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BBGP

swMATH ID: 34286
Software Authors: Topa, H., Jónás, Á., Kofler, R., Kosiol, C.,Honkela, A.
Description: Gaussian process test for high-throughput sequencing time series: application to experimental evolution. Results: 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. Availability and implementation: R software implementing the test is available at https://github.com/handetopa/BBGP.
Homepage: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4443671/
Source Code:  https://github.com/handetopa/BBGP
Dependencies: R
Related Software: WinBUGS; Bioconductor; L-BFGS; otrimle; PMTK; Rcpp; PoPoolation2; R
Cited in: 4 Documents

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