NDLI: FARMS: A New Algorithm for Variable Selection

Content Provider	PubMed Central
Author	Perez Alvarez, Susana Gómez, Guadalupe Brander, Christian
Copyright Year	2015
Abstract	Large datasets including an extensive number of covariates are generated these days in many different situations, for instance, in detailed genetic studies of outbreed human populations or in complex analyses of immune responses to different infections. Aiming at informing clinical interventions or vaccine design, methods for variable selection identifying those variables with the optimal prediction performance for a specific outcome are crucial. However, testing for all potential subsets of variables is not feasible and alternatives to existing methods are needed. Here, we describe a new method to handle such complex datasets, referred to as FARMS, that combines forward and all subsets regression for model selection. We apply FARMS to a host genetic and immunological dataset of over 800 individuals from Lima (Peru) and Durban (South Africa) who were HIV infected and tested for antiviral immune responses. This dataset includes more than 500 explanatory variables: around 400 variables with information on HIV immune reactivity and around 100 individual genetic characteristics. We have implemented FARMS in R statistical language and we showed that FARMS is fast and outcompetes other comparable commonly used approaches, thus providing a new tool for the thorough analysis of complex datasets without the need for massive computational infrastructure.
Related Links	http://dx.doi.org/10.1155/2015/319797
Starting Page	319797
File Format	PDF
ISSN	23146133
e-ISSN	23146141
Journal	BioMed Research International
Volume Number	2015
Language	English
Publisher	Hindawi Publishing Corporation
Publisher Date	2015-01-01
Access Restriction	Open
Rights Holder	Hindawi Publishing Corporation
Subject Keyword	Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Immunology and Microbiology Medicine Biochemistry, Genetics and Molecular Biology

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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