Bioinformatics - Level 1 Module 1 - Shannon Saad

Shannon Saad - Self-Assessment - Module 1 S2 (REPOST)

1) Things Learned:

  • Technical Area:
    • Rstudio: Basic packages, ggplots package, and operations of different parts
    • Github: Made account, learned how to contribute to projects
    • R Programming: basics of coding language, statistical aspect, played around with graphs, and data analysis functions
    • Scientific Papers: Efficient approach to read and fully understand paper
    • Biology: Deeper understanding into function of microRNA and lncRNA within cells, process of finding prognostic markers for cancer in genes
    • Sequencing: learned how microarrays and DNA sequencing work and how differential expression and transcriptomics works
  • Tools:
    • Rstudio: Platform for R programming
    • Stem-away: Reading direction from mentors, asking for further help
    • Github: Learned about platform for future team projects
    • GEO2R: Used to analyze differential gene expression levels in diseased patients vs. control patients.
    • Google: Searching for ways to set up Rstudio, meaning of error messages
    • Youtube: Accessing Stem-Away videos and instructions, guidance from others in
  • Soft Skills:
    • Time management: Learned to ignore distractions after they were slowing me down
    • Willingness to ask for help: Contacted my mentor, Anya, when I was unsure of the next steps
    • Direction following skills: Closely read and followed Rstudio and R program directions (introduction documents)
    • Problem solving skills: Worked through problems that arose in programming using R by researching error messages, etc.
    • Grit: Pushed through setbacks.

2) Achievement Highlights:

  • Learned new programming language R with no prior experience
  • Navigated RStudio, Github, GEO, and Stem-away site successfully.
  • Met with with Team Lead Hale, other leads, and team (support system)
  • Furthered my passion for bioinformatics as I better understand how it works to detect diseases and how it can be used in prevention.

3) Tasks Completed:

  • Downloaded RStudio to my computer and got familiar with R programming even though I first needed to work through some problems getting the program running(functions, data analysis, etc.)
  • Took notes on how microarray and DNA sequencing can be used in data analysis and can later lead to greater understanding of diseases.
  • Joined Github and had an introduction to the platform.
  • Analyzed a gene dataset using GEO2R in order to see different expression levels of genes for Alzheimer’s patients and controls, though I needed to do some further research on this site because I had trouble finding some of its features.

Shannon Saad (Level 1) - Self-Assessment - Module 2 Session 2

  1. Things Learned:
  • Technical Area:
    • GEO database & Rstudio:
      • Learned where to find background information about the data that I am using in my analysis.
      • Used the Series Matrix file and Excel to organize metadata into a chart and loaded this into R using read.csv().
      • Downloaded CEL files and imported them to R studio using readAffy().
      • Used getGEO() to import dataset to Rstudio as well.
    • Scientific Papers: Learned how to better read scientific papers.
  • Tools:
    • GEO database
    • Rstudio
    • Google (for help)
    • Stem-Away Videos and Mentors
    • Youtube
  • Soft Skills:
    • Communication: explained problems I was having to Anya and other mentors who were able to help me.
    • Problem-Solving: When I ran into problems, I experimented with different ways to solve them.
    • Time management: I am improving in staying on task when I am working on a project.
  1. Achievement Highlights:
  • Got much more familiar with the GEO database and R programming.
  • Problem solved through errors and asked mentors for help when needed.
  • Learned how to efficiently read scientific papers.
  • Got more familiar with my team.
  1. Tasks Completed
  • Exceeded in using the GEO database to get data for analysis.
  • Successfully loaded metadata and CEL files into R studio.
  • Successfully loaded packages into RStudio.

Shannon Saad (Level 1) - Self-Assessment - Module 3 Session 2

  1. Things Learned:
  • Technical Area:
    • GEO: using lung cancer data (gene expression levels for both cancerous and normal tissues)
    • Rstudio: Learned how to do quality control, background correction, normalization, and how to create data visualizations.
  • Tools:
    • Rstudio: Used to process gene data.
    • Stem-away: followed directions and asked Anya for help.
    • Github: uploaded Module 3 deliverables.
    • Google: Searched for meanings of errors and solutions.
  • Soft Skills:
    • Problem-Solving: Worked through problems until I found the answer (Google, experimenting, asking for help etc.)
    • Team-Work: Asked my mentor for help and clarification by pinpointed what was going wrong (error messages, etc.).
  1. Achievement Highlights:
  • Learned how to spot outliers by using a PCA graph, boxplot, and heatmap.
  • Uploaded deliverables to Github.
  • Learned how to background correct and normalize data.
  1. Tasks Completed & Hurdles:
  • Did quality control of gene data, and visualized the data using different packages and functions in Rstudio.
  • Normalized data using an affy object.
  • I had some trouble using the ggplot2 package but fixed the problem after asking Anya for help.