Congratulations to Professor Sheida Nabavi and Fatima Zare for winning the best poster award at the recent Association for Computing Machinery Conference on Bioinformatics, Computational Biology, and Health Informatics held in Boston. They presented their research project entitled “Bias and Noise Cancellation for Robust Copy Number Variation Detection” and according to Fatima, “the high-throughput next generation sequencing (NGS) technologies have created an opportunity for detecting copy number variations (CNVs) more accurately. However, efficient and precise detection of CNVs remains challenging due to high levels of noise and biases, data heterogeneity and the “big data” nature of NGS data. In this work, we introduce a novel preprocessing pipeline to improve the detection accuracy of CNVs in heterogeneous NGS data such as cancer whole exome sequencing data. We employ several normalizations to reduce biases due to GC contents, map ability and tumor contamination. We also utilize the Taut String method as an efficient effective smoothing approach to reduce noise.”
