Author ORCID Identifier

0000-0002-9542-5292

Date of Award

5-4-2021

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Science

First Advisor

Pavel Skums

Abstract

Reproducibility and robustness of genomic tools are two important factors to assess the reliability of bioinformatics analysis. Such assessment based on these criteria requires repetition of experiments across lab facilities which is usually costly and time consuming. In this study we propose methods that are able to generate computational replicates, allowing the assessment of the reproducibility of genomic tools. We analyzed three different groups of genomic tools: DNA-seq read alignment tools, structural variant (SV) detection tools and RNA-seq gene expression quantification tools. We tested these tools with different technical replicate data. We observed that while some tools were impacted by the technical replicate data some remained robust. We observed the importance of the choice of read alignment tools for SV detection as well. On the other hand, we found out that the RNA-seq quantification tools (Kallisto and Salmon) that we chose were not affected by the shuffled data but were affected by reverse complement data. Using these findings, our proposed method here may help biomedical communities to advice on the robustness and reproducibility factors of genomic tools and help them to choose the most appropriate tools in terms of their needs. Furthermore, this study will give an insight to genomic tool developers about the importance of a good balance between technical improvements and reliable results.

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