Preprocess and data analysis techniques for affymetrix DNA microarrays using bioconductor: a case study in Alzheimer disease


Autoria(s): Poncelas, Alberto
Contribuinte(s)

Inza Cano, Iñaki

Ciencia de la Computación e Inteligencia Artificial/Konputazio Zientzia eta Adimen Artifiziala

Data(s)

12/08/2013

12/08/2013

12/08/2013

Resumo

DNA microarray, or DNA chip, is a technology that allows us to obtain the expression level of many genes in a single experiment. The fact that numerical expression values can be easily obtained gives us the possibility to use multiple statistical techniques of data analysis. In this project microarray data is obtained from Gene Expression Omnibus, the repository of National Center for Biotechnology Information (NCBI). Then, the noise is removed and data is normalized, also we use hypothesis tests to find the most relevant genes that may be involved in a disease and use machine learning methods like KNN, Random Forest or Kmeans. For performing the analysis we use Bioconductor, packages in R for the analysis of biological data, and we conduct a case study in Alzheimer disease. The complete code can be found in https://github.com/alberto-poncelas/ bioc-alzheimer

Identificador

http://hdl.handle.net/10810/10478

Idioma(s)

eng

Relação

2013;2

Direitos

info:eu-repo/semantics/openAccess

Palavras-Chave #DNA microarray #bioconductor #data analysis #Alzheimer disease
Tipo

info:eu-repo/semantics/masterThesis