Data Management

Facilitating Genetic Analysis: SAS, the NHLBI and CARe

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Executive Summary

Two common tasks for a SAS programmer are creating summary statistics and distributing data. Often, these are relatively benign tasks requiring only a handful of SAS statements but on the occasions when a large volume of data must be processed, writing too many of these statements by hand becomes inefficient and ultimately error prone. The purpose of this paper is to describe several techniques for summarizing and distributing a large number of SAS data sets and variables. The methods are discussed within the context of the National Heart Lung Blood and Sleep Institute's (NHLBI) Candidate Gene Association Resource (CARe) project which assembled genotype and phenotype data from more than 40,000 individuals across 9 longitudinal, epidemiological cohorts (Musunuru et al. 2010).

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