Cancer GAMAdb: database of cancer genetic associations from meta-analyses and genome-wide association studies

被引:0
|
作者
Sheri D Schully
Wei Yu
Victoria McCallum
Camilla B Benedicto
Linda M Dong
Anja Wulf
Melinda Clyne
Muin J Khoury
机构
[1] National Cancer Institute,Division of Cancer Control and Population Sciences
[2] Office of Public Health Genomics,Division of Cancer Epidemiology and Genetics
[3] Centers for Disease Control and Prevention,undefined
[4] Office of Workforce Development,undefined
[5] National Cancer Institute,undefined
[6] National Cancer Institute,undefined
来源
关键词
cancer; meta-analyses; pooled analyses; GWAS;
D O I
暂无
中图分类号
学科分类号
摘要
In the field of cancer, genetic association studies are among the most active and well-funded research areas, and have produced hundreds of genetic associations, especially in the genome-wide association studies (GWAS) era. Knowledge synthesis of these discoveries is the first critical step in translating the rapidly emerging data from cancer genetic association research into potential applications for clinical practice. To facilitate the effort of translational research on cancer genetics, we have developed a continually updated database named Cancer Genome-wide Association and Meta Analyses database that contains key descriptive characteristics of each genetic association extracted from published GWAS and meta-analyses relevant to cancer risk. Here we describe the design and development of this tool with the aim of aiding the cancer research community to quickly obtain the current updated status in cancer genetic association studies.
引用
收藏
页码:928 / 930
页数:2
相关论文
共 50 条
  • [1] Cancer GAMAdb: database of cancer genetic associations from meta-analyses and genome-wide association studies
    Schully, Sheri D.
    Yu, Wei
    McCallum, Victoria
    Benedicto, Camilla B.
    Dong, Linda M.
    Wulf, Anja
    Clyne, Melinda
    Khoury, Muin J.
    EUROPEAN JOURNAL OF HUMAN GENETICS, 2011, 19 (08) : 928 - 930
  • [2] Genetic polymorphisms and lung cancer risk: Evidence from meta-analyses and genome-wide association studies
    Liu, Caiyang
    Cui, Huijie
    Gu, Dongqing
    Zhang, Min
    Fang, Yanfei
    Chen, Siyu
    Tang, Mingshuang
    Zhang, Ben
    Chen, Huanwen
    LUNG CANCER, 2017, 113 : 18 - 29
  • [3] Genetic polymorphisms and breast cancer risk: evidence from meta-analyses, pooled analyses, and genome-wide association studies
    Peng, Sihua
    Lue, Bingjian
    Ruan, Wenjing
    Zhu, Yimin
    Sheng, Hongqiang
    Lai, Maode
    BREAST CANCER RESEARCH AND TREATMENT, 2011, 127 (02) : 309 - 324
  • [4] Genetic polymorphisms and breast cancer risk: evidence from meta-analyses, pooled analyses, and genome-wide association studies
    Sihua Peng
    Bingjian Lü
    Wenjing Ruan
    Yimin Zhu
    Hongqiang Sheng
    Maode Lai
    Breast Cancer Research and Treatment, 2011, 127
  • [5] Interpreting Meta-Analyses of Genome-Wide Association Studies
    Han, Buhm
    Eskin, Eleazar
    PLOS GENETICS, 2012, 8 (03):
  • [6] Meta-Analyses of Genome-Wide Association Studies for Postpartum Depression
    Guintivano, Jerry
    Byrne, Enda M.
    Kiewa, Jacqueline
    Yao, Shuyang
    Bauer, Anna E.
    Aberg, Karolina A.
    Adams, Mark J.
    Campbell, Archie
    Campbell, Megan L.
    Choi, Karmel W.
    Corfield, Elizabeth C.
    Havdahl, Alexandra
    Hucks, Donald
    Koen, Nastassja
    Lu, Yi
    Maegbaek, Merete L.
    Mullaer, Jimmy
    Peterson, Roseann E.
    Raffield, Laura M.
    Sallis, Hannah M.
    Sealock, Julia M.
    Walker, Alicia
    Watson, Hunna J.
    Xiong, Ying
    Yang, Jessica M. K.
    Anney, Richard J. L.
    Gordon-Smith, Katherine
    Hubbard, Leon
    Jones, Lisa A.
    Mihaescu, Raluca
    Nyegaard, Mette
    Pardinas, Antonio F.
    Perry, Amy
    Saquib, Nazmus
    Shadyab, Aladdin H.
    Viktorin, Alexander
    Andreassen, Ole A.
    Bigdeli, Tim B.
    Davis, Lea K.
    Dennis, Cindy-Lee
    Di Florio, Arianna
    Dubertret, Caroline
    Feng, Yen-Chen A.
    Frey, Benicio N.
    Grigoriadis, Sophie
    Gloaguen, Emilie
    Jones, Ian
    Kennedy, James L.
    Krohn, Holly
    Kallak, Theodora Kunovac
    AMERICAN JOURNAL OF PSYCHIATRY, 2023, 180 (12): : 884 - 895
  • [7] On Genome-wide Association Studies and their Meta-analyses - Lessons Learned from Osteoporosis Studies
    Liu, Yongjun
    Zhang, Lei
    Pei, Yufang
    Papasian, Christopher
    Deng, Hong-Wen
    JOURNAL OF BONE AND MINERAL RESEARCH, 2013, 28
  • [8] On Genome-Wide Association Studies and Their Meta-Analyses: Lessons Learned From Osteoporosis Studies
    Liu, Yong-Jun
    Zhang, Lei
    Pei, Yufang
    Papasian, Christopher J.
    Deng, Hong-Wen
    JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM, 2013, 98 (07): : E1278 - E1282
  • [9] Genome-Wide Association Studies and Meta-Analyses for Congenital Heart Defects
    Agopian, A. J.
    Goldmuntz, Elizabeth
    Hakonarson, Hakon
    Sewda, Anshuman
    Taylor, Deanne
    Mitchell, Laura E.
    CIRCULATION-CARDIOVASCULAR GENETICS, 2017, 10 (03)
  • [10] Heterogeneity in Meta-Analyses of Genome-Wide Association Investigations
    Ioannidis, John P. A.
    Patsopoulos, Nikolaos A.
    Evangelou, Evangelos
    PLOS ONE, 2007, 2 (09):