Fully Automatic Analysis of DNA Microarray Images
Poster Feb 01, 2007
S.Mitterhuber, B.Petersch and O.Serrano
During the last years, the advent and rapid development of DNA microarray techniques has revolutionized genetic research in life sciences. We are presenting a new stand-alone software for fully automated analysis of microarray images. It employs a number of novel image processing algorithms for grid detection and spot segmentation which assure high calculation speed and accuracy.
The software can be run using a self-explanatory graphical user interface (GUI) or from the command line which gives additional flexibility and allows integration into larger microarray analysis frameworks. Batches of images as well as single images can be processed.
The main benefits of this software over existing ones are its extremely easy handling (no user interaction required), the fast and robust gridding, the flexible free form spot segmentation and its multiple usage scenarios. We present examples of the performance of the proposed algorithms on real-world microarray images with heavy noise and artefacts.
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Genome-wide association studies (GWAS) have identified more than 100 genetic loci associated with type 2 diabetes. The majority of these are located in the intergenic or intragenic regions suggesting that the implicated variants may alter chromatin conformation. This, in turn, is likely to influence the expression of nearby or more remotely located genes to alter beta cell function. At present, however, detailed molecular and functional analyses are still lacking for most of these variants. We recently analysed one of these loci and mapped five causal variants in an islet-specific enhancer cluster within the STARD10 gene locus. Here, we aimed to understand how these causal variants influence b-cell function by alteration of the chromatin structure of enhancer clusterREAD MORE
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