Forum:Live Webinar on DNA-Seq data analysis- Case Studies on 22 Feb
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7.2 years ago
Genomics ▴ 70

DNA-Seq data can be analyzed and visualized using an extensive workflow in Strand NGS software. The software has been designed for the biologists. Strand NGS supports analysis of whole exome, whole genome and targeted sequencing experiments. The DNA-Seq workflow includes the ability to detect variants (SNPs, MNPs and short InDels), annotate them with dbSNP, and report for each SNP the kind of effect it has on the genes and provides list of affected genes. Biological contextualization of the affected genes can be performed by downstream analysis such as GO, GSA, pathway analysis.

Large structural variations, including large insertions, deletions, inversions, and translocations, can also be detected with paired-end and mate-paired data. Copy number variation (CNV) analysis can be done using tumor-normal pairs. Strand NGS has easy to use built in pipelines (with an option to customize) for time consuming jobs which automates analysis and leaves more time for end data interpretation. In this webinar we will discuss case studies using the DNA-Seq data analysis workflow in Strand NGS and also highlight on parameters within each feature that can be optimized depending on datasets and analysis needs.

Details:

Session 1: 2:30 PM IST, 22 Feb
Session 2: 10:30 PM IST, 22 Feb

Speaker: Dr. Suman Kapoor, Manager- Application Science at Strand Life Sciences, has over 10 years experience in molecular biology, next-generation sequencing based testing, clinical genomics, and personalized medicine for disease management and prenatal testing. Dr. Suman holds a Ph.D in Molecular and Cell Biology from Indian Institute of Science, Bangalore. Prior to joining Strand NGS team, Suman has worked extensively on protein synthesis in eubacteria and has experience working in CAP and NABL accredited lab validating and interpreting NGS based diagnostic tests.

Register here: http://www.strand-ngs.com/webinar_registration

alignment RNA-Seq genome SNP • 1.4k views
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