Somatic Mutations in Single-Cell Sequencing: Separating Signal from Noise

Discover a groundbreaking webinar delving into the development of SCAN2 and how this algorithm enables single-cell sequencing with high accuracy for somatic mutations. Somatic mutations arise due to DNA damage or errors in DNA synthesis and are propagated through cell division. Unlike inherited variants, somatic mutations are shared by only a fraction of the cells in an organism. Numerous algorithms have been developed to identify somatic mutations present in clonal populations in cancer cells. But, for non-cancer cells, the majority of somatic mutations — other than those that arise very early in development — are shared by very few cells or can even be private to a single cell. To identify such mutations, new detection techniques are required.

With standard bulk sequencing approaches, detecting mutations in <5% of cells is difficult at typical whole-genome sequencing depths of 30-60X. Increased sequencing depth allows access to lower-frequency mutations, but the cost of sequencing quickly becomes prohibitive and the detection limit does not improve substantially.

Join this webinar to gain insights into the SCAN2 algorithm and how it enables single-cell sequencing with high accuracy for somatic mutations.

Speakers

Peter J. Park, PhD, Professor of Biomedical Informatics, Harvard Medical School

Dr. Peter J. Park is a Professor of Biomedical Informatics at Harvard Medical School and Director of its Bioinformatics and Integrative Genomics PhD program. His research group specializes in computational and statistical analysis of large-scale DNA sequencing data to understand genetic and epigenetic mechanisms related to disease processes.

Originally trained in applied mathematics (BA from Harvard; PhD from Caltech), he was introduced to molecular biology and genetics during his postdoctoral studies in biostatistics. His laboratory has developed several algorithms for genome analysis and has made substantial contributions to consortium projects such as The Cancer Genome Atlas (TCGA), Encyclopedia of DNA Elements (ENCODE), Brain Somatic Mosaicism Network and 4D Nucleome (4DN).

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Lovelace J. Luquette, PhD, Postdoctoral Fellow, Harvard Medical School

Dr. Lovelace J. Luquette is a Postdoctoral Research Fellow in the laboratory of Dr. Peter Park at Harvard Medical School. He received his BA in mathematics and computer science at Boston University and his PhD in bioinformatics and integrative genomics at Harvard University. His expertise is in developing bioinformatic methods to analyze DNA sequencing data, with a special interest in somatic mutation discovery and single-cell technologies.

He is a contributor to several large projects focused on somatic mutation discovery, including The Cancer Genome Atlas (TCGA), the Brain Somatic Mosaicism Network (BSMN) and the Somatic Mosaicism across Human Tissues network (SMaHT) and has had the great opportunity to study mutational dynamics in the human brain at single-cell resolution through a long and fruitful collaboration with the laboratory of Dr. Christopher Walsh at Boston Children’s Hospital.

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