Data Wrangling is another class in the NIH Library Introduction to R and RStudio Series. A basic understanding of using R and RStudio to manage data is expected. This one-hour class will build on the introduction provided in Data Wrangling Part 1 to further explore the R tidyverse package and how to use it to manipulate, analyze and export data. This class will explore options for using the tidyverse functions group_by, summarize, count, arrange, pivot_wider, pivot_longer, and export.
Data Wrangling is another class in the NIH Library Introduction to R and RStudio Series. A basic understanding of using R and RStudio to manage data is expected. This one-hour class will introduce the R tidyverse package and how to use it to manipulate, analyze and export data. This class will explore options for using the tidyverse functions select, filter, pipes, mutate, head, is.na, and export. Learning these functions will enable users to have well formatted data frames for future clean and consistent analysis and visualizations.
This one-hour session builds on the Introduction to R & RStudio class. The session begins by introducing and identifying different categories of data. Participants will examine data types, create vectors, and assign values to vectors. They will also learn how to import data into RStudio, and examine those data frames for further cleaning, analysis and visualization. Participants will learn the differences between numeric, character, and logical data and how to change data types in R. They will also be able to create subsets and export project data for future use.
Clinical variant analysis is a three-stage process that entails quality control and processing of data, creating a draft report for cell variant evaluations using different genomic databases and annotation sources, assessing the draft report, and signing-off on the final report. VSClinical is software that uses a single testing paradigm to consolidate and automate the workflow of this three-part analysis.
VSClinical is designed for researchers to efficiently process the clinical interpretation of cell variants based on Association for Molecular Pathology (AMP) and American College of Medical Genetics and Genomics (ACMG) guidelines. This class will demonstrate how VSClinical enables labs to test for both germline and somatic cell variants according to the American College of Medical Genetics (ACMG) and AMP guidelines in an automated fashion.
Using VSClinical for American College of Medical Genetics (ACMG) Guidelines and Copy Numerical Variations (CNVs)
Evaluating variants according to the American College of Medical Genetics and Genomics (ACMG) guidelines can be an extensive process that requires an in-depth understanding of all available criteria for any cell variant. VSClinical is software that uses a single testing paradigm to automate the complex ACMG guidelines process. Copy Number Variation (CNV) is a type of structural variation in which sections of the genome are duplicated or deleted.
The Human Gene Mutation Database (HGMD) database provides quick access to known published gene lesions responsible for human inherited disease. This session will explore how to query genes and mutations in HGMD and how to view the curated content.
Single nucleotide polymorphism (SNP) & Variation Suite (SVS) is an analytic tool created to empower researchers to perform complex analyses and visualizations on genomic and phenotypic data. Genome-Wide Association Studies (GWAS) continues to be an effective method for identifying disease susceptible genes in humans and other organisms.
VSClinical is designed for researchers to efficiently process the clinical interpretation of variants based on Association for Molecular Pathology (AMP) and American College of Medical Genetics and Genomics (ACMG) guidelines. This class will review the importance and value of automating the search for available clinical trials for the improvement of cancer treatment and prevention. Attendees will explore content and examples leveraged by VSClinical for site, inclusion criteria, relevant drugs, and matching biomarkers.
Key Pathway Advisor (KPA) is a web application for biological pathway analysis of OMICs data. This session will demonstrate using KPA to: explore the biological meaning of data; predict key protein activity changes that could be the root cause of gene expression alterations; understand how biological pathways are impacted by data; create hypotheses about new targets, mechanisms of action, biomarkers and disease associations; and align results with current knowledge of biomarkers and drug targets. Bioinformatics experience is not required to use this tool.
This is the first class in the NIH Library Introduction to R Series. This class provides a basic overview of the functionality of R programming language and RStudio. R is a programming language and open source environment for statistical computing and graphics.
This is the second class in the NIH Library Introduction to R Series. A basic understanding of R and RStudio is expected. This class provides a basic overview of R data types, data frames, and factors. Additionally, this class will cover indexing and subsetting data frames, and dealing with missing data. R is a programming language and open source environment for statistical computing and graphics.
For the Introductory Training we will cover basic topics such as: MetaCore overview; how to use MetaCore as a knowledge mining tool; how to upload data; running functional enrichments and exploring pathway maps; and running workflows.
For the Advanced Training, topics covered depend upon survey results: find key hubs using over-connectivity analysis; using Microarray repository for gene comparisons against public data; building networks with MetaCore; constructing your own pathway maps; performing toxicogenomic analysis in MetaCore; analyzing and building networks with miRNA and mRNA data; analyzing multi-omics data (RNA-seq, proteomics, metabolomics, etc).