Virtual Workshop

R Programming for Biologists: Beginners Level

Empowering Biologists with R: From Basics to Breakthroughs in Data Analysis.

About Workshop:

The workshop is an immersive and practical learning experience designed to equip biologists with essential skills in R programming. This workshop provides participants with a foundational understanding of R syntax, data manipulation, statistical analysis, and data visualization, all tailored to the specific needs of biologists. Through hands-on exercises and real-world case studies, participants gain practical experience in importing, cleaning, and analyzing biological datasets using R. The workshop emphasizes the application of R programming in diverse biological contexts, including experimental design, clinical data analysis, ecological modeling, and genomic exploration. By the end of the workshop, participants will have acquired the skills to effectively use R for data-driven decision-making in their biological research, setting a strong foundation for further exploration of advanced R topics. The interactive nature of the workshop fosters a collaborative learning environment, ensuring that participants leave with the confidence and proficiency to apply R programming to their specific research challenges.

Aim: The aim of the workshop is to empower biologists with essential skills in R programming, fostering a comprehensive understanding of its applications in biological research. This workshop aims to demystify the complexities of R, providing participants, from beginners to intermediate users, with a solid foundation in utilizing R for data analysis in the biological sciences. Through a combination of theoretical knowledge and hands-on practical sessions, attendees will gain proficiency in data manipulation, statistical analysis, and visualization, enabling them to harness the full potential of R as a powerful tool for extracting meaningful insights from biological datasets. By the end of the workshop, participants will be equipped with the confidence and skills necessary to integrate R seamlessly into their research workflows, ultimately enhancing the efficiency and depth of their biological analyses.

Workshop Objectives:

  • Biological Data Import: Enable participants to import diverse biological datasets (e.g., genomics, ecology) into R for analysis.
  • Bioinformatics Workflow Automation: Instruct on creating automated bioinformatics workflows in R, streamlining data processing and analysis pipelines.
  • Data Visualization for Biological Data: Learn the principles of effective data visualization and explore different types of plots suitable for biological data.
  • Statistical Analysis: Introduction to basic statistical concepts using R relevant to biological data.
  • Handling Biological Sequence Data in R: Learn  to import, manipulate, and analyze biological sequence data using R.
  • Making Publication-Quality Plots using ggplot2: In-depth exploration of ggplot2, a powerful data visualization package in R.

What you will learn?

Day 1: 

  • Introduction to R studio
  • Data Structures in R- vectors, matrix, lists and Dataframes
  • Using and Manipulating Basic R Data Types.
  • Control flow- if else, loops, apply

Day 2: 

  • Installing R libraries for data analysis
  • Basic statistical analysis with R
  • Correlation, Regression analysis
  • Concepts of R tidyverse

Day 3:

  • Data Visualization with ggplot2- bar plot, frequency plot, box plot, histogram, pie chart
  • Heat map generation
  • DNA and Protein sequence analysis with seqinr
  • Basics of Bio conductor package

Note: Any OS with latest version of R and R studio installed

Mentor Profile

Dr. Subarna Thakur is an Assistant Professor in the Department of Bioinformatics at the University of North Bengal. She received his/her Ph.D. Degree in Botany from the University of North Bengal in 2014 and then worked as a Post Doc in various institutes like JNU, Bose Institute and IRHS, Angers, France for 4 Years. She is having more than 10 Years of Experience in the field of Computational Biology and Genomics. Her Area of Expertise includes NGS Data analysis, Transcriptomics, Network Biology. She is the author of 10 original research articles in high-impact peer-reviewed journals.

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Fee Plan

StudentINR 999/- OR USD 40
Ph.D. Scholar / ResearcherINR 1199/- OR USD 45
Academician / FacultyINR 1499/- OR USD 50
Industry ProfessionalINR 1999/- OR USD 75

Important Dates

Registration Ends
07 Dec 2023 AT IST : 02:00 PM
Workshop Dates  07 Dec 2023 to 09 Dec 2023  AT IST : 03:00 PM

Get an e-Certificate of Participation!

Intended For : Graduates, Post Graduates, Research Scholars, Academicians, Industry Professionals of Biology, Genetics, Bioinformatics, Pharmaceutical and Biotech companies.

Career Supporting Skills

Data AnalysisR ProgrammingBioinformatics Tools and PipelinesBiostatistics for Healthcare ResearchDrug Discovery and Bioinformatics

Workshop Outcomes

  • Basic R Proficiency: Participants will have a foundational understanding of R programming, including syntax, data types, and basic functions.
  • Data Handling and Cleaning Skills: Participants will be able to import biological datasets into R, clean and preprocess data, addressing common challenges encountered in real-world scenarios.
  • Statistical Analysis Competence: Participants will possess the skills to perform basic statistical analyses using R, allowing them to draw meaningful conclusions from biological data.
  • Effective Data Visualization: Participants will be capable of creating clear and informative visualizations using R, enhancing their ability to communicate findings visually.
  • Introduction to Scripting: Participants will be familiar with scripting in R, enabling them to automate repetitive tasks and create reusable code.
  • Application of Statistical Tests: Participants will be able to apply statistical tests relevant to biological research questions, enhancing their ability to make data-driven decisions.
  • Practical Experience with Real Biological Data: Participants will have worked with real biological datasets during hands-on exercises and case studies, gaining practical experience in applying R to actual research scenarios.
  • Preparation for Intermediate R Topics: Participants will be prepared to explore intermediate-level topics in R programming and more specialized applications in their specific areas of biological research.