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The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers
Cancer epidemiology, biomarkers & prevention, 2017-01, Vol.26 (1), p.126-135
Amos, Christopher I
Dennis, Joe
Wang, Zhaoming
Byun, Jinyoung
Schumacher, Fredrick R
Gayther, Simon A
Casey, Graham
Hunter, David J
Sellers, Thomas A
Gruber, Stephen B
Dunning, Alison M
Michailidou, Kyriaki
Fachal, Laura
Doheny, Kimberly
Spurdle, Amanda B
Li, Yafang
Xiao, Xiangjun
Romm, Jane
Pugh, Elizabeth
Coetzee, Gerhard A
Hazelett, Dennis J
Bojesen, Stig E
Caga-Anan, Charlisse
Haiman, Christopher A
Kamal, Ahsan
Luccarini, Craig
Tessier, Daniel
Vincent, Daniel
Bacot, François
Van Den Berg, David J
Nelson, Stefanie
Demetriades, Stephen
Goldgar, David E
Couch, Fergus J
Forman, Judith L
Giles, Graham G
Conti, David V
Bickeböller, Heike
Risch, Angela
Waldenberger, Melanie
Brüske-Hohlfeld, Irene
Hicks, Belynda D
Ling, Hua
McGuffog, Lesley
Lee, Andrew
Kuchenbaecker, Karoline
Soucy, Penny
Manz, Judith
Cunningham, Julie M
Butterbach, Katja
Kote-Jarai, Zsofia
Kraft, Peter
FitzGerald, Liesel
Lindström, Sara
Adams, Marcia
McKay, James D
Phelan, Catherine M
Benlloch, Sara
Kelemen, Linda E
Brennan, Paul
Riggan, Marjorie
O'Mara, Tracy A
Shen, Hongbing
Shi, Yongyong
Thompson, Deborah J
Goodman, Marc T
Nielsen, Sune F
Berchuck, Andrew
Laboissiere, Sylvie
Schmit, Stephanie L
Shelford, Tameka
Edlund, Christopher K
Taylor, Jack A
Field, John K
Park, Sue K
Offit, Kenneth
Thomassen, Mads
Schmutzler, Rita
Ottini, Laura
Hung, Rayjean J
Marchini, Jonathan
Amin Al Olama, Ali
Peters, Ulrike
Eeles, Rosalind A
Seldin, Michael F
Gillanders, Elizabeth
Seminara, Daniela
Antoniou, Antonis C
Pharoah, Paul D P
Chenevix-Trench, Georgia
Chanock, Stephen J
Simard, Jacques
Easton, Douglas F
2017
Volltextzugriff (PDF)
Details
Autor(en) / Beteiligte
Amos, Christopher I
Dennis, Joe
Wang, Zhaoming
Byun, Jinyoung
Schumacher, Fredrick R
Gayther, Simon A
Casey, Graham
Hunter, David J
Sellers, Thomas A
Gruber, Stephen B
Dunning, Alison M
Michailidou, Kyriaki
Fachal, Laura
Doheny, Kimberly
Spurdle, Amanda B
Li, Yafang
Xiao, Xiangjun
Romm, Jane
Pugh, Elizabeth
Coetzee, Gerhard A
Hazelett, Dennis J
Bojesen, Stig E
Caga-Anan, Charlisse
Haiman, Christopher A
Kamal, Ahsan
Luccarini, Craig
Tessier, Daniel
Vincent, Daniel
Bacot, François
Van Den Berg, David J
Nelson, Stefanie
Demetriades, Stephen
Goldgar, David E
Couch, Fergus J
Forman, Judith L
Giles, Graham G
Conti, David V
Bickeböller, Heike
Risch, Angela
Waldenberger, Melanie
Brüske-Hohlfeld, Irene
Hicks, Belynda D
Ling, Hua
McGuffog, Lesley
Lee, Andrew
Kuchenbaecker, Karoline
Soucy, Penny
Manz, Judith
Cunningham, Julie M
Butterbach, Katja
Kote-Jarai, Zsofia
Kraft, Peter
FitzGerald, Liesel
Lindström, Sara
Adams, Marcia
McKay, James D
Phelan, Catherine M
Benlloch, Sara
Kelemen, Linda E
Brennan, Paul
Riggan, Marjorie
O'Mara, Tracy A
Shen, Hongbing
Shi, Yongyong
Thompson, Deborah J
Goodman, Marc T
Nielsen, Sune F
Berchuck, Andrew
Laboissiere, Sylvie
Schmit, Stephanie L
Shelford, Tameka
Edlund, Christopher K
Taylor, Jack A
Field, John K
Park, Sue K
Offit, Kenneth
Thomassen, Mads
Schmutzler, Rita
Ottini, Laura
Hung, Rayjean J
Marchini, Jonathan
Amin Al Olama, Ali
Peters, Ulrike
Eeles, Rosalind A
Seldin, Michael F
Gillanders, Elizabeth
Seminara, Daniela
Antoniou, Antonis C
Pharoah, Paul D P
Chenevix-Trench, Georgia
Chanock, Stephen J
Simard, Jacques
Easton, Douglas F
Titel
The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers
Ist Teil von
Cancer epidemiology, biomarkers & prevention, 2017-01, Vol.26 (1), p.126-135
Ort / Verlag
United States: American Association for Cancer Research, Inc
Erscheinungsjahr
2017
Quelle
MEDLINE
Beschreibungen/Notizen
Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126-35. ©2016 AACR.
Sprache
Englisch
Identifikatoren
ISSN: 1055-9965
eISSN: 1538-7755
DOI: 10.1158/1055-9965.epi-16-0106
Titel-ID: cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5224974
Format
–
Schlagworte
Bioindicators
,
Cancer
,
Causation
,
Consortia
,
Ecological risk assessment
,
Etiology
,
Female
,
Gene mapping
,
Genetic diversity
,
Genetic Predisposition to Disease - epidemiology
,
Genetic variance
,
Genetic Variation - genetics
,
Genome-Wide Association Study - methods
,
Genomes
,
Genotype
,
Genotyping
,
Health risks
,
Humans
,
Male
,
Neoplasms - epidemiology
,
Neoplasms - genetics
,
Neoplasms - physiopathology
,
Polymorphism, Single Nucleotide - genetics
,
Prevalence
,
Principal components analysis
,
Prognosis
,
Quality control
,
Risk Assessment
,
Selection, Genetic
,
Single-nucleotide polymorphism
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