Abstract

The Biostatistics Core will: 1) Provide advice on research design and statistical and genetic analyses, including sample size and power calculations. 2) Conduct statistical analyses of population and family data, including data transformations and adjustments. 3) Conduct genetic analyses of population and family data, including: a) two-point and multi-point linkage analyses of quantitative traits and qualitative disease status with genetic markers, and b) family and population based tests of association of disease status and quantitative traits with genetic markers. 4) Aid in the interpretation of the results of analyses to identify the next steps in a research plan. 5) Provide advice on experimental design and computer analyses of data generated by murine crosses. 6) Provide Bioinformatics support in the use of genome databases to aid in the construction of EST contigs and the identification of the coding regions on long rage sequences in databases.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Program Projects (P01)
Project #
5P01HL028481-17
Application #
6450044
Study Section
Heart, Lung, and Blood Initial Review Group (HLBP)
Project Start
2001-04-01
Project End
2001-12-31
Budget Start
Budget End
Support Year
17
Fiscal Year
2001
Total Cost
$234,837
Indirect Cost

  Institution

Name
University of California Los Angeles
Department
Type
DUNS #
119132785
City
Los Angeles
State
CA
Country
United States
Zip Code
90095

  Publications

Miao, Zong; Alvarez, Marcus; Pajukanta, Päivi et al. (2018) ASElux: an ultra-fast and accurate allelic reads counter. Bioinformatics 34:1313-1320
Kurt, Zeyneb; Barrere-Cain, Rio; LaGuardia, Jonnby et al. (2018) Tissue-specific pathways and networks underlying sexual dimorphism in non-alcoholic fatty liver disease. Biol Sex Differ 9:46
Orozco, Luz D; Farrell, Colin; Hale, Christopher et al. (2018) Epigenome-wide association in adipose tissue from the METSIM cohort. Hum Mol Genet 27:1830-1846
Chella Krishnan, Karthickeyan; Kurt, Zeyneb; Barrere-Cain, Rio et al. (2018) Integration of Multi-omics Data from Mouse Diversity Panel Highlights Mitochondrial Dysfunction in Non-alcoholic Fatty Liver Disease. Cell Syst 6:103-115.e7
Freund, Malika Kumar; Burch, Kathryn S; Shi, Huwenbo et al. (2018) Phenotype-Specific Enrichment of Mendelian Disorder Genes near GWAS Regions across 62 Complex Traits. Am J Hum Genet 103:535-552
Pan, David Z; Garske, Kristina M; Alvarez, Marcus et al. (2018) Integration of human adipocyte chromosomal interactions with adipose gene expression prioritizes obesity-related genes from GWAS. Nat Commun 9:1512
Small, Kerrin S; Todor?evi?, Marijana; Civelek, Mete et al. (2018) Regulatory variants at KLF14 influence type 2 diabetes risk via a female-specific effect on adipocyte size and body composition. Nat Genet 50:572-580
Mangul, Serghei; Yang, Harry Taegyun; Strauli, Nicolas et al. (2018) ROP: dumpster diving in RNA-sequencing to find the source of 1 trillion reads across diverse adult human tissues. Genome Biol 19:36
Cantor, Rita; Navarro, Linda; Pan, Calvin (2018) Identifying fenofibrate responsive CpG sites. BMC Proc 12:43
Rahmani, Elior; Schweiger, Regev; Shenhav, Liat et al. (2018) BayesCCE: a Bayesian framework for estimating cell-type composition from DNA methylation without the need for methylation reference. Genome Biol 19:141

Showing the most recent 10 out of 518 publications