin Kosiol
    Developer

    Helsinki Institute for Information Technology (HIIT), Department of Information and Computer Science, Finland

  5. Antti Honkela
    Investigator

    Helsinki Institute for Information Technology (HIIT), Department of Information and Computer Science, Finland

Community Ratings

UsabilityEfficiencyReliabilityRated By
0 user
Sign in to rate
Summary
AccessionBT001798
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Country/RegionFinland
Submitted ByAntti Honkela