Workshop

Using Comparative Genomics To Predict Protein Coevolution Networks With The DECIPHER And Synextend Packages***

Comparative Genomics with DECIPHER and SynExtend*** Author(s): Aidan Hunter Lakshman, Nicholas Cooley, Erik Scott Wright Affiliation(s): University of Pittsburgh Twitter: @ahlakshman In the past decade, the number of sequenced proteins with unknown functions has grown exponentially while the number of experimentally analyzed proteins has increased at a relatively constant rate. To assign functions to more proteins, many in silico methods have been produced that predict protein function purely from gene sequence data.

Tidy Transcriptomics For Single-Cell RNA Sequencing Analyses**

Tidy Transcriptomics For Single-Cell RNA Sequencing Analyses** Author(s): Stefano Mangiola, Maria Doyle Affiliation(s): Walter and Eliza Hall Institute of Medical Research, Peter MacCallum Cancer Center This workshop will present how to perform analysis of single-cell RNA sequencing data following the tidy data paradigm. The tidy data paradigm provides a standard way to organize data values within a dataset, where each variable is a column, each observation is a row, and data is manipulated using an easy-to-understand vocabulary.

Pharmacogx 3.0: Data Structures And Methods For Discovering Molecular Biomarkers Of Response To Drug Combination Therapy In Precision Oncology**

Pharmacogx 3.0: Data Structures And Methods For Discovering Molecular Biomarkers Of Response To Drug Combination Therapy In Precision Oncology** Author(s): Christopher Bernard Eeles, Petr Smirnov, Benjamin Haibe-Kains Affiliation(s): Princess Margaret Cancer Center Initially published to address gaps in the reproducibility and comparability of large high-throughput pharmacogenomic studies, PharmacoGx has evolved into a rich set of tools for storing, annotating, curating, and analyzing the relationship between molecular phenotypes and drug response in preclinical cancer models.

Multi-omic Integration Of Cbioportal And TCGA Data With Multiassayexperiment**

Multi-omic Integration Of Cbioportal And TCGA Data With Multiassayexperiment** Author(s): Marcel Ramos, Levi Waldron, Ludwig Geistlinger Affiliation(s): CUNY Graduate School of Public Health and Health Policy Twitter: @M2RuseR This workshop demonstrates how to leverage public multi-omics databases, such as the cBioPortal and The Cancer Genome Atlas (TCGA). Workshop participants are given an overview of the `cBioPortalData`, `curatedTCGAData`, and `terraTCGAdata` (experimental) data packages. It introduces users to minimal data management with `MultiAssayExperiment` and `TCGAutils`, packages that organize and manage multi-omics datasets.

Introduction to Bioconductor annotation resources*

Introduction to Bioconductor annotation resources* Author(s): James MacDonald Affiliation(s): University of Washington There are various annotation packages provided by the Bioconductor project that can be used to incorporate additional information to results from high-throughput experiments. This can be as simple as mapping Ensembl IDs to corresponding HUGO gene symbols, to much more complex queries involving multiple data sources. In this workshop we will cover the various classes of annotation packages, what they contain, and how to use them efficiently.

Epidemiology for Bioinformaticians**

Epidemiology for Bioinformaticians** Author(s): Chloe Anya Mirzayi, Levi Waldron Affiliation(s): City University of New York (CUNY) Twitter: @cmirzayi Concepts of causal inference in epidemiology have important ramifications for studies across bioinformatics and other fields of health research. In this workshop, we introduce basic concepts of epidemiology, study design, and causal inference for bioinformaticians. Emphasis is placed on addressing bias and confounding as common threats to assessing a causal pathway in a variety of study design types and when using common forms of analyses such as GWAS and survival analysis.

Bioconductor Docker Images For Multi-Node Parallel Computing On The Cloud***

Bioconductor Docker Images For Multi-Node Parallel Computing On The Cloud*** Author(s): Nitesh Turaga Affiliation(s): Dana Farber Cancer Institute Twitter: @niteshturaga Bioconductor produces docker images that are widely used because they containerize system dependencies of all Bioconductor packages along with the community version of RStudio. Using Kubernetes, a container orchestration software, it is now possible to deploy these docker images on a cluster and use them for multi-node parallel computing.

Workshop

Using Comparative Genomics To Predict Protein Coevolution Networks With The DECIPHER And Synextend Packages***

Tidy Transcriptomics For Single-Cell RNA Sequencing Analyses**

Pharmacogx 3.0: Data Structures And Methods For Discovering Molecular Biomarkers Of Response To Drug Combination Therapy In Precision Oncology**

Multi-omic Integration Of Cbioportal And TCGA Data With Multiassayexperiment**

Introduction to Bioconductor annotation resources*

Epidemiology for Bioinformaticians**

Bioconductor Docker Images For Multi-Node Parallel Computing On The Cloud***

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