Högskolan i Skövde

his.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Comparative study of topology based pathway enrichment analysis methods for cardiac hypertrophy from a stem cell model using: ToPASeq and EnrichmentBrowser packages
University of Skövde, School of Bioscience.
2020 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Pathway enrichment analysis is an approach extensively used when analyzing high throughput data to identify pathways enriched within a group of differentially expressed genes. Furthermore, different methods utilizing the topology of the pathway offer a unique way of analyzing and interpreting gene expression data. These methods usually offer pathway topologies with a limited number of methods and visualization of results. Also, the use of different methods individually and comparison of their results can be very cumbersome, time-consuming and prone to errors due to the need for repeated data conversion and transfer. Packages that offer a common interface to multiple methods are therefore necessary, to provide a uniform way of calling these methods or specifying parameters, and making simultaneous application of the methods easier.

In this study topology-based pathway enrichment analysis was performed by using the R packages EnrichmentBrowser and ToPASeq on a time series RNA-Seq data for cardiac hypertrophy in order to compare their usability. Additionally, different topology-based enrichment analysis methods included in the packages were compared with a non-topology-based pathway enrichment analysis method as well as the combination of their results in order to assess biological insights.

Regarding usability, the available instructions for how to use both EnrichmentBrowser and ToPASeq were easy to understand and apply in the R workspace. Furthermore, both packages were easy to install and adjust to various parameters. However, ToPASeq returned errors when some parameters other than the default ones were used. Also, one of the differences between the tools was the flexibility of options for visualization and interpretation of the results, where EnrichmentBrowser had clear advantages. Regarding biological insights, the methods SPIA and DEGraph produced significant pathways linked to the phenotype cardiac hypertrophy, with a clear advantage for SPIA that performed well in both tested data setups. Finally, combining results from both SPIA and GSEA (non-topology-based pathway enrichment analysis method) improved individual ranking by increasing confidence in specific target pathways and eliminating irrelevant pathways.

Place, publisher, year, edition, pages
2020. , p. 62
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:his:diva-19465OAI: oai:DiVA.org:his-19465DiVA, id: diva2:1527558
Subject / course
Bioinformatics
Educational program
Bioinformatics - Master’s Programme
Supervisors
Examiners
Available from: 2021-02-11 Created: 2021-02-11 Last updated: 2021-02-11Bibliographically approved

Open Access in DiVA

fulltext(1804 kB)289 downloads
File information
File name FULLTEXT01.pdfFile size 1804 kBChecksum SHA-512
094ab7f1167a497cf1e5743497dc35d806264387ca25d0d9226ffe5a7f91c9a555c8ac8b8be0ce96f6c9ab1681b33593a1a306962970712ea00b6bc8c7d8a5f7
Type fulltextMimetype application/pdf

By organisation
School of Bioscience
Bioinformatics and Systems Biology

Search outside of DiVA

GoogleGoogle Scholar
Total: 289 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 267 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf