Abstract Motivation: Synthesis of data from published human genetic association studies is a critical step in the translation of human genome discoveries into health application. Although genetic association studies account for a substantial proportion of the abstracts in PubMed, identifying them with standard queries is not always accurate or efficient. Further automating the literature screening process can reduce the burden of a labor-intensive and time-consuming traditional literature search. The Support Vector Machine (SVM), a well-established machine learning technique, has been successful in classifying text, including biomedical literature. The GAPscreener, a free SVM-based software, can be used to assist in screening PubMed abstracts for human genetic association studies. GAPscreener has been used in the screening and curation of HuGE Navigator database (http://www.hugenavigator.net ). Results: Weighted SVM feature selection based on a keyword list obtained by the two-way z-score method demonstrated the best screening performance, achieving 97.5% sensitivity and 98.3% specificity in performance testing. Compared with the traditional screening process based on a complex PubMed query, the SVM tool reduced by about 90% the number of abstracts requiring individual review by the database curator. The tool also ascertained 47 articles that were missed by the traditional literature screening process during the four-week test period. We examined the literature on genetic associations with preterm birth as an example; compared with the traditional, manual process, the GAPscreener both reduced effort and improved accuracy.

Installation instruction: Download the software here. Follow the installation process. After finishing the installation, the program icon should be on your desktop and on the program menu list. Tip: If you do not have privileges to install the software into the Program File directory (by default), you can change the directory when the popup window asks for the directory during the installation, and keep clicking OK in the error message window.

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