Offered Again 5/11/21 & 9/14/21
'R' is a popular statistics software program used widely in various research fields. This live remote two day lecture and hands-on computer based laboratory workshop is designed to introduce bench scientists to R programming, utilizing the different tools available for scientific data analysis. Hands-on topics will include Data Types; Import/Export Data; "Manipulation of Tabular Data", "Basic Statistics, and "Visualization using R".
Real-Time Interactive Lecture, Laboratory Protocol and Discussion
Team taught by active researchers
Lectures, Lab Protocols, Reference Materials included
Space limited to 24 participants
No Travel, Convenient and Cost Effective
"Very informative workshop with a very knowledgable lecturer. Covered the various aspects of NGS and provided guidance I needed."
University of the West Indies (Cave Hill)
"It was my first experience with professional development workshop in the USA. I liked it a lot. It was well organized, flexible and friendly. It helped to put in order my preceding knowledge and gain more."
Staff Scientist II
Maine Medical Center Research Institute
"This was a great workshop to become acquainted with Next Generation Sequencing Technologies and applications. I would highly recommend this course to anyone interested in an in-depth hands-on course covering relevant NGS bioinformatics and command line tools. Great experience!"
Henry M. Jackson Foundation
for the Advancement of Military Medicine
"Great investment. Took material that would have taken months to compile and perfect on my own, and packed it into 3 days."
University of Central Florida
Assistance will be given to those who need help installing 'R' and 'R Studio' (please make sure you have administrator rights). By using your personal laptop, you will be able to continue using R and R Studio, utilizing the examples given during the program after the workshop has ended.
|Sajung Yun, Ph.D.
Dr. Sajung Yun received his Ph.D. in biomedical sciences from University of Hawaii at Manoa. His doctoral dissertation was about relationships between vascular architecture of Circle of Willis and dementia including Alzheimer's disease. Currently a contractor with the National Institute of Diabetes Digestive and Kidney Diseases (NIDDK), Dr. Yun’s current research projects focus on in vivo and in vitro gastrointestinal tumors using CRISPR-Cas9. Dr. Yun has managed large clinical databases and currently holds a certification in healthcare data analytics.
|Allissa Dillman, Ph.D.
Dr. Allissa Dillman received her Ph.D. in neuroscience from the graduate partnership program between NIH and the Karolinska Institutet. She studied gene expression regulation, splicing and RNA editing in development and disease. Her specific interest in RNA modifications include base pair mapping in the transcriptome and their potential biological function. In 2015, she joined the National Cancer Institute for her postdoctoral work where she studies epigenetic regulation of splicing and the identification and biological function of novel RNA modifications. Throughout her scientific career she has contributed to more than 30 scientific publications and participates in mentorship and teaching of both bioinformatics and RNA biology. Dr. Dillman has also participated as a team lead for RNA related projects in multiple hackathons at the NIH.
|Niraj Trivedi, Ph.D.
Dr. Trivedi is a branch statistician for Columbus Technologies as a contractor for the Social Behavioral Research Branch at the National Human Genome Research Institute (NHGRI) at the National Institutes of Health. Dr. Trivedi provides statistical, computational, and bioinformatic support to scientists of the institute for their data analysis needs. This includes microarray analysis, statistical analysis, and general analysis in biomedical "big data"
Introduction to R & R Studio
R as a calculator and like an Excel Spreadsheet
• Installation of R and R Studio
• Data types: Integer, real, complex, character, factor, logical
• Data structures
• Vectors, matrices, data frames, lists, objects
• Working with packages: install.packages(), library()
Statistics with R
R as a statistics software such as SPSS and SAS
• Chi-square test
• Fisher’s exact test
• Non parametric tests (Wilcox test, Kolmogorov-Smirnov test)
• Shapiro-Wilk normality test
• Correlation analysis
Plotting with R
R as a graphing software like Prism
• Basic plottings
• Histograms, density plots, bar plots
• Scatter plots, linear regression, violin plots
Programming in R
R as a programming language
• Analysis of R Start-up message
• R Markdown
• Operators, functions, arguments, variables, data types
• Fixing the missing values
• Apply function (lapply, sapply, tapply), for loop, if statement
• Custom functions
• Data visualization
• Dplyr package Statistics
• Models in R
• Packaging and Sharing your R codes with others
Advanced Topics in R
R for advanced analysis
• Machine learing in R
• PCA, t-SNE
• Graph theory in R
• Genomic applications in R
• Packaging and Sharing your R codes with others