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Statistical analysis and modelling of gene count data in metagenomics


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Title: Statistical analysis and modelling of gene count data in metagenomics
Authors: Viktor, Jonsson
E-mail: v.a.jonsson@gmail.com
Issue Date: 26-Jan-2017
University: University of Gothenburg. Faculty of Science
Institution: Department of Mathematical Sciences ; Institutionen för matematiska vetenskaper
Parts of work: I. Jonsson, V., Österlund, T., Nerman, O., Kristiansson, E. (2016). Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomics. BMC genomics, 17(1), 1.
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II. Jonsson, V., Österlund, T., Nerman, O., Kristiansson, E. (2016). Variability in metagenomic count data and its influence on the identification of differentially abundant genes. Journal of Computational Biology, ahead of print.
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III. Jonsson, V., Österlund, T., Nerman, O., Kristiansson, E. (2017). A zero-inflated model for improved inference of metagenomic gene count data. Manuscript.

IV. Österlund, T., Jonsson, V., Kristiansson, E. (2017). HirBin: High-resolution identification of differentially abundant functions in metagenomes. Submitted.
Date of Defence: 2017-02-17
Disputation: Fredagen den 17 februari 2017, kl. 10.00, Pascal, Matematiska Vetenskaper, Chalmers tvärgata 3
Degree: Doctor of Philosophy
Publication type: Doctoral thesis
Keywords: metagenomics
statistical modelling
hierarchical statistical models
gene ranking
overdispersion
zero-inflation
false discovery rate
receiver operating characteristic curves
Abstract: Microorganisms form complex communities that play an integral part of all ecosystems on Earth. Metagenomics enables the study of microbial communities through sequencing of random DNA fragments from the collective genome of all present organisms. Metagenomic data is discrete, high-dimensional and contains excessive levels of both biological and technical variability, which makes the statistical analysis challenging. This thesis aims to improve the statistical analysis of metagenomic data in t... more
ISBN: 978-91-629-0089-2 (PRINT)
978-91-629-0090-8 (PDF)
URI: http://hdl.handle.net/2077/48788
Appears in Collections:Doctoral Theses from University of Gothenburg / Doktorsavhandlingar från Göteborgs universitet
Doctoral Theses / Doktorsavhandlingar Institutionen för biologi och miljövetenskap

 

 

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