Abstract:

This webinar will focus on the detection of differentially expressed genes and their biological contextualization using Strand NGS as a platform for complete analysis, visualization, and data management.

RNA-Seq data analysis involves many diverse challenges like the need for curated biological annotations, statistical test choices, and intuitive visualizations that support large-scale data. By providing all the means that help biologists in decision-making, we intend to enable them for faster and more accurate publication-quality analysis.

Strand NGS is a NGS data analysis software designed for the biologists. In this Webinar, Srikanthi, a biologist by training, would present the features of Strand NGS using a cardiac data set from a non-primate mammal as an example. These include, the ease of analyzing RNA-Seq data from any model or non-model organism using the packaged annotations, data import, normalization, sample phenotype addition, differential expression analysis of multi-factorial study designs, and complete biological contextualization of the resultant gene lists to be showcased in detail. She would also discuss how Strand NGS enables the use of multiple differential expression methods in the same experiment thereby ensuring an easy comparison of results from various methods.

Do join us to see how we go from a raw data set to publication-ready images in less than an hour.

About the speaker:

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Ms. Srikanthi Ramachandrula has a Masters in Biotechnology from the prestigious IIT - Bombay, India. As an Application Scientist working with multi-disciplinary teams, she is responsible for scoping, validating, documenting, and communicating the utility of various bioinformatics tools for solving biological research problems. At Strand Life Sciences, she has been involved in the co-design of microarray and sequencing data analysis software. With a decade of experience, her involvement in a number of collaborative projects with various academic and commercial institutes around the globe helped in developing a deep understanding of integrated biology approaches involved in studying genotype-phenotype associations.



Webinar details

Sessions San Francisco Time
(PDT)
Tokyo Time
(JST)
Belgium Time
(CET)
Mumbai Time
(IST)
Session 1 20 Mar
3:00 AM
20 Mar
7:00 PM
20 Mar
11:00 AM
20 Mar
3:30 PM
Session 2 20 Mar
11:00 AM
21 Mar
3:00 AM
20 Mar
7:00 PM
20 Mar
11:30 PM

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