Bioinformatics - Level 1 Module 1: Nayana Vallamkondu

Technical Area:

  • R Studio: Understanding the fundamentals of R code and getting familiar with its interface
  • Learning how to read research papers efficiently
  • Understanding more about the bioinformatics field, such as methods and tools used

Tools:

  • R studio and R installer
    • ggplot2
    • Bioconductor (specifically EnhancedVolcano)
  • Resources:
    • Official ggplot2 website
    • YouTube
    • Stack Overflow
    • RStudio Community

Soft Skills:

  • Time management: pacing myself between reading the given material and performing tasks myself on application
  • Utilizing resources: Researching and clarifying my own problem with resources at hand:
    • Official ggplot2 website
    • YouTube
    • Stack Overflow
    • RStudio Community
  • Navigation: Understanding how to use the Stem-Away website
  • Communication: Communicating with the leads/founder to clarify any doubts
  • Determination: At first I thought I wouldn’t be able to understand R, but after going through the material provided, I understand it very well to the point I was able to do problem solving and enjoyed writing code with it very much

Three Achievement Highlights:

  • Reading through the materials given and practiced on the application itself. This allowed me to grasp the fundamentals of R and understand its interface
  • Errors: Experimenting with the list and tasks of different errors provided in addition to fixing errors that I personally occurred when I tried to execute code
  • Understand the basics of how to read scientific papers and getting a better understanding of the bioinformatics field

Tasks Completed:

Originally I was confused about the platform, but I was able to navigate and accomplish the given tasks for this module successfully. I was able to navigate through the STEM-Away website and make use of the resources given to us. I read the given material and was able to understand the basic fundamentals of R: intro to R (download R studio and R installer and understand its interface), syntax and data structures, functions and arguments, and data wrangling, and visualization (creating basic scatterplots, barplots, histograms, box plots, and volcano plots and changing their appearance such as labeling, font, color, and themes) . Whenever I encountered any problems while executing the code or wanted more clarification on certain commands, I was successfully able to use available resources on the internet, such Stack Overflow, RStudio Community, the official ggplot2 website, and YouTube. I was also able to familiarize myself with the different types of errors (syntax, semantic, and logical errors). There were some errors and issues that I personally encountered when executing code, which I was able to find the solution for based on what I learned. Outside of R, I learned efficient ways to read a research paper and get an understanding of how all the information in it can be condensed to something that encompasses all the important points. In addition to this, I was able to understand more about the bioinformatics field and the resources and methods that are used to accomplish many tasks that are required by the field (ex: microarrays, RNA sequencing, FASTQC, GEO2R, and R).