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COMPARING BWA AND BOWTIE 2 ALIGNERS IN RNA-SEQ DIFFERENTIAL EXPRESSION ANALYSES

Geniviva, Morgan (2023) COMPARING BWA AND BOWTIE 2 ALIGNERS IN RNA-SEQ DIFFERENTIAL EXPRESSION ANALYSES. Master's Thesis, University of Pittsburgh. (Unpublished)

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Abstract

RNA-seq is becoming an increasingly popular technique for better understanding complex disease. Because this technique is relatively new, there is no “gold standard” for which algorithms to use for each of the steps of the pipeline. The goal for this project is to compare the Burrows–Wheeler Aligner (BWA) and the Bowtie 2 aligner to determine which one performs better in aligning RNA-seq reads to the reference transcriptome. I performed two RNA-seq pipelines identical in all aspects except for the aligner used for the alignment step. Using publicly available raw RNA sequencing data from NCBI’s GEO, I then performed a differential gene expression analysis and a weighted correlation network analysis to compare how the output from the two aligners affect the output of these downstream analyses. The percentage of reads mapped for each aligner were calculated and compared using graphical representation. The output of the differential gene expression analysis included the log2-fold change of expression for each gene between cases and controls and the output for the weighted correlation network analysis was modules that define highly correlated genes. Overall, the two aligners had similar success in aligning reads to the reference transcriptome and created similar outputs in downstream analyses. Therefore, the main conclusion I reached is that researchers can use either the BWA or the Bowtie 2 aligner in their RNA-seq pipeline with a good deal of confidence in their outcomes.

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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Geniviva, MorganMNG13@pitt.eduMNG13
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Thesis AdvisorFan, Kang-Hsienfrank.fan@pitt.edukaf166
Committee MemberMinster, Ryanrminster@pitt.edurminster
Committee MemberRosenthal, Samanthaslr61@pitt.eduslr61
Date: 3 January 2023
Date Type: Publication
Defense Date: 5 December 2022
Approval Date: 3 January 2023
Submission Date: 16 December 2022
Access Restriction: 2 year -- Restrict access to University of Pittsburgh for a period of 2 years.
Number of Pages: 48
Institution: University of Pittsburgh
Schools and Programs: School of Public Health > Human Genetics
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: RNA-Seq, differential expression, alignment tools
Date Deposited: 03 Jan 2023 13:59
Last Modified: 03 Jan 2023 13:59
URI: http://d-scholarship.pitt.edu/id/eprint/44041

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