Recently, Copy Number Variation (CNV) has been recognized as one of the most important genomic alterations in the study of human variation, as it can be employed as a novel marker for human disease studies. Thus, many hardware technologies have been developed to detect copy number variations, including chip-based technologies. However, owing to its complexity, relatively few analysis tools are currently available for CNV, and most public tools have only limited functions and Graphic User Interfaces (GUI). CNVAS is a powerful software package for the analysis of CNV. Two different algorithms, Smith Waterman (SW) and Circular Binary Segmentation (CBS), are implemented for the detection of CNV regions. Furthermore, in order to evaluate the relationship between phenotype and CNV, CNVAS can perform the Chi-square test and Fisher’s exact test. Result visualization is another strong merit of the CNVAS software. CNVAS can show the analysis results in the form of chromosome ideograms, and these can be exported in the form of an image file. Furthermore, CNVAS has a database system, which can manage the user’s data from different sources and under different experimental conditions. CNVAS is a web-based program, and users can freely access the CNVAS by connecting to http://biomi.cdc.go.kr/CNVAS/.