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Data Mining the Genetics of Leukemia

Acute Lymphoblastic Leukemia (ALL) is the most common cancer in children under
the age of 15. At present, diagnosis, prognosis and treatment decisions are made
based upon blood and bone marrow laboratory testing. With advances in microarray
technology it is becoming more feasible to perform genetic assessment of individual
patients as well. We used Singular Value Decomposition (SVD) on Illumina SNP,
Affymetrix and cDNA gene-expression data and performed aggressive attribute se-
lection using random forests to reduce the number of attributes to a manageable
size. We then explored clustering and prediction of patient-specific properties such
as disease sub-classification, and especially clinical outcome. We determined that
integrating multiple types of data can provide more meaningful information than
individual datasets, if combined properly. This method is able to capture the cor-
relation between the attributes. The most striking result is an apparent connection
between genetic background and patient mortality under existing treatment regimes.
We find that we can cluster well using the mortality label of the patients. Also, using
a Support Vector Machine (SVM) we can predict clinical outcome with high accu-racy. This thesis will discuss the data-mining methods used and their application to
biomedical research, as well as our results and how this will affect the diagnosis and
treatment of ALL in the future. / Thesis (Master, Computing) -- Queen's University, 2010-01-12 18:40:44.2

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OKQ.1974/5390
Date13 January 2010
CreatorsMorton, Geoffrey
ContributorsQueen's University (Kingston, Ont.). Theses (Queen's University (Kingston, Ont.))
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish, English
Detected LanguageEnglish
TypeThesis
Format608450 bytes, application/pdf
RightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.
RelationCanadian theses

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