Influence of Dictionary Size on the Lossless Compression of Microarray Images

A key challenge in the management of microarray data is the large size of images that constitute the output of microarray experiments. Therefore, only the expression values extracted from these experiments are generally made available. However, the extraction of expression data is effected by a variety of factors, such as the thresholds used for background intensity correction, method used for grid determination, and parameters used in foreground (spot)-background delineation. This information is not always available or consistent across experiments and impacts downstream data analysis. Furthermore, the lack of access to the image-based primary data often leads to costly replication of experiments. Currently, both lossy and lossless compression techniques have been developed for microarray images. While lossy algorithms deliver better compression, a significant advantage of the lossless techniques is that they guarantee against loss of information that is putatively of biological impo...

• Type: Conference
• Year: 2007
• Where: CBMS
• Authors: Robert Bierman, Rahul Singh
• Keywords: CBMS 2007, Dictionary Size, Lossless Compression Techniques, Medical Imaging, Microarray Data