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Developing a web based tool for identification of disease modules
University of Skövde, School of Bioscience.
2018 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Complex diseases such as cancer or obesity are thought to be caused by abnormalities in multiple  genes and cannot be derived to one specific location in the genome. It has been shown that  identification of disease associated genes can be made through looking at interaction patterns in a  protein‐protein interaction network, where the disease associated genes are represented in clusters,  or disease modules. There are several algorithms developed to infer these disease modules, but  studies have shown that the reliability of the results increase if multiple algorithms are used and a  consensus module is derived from them. MODifieR is an R package developed to combine the results  of multiple  disease module inferring algorithms and has proven to provide a stable result. To  increase usability of the R package and make it available not only for users with programmatic skills,  MODifieR Web was developed as a web based tool with a graphical user interface. The tool was built  using Angular and .NET core, invoking the MODifieR R package in the backend. The interface requires  input in the form of an expression matrix and a probe map from the user, easily uploadable in a  drag‐and‐drop  interface.  It  gives  the  user  the  possibility  to  analyze  data  using  seven  different  algorithms and provide results as gene lists and visualizes the consensus module in a network image.  MODifieR Web is a first version of an application that is a novel contribution to the existing tools for  identification of disease modules, although in need of further improvements to be able to serve a  greater  pool  of  users  in  a  more  effective  way.  The  tool  is  available  to  try  out  at   http://transbioinfo.liu.se/modifier#/home and the source code is released as an open‐source project  in Github (https://github.com/emmape/MODifieRProject).  

Place, publisher, year, edition, pages
2018. , p. 35
Keywords [en]
Modifier
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:his:diva-16479OAI: oai:DiVA.org:his-16479DiVA, id: diva2:1269144
Subject / course
Bioinformatics
Educational program
Bioinformatics - Master’s Programme
Supervisors
Examiners
Available from: 2018-12-10 Created: 2018-12-09 Last updated: 2018-12-10Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
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  • Other style
More styles
Language
  • de-DE
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  • en-US
  • fi-FI
  • nn-NO
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  • Other locale
More languages
Output format
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