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Computational Identification of Recessive Mutations in Cancers using High Throughput SNP-arrays

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dc.date.accessioned 2010-11-25T12:19:58Z und
dc.date.accessioned 2017-11-06T11:16:50Z
dc.date.available 2010-11-25T12:19:58Z und
dc.date.available 2017-11-06T11:16:50Z
dc.date.issued 2007-01-29
dc.identifier.uri http://hdl.handle.net/10138/21427
dc.publisher Helsingin yliopisto fi
dc.publisher Helsingfors universitet sv
dc.publisher University of Helsinki en
dc.title Computational Identification of Recessive Mutations in Cancers using High Throughput SNP-arrays en
ethesis.department.URI http://data.hulib.helsinki.fi/id/225405e8-3362-4197-a7fd-6e7b79e52d14
ethesis.department Institutionen för datavetenskap sv
ethesis.department Department of Computer Science en
ethesis.department Tietojenkäsittelytieteen laitos fi
ethesis.faculty Matematisk-naturvetenskapliga fakulteten sv
ethesis.faculty Matemaattis-luonnontieteellinen tiedekunta fi
ethesis.faculty Faculty of Science en
ethesis.faculty.URI http://data.hulib.helsinki.fi/id/8d59209f-6614-4edd-9744-1ebdaf1d13ca
ethesis.university.URI http://data.hulib.helsinki.fi/id/50ae46d8-7ba9-4821-877c-c994c78b0d97
ethesis.university Helsingfors universitet sv
ethesis.university University of Helsinki en
ethesis.university Helsingin yliopisto fi
dct.creator Laakso, Marko
dct.issued 2007
dct.language.ISO639-2 eng
dct.abstract This thesis presents a highly sensitive genome wide search method for recessive mutations. The method is suitable for distantly related samples that are divided into phenotype positives and negatives. High throughput genotype arrays are used to identify and compare homozygous regions between the cohorts. The method is demonstrated by comparing colorectal cancer patients against unaffected references. The objective is to find homozygous regions and alleles that are more common in cancer patients. We have designed and implemented software tools to automate the data analysis from genotypes to lists of candidate genes and to their properties. The programs have been designed in respect to a pipeline architecture that allows their integration to other programs such as biological databases and copy number analysis tools. The integration of the tools is crucial as the genome wide analysis of the cohort differences produces many candidate regions not related to the studied phenotype. CohortComparator is a genotype comparison tool that detects homozygous regions and compares their loci and allele constitutions between two sets of samples. The data is visualised in chromosome specific graphs illustrating the homozygous regions and alleles of each sample. The genomic regions that may harbour recessive mutations are emphasised with different colours and a scoring scheme is given for these regions. The detection of homozygous regions, cohort comparisons and result annotations are all subjected to presumptions many of which have been parameterized in our programs. The effect of these parameters and the suitable scope of the methods have been evaluated. Samples with different resolutions can be balanced with the genotype estimates of their haplotypes and they can be used within the same study. en
dct.language en
ethesis.language.URI http://data.hulib.helsinki.fi/id/languages/eng
ethesis.language English en
ethesis.language englanti fi
ethesis.language engelska sv
ethesis.supervisor Rousu, Juho
ethesis.supervisor Hautaniemi, Sampsa
ethesis.thesistype pro gradu-avhandlingar sv
ethesis.thesistype pro gradu -tutkielmat fi
ethesis.thesistype master's thesis en
ethesis.thesistype.URI http://data.hulib.helsinki.fi/id/thesistypes/mastersthesis
dct.identifier.urn URN:NBN:fi-fe20071065
dc.type.dcmitype Text
dct.rights This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited. en
dct.rights Publikationen är skyddad av upphovsrätten. Den får läsas och skrivas ut för personligt bruk. Användning i kommersiellt syfte är förbjuden. sv
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