Abstract

The Biostatistics Core of this project will be led by Professor Richard Olshen, who will be joined in supportive efforts by Professors Bradley Efron and Lu Tian. There will be high level statistical consulting on all projects and all investigators of SHIMR by these investigators. All data made available to these individuals will be anonymized compliant with HIPPA rules. Open source computer programs written in the popular R language www.r-project.org/ will be made available to SHIMR investigators. Stanford's Data Coordinating Center (DCC) is the umbrella organization that will supervise writing these open source computer programs. In most instances the programs will call existing routines, available for downloading from CRAN http://cran.r proiect.org/, though occasionally we will create the ingredient routines ourselves.

Public Health Relevance

We wish to analyze a variety of different disease/vaccine models in order to define common and unique characteristics of responder and non-responder individuals. The Biostatistics Core will work with the investigators on all Research Projects and Cores to provide statistical analyses that should be illuminating both to specific questions regarding these study groups and will also be of benefit generally with respect to

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
5U19AI090019-03
Application #
8377338
Study Section
Special Emphasis Panel (ZAI1-QV-I)
Project Start
Project End
Budget Start
2012-07-01
Budget End
2013-06-30
Support Year
3
Fiscal Year
2012
Total Cost
$87,161
Indirect Cost
$24,838

  Institution

Name
Stanford University
Department
Type
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305

  Publications

Bongen, Erika; Vallania, Francesco; Utz, Paul J et al. (2018) KLRD1-expressing natural killer cells predict influenza susceptibility. Genome Med 10:45
Cheung, Peggie; Vallania, Francesco; Warsinske, Hayley C et al. (2018) Single-Cell Chromatin Modification Profiling Reveals Increased Epigenetic Variations with Aging. Cell 173:1385-1397.e14
Furman, David; Chang, Junlei; Lartigue, Lydia et al. (2017) Expression of specific inflammasome gene modules stratifies older individuals into two extreme clinical and immunological states. Nat Med 23:174-184
HIPC-CHI Signatures Project Team; HIPC-I Consortium (2017) Multicohort analysis reveals baseline transcriptional predictors of influenza vaccination responses. Sci Immunol 2:
O'Gorman, W E; Kong, D S; Balboni, I M et al. (2017) Mass cytometry identifies a distinct monocyte cytokine signature shared by clinically heterogeneous pediatric SLE patients. J Autoimmun :
Blazkova, Jana; Gupta, Sarthak; Liu, Yudong et al. (2017) Multicenter Systems Analysis of Human Blood Reveals Immature Neutrophils in Males and During Pregnancy. J Immunol 198:2479-2488
Nair, Nitya; Feng, Ningguo; Blum, Lisa K et al. (2017) VP4- and VP7-specific antibodies mediate heterotypic immunity to rotavirus in humans. Sci Transl Med 9:
Brodin, Petter; Davis, Mark M (2017) Human immune system variation. Nat Rev Immunol 17:21-29
Haddon, D James; Wand, Hannah E; Jarrell, Justin A et al. (2017) Proteomic Analysis of Sera from Individuals with Diffuse Cutaneous Systemic Sclerosis Reveals a Multianalyte Signature Associated with Clinical Improvement during Imatinib Mesylate Treatment. J Rheumatol 44:631-638
Su, Laura F; Del Alcazar, Daniel; Stelekati, Erietta et al. (2016) Antigen exposure shapes the ratio between antigen-specific Tregs and conventional T cells in human peripheral blood. Proc Natl Acad Sci U S A 113:E6192-E6198

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