Bioinformatics - Level 1 Module 1 - Shannon Saad

Shannon Saad - Self-Assessment - Module 1

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 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: Learned to push through setbacks and continue even though I felt that I had fallen behind; self-encouragement

2) Achievement Highlights:

  • Learned new programming language R with no prior experience
  • Navigated RStudio, Github, GEO, and Stem-away site successfully and learned their roles in bioinformatics
  • Made contact and interacted with Stem-away mentor (support system)
  • Furthered my passion for bioinformatics as I understand how it works to detect disease which can be implemented in disease 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.

@anya

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Shannon Saad - Self-Assessment - Module 2

1) Things Learned:

  • Technical Area:
    • Rstudio: importing csv files, getting metadata, affy packages functions, ReadAffy function, installing and loading libraries
    • GEO: using GEO2R for data analysis, downloading .tar and .CEL files
  • Tools:
    • Rstudio: platform for gene data analysis
    • Stem-away: communicating with mentor for further help, reading instructions
    • Github: added to bioinformatics team
    • GEO2R: used for gene expression data analysis
    • Google: searched for meaning of R messages (update messages, etc.)
  • Soft Skills:
    • Communication skills: talked to my mentor about the problems
    • Confidence: felt more confident in what I was doing

2) Achievement Highlights:

  • Imported colorectal cancer metadata into R after making a .csv file in Excel for the first time.
  • Learned different functions of packages such as affy and pheatmap (ReadAffy())
  • Explored GEO database and GEO2R
  • Learned how to find sample data in .txt files.

3) Tasks Completed & Hurdles:

  • Downloaded .txt file and learned how to find info for datatable in excel; imported .csv file into Rstudio
  • Initially had some trouble importing .CEL file into R and using ReadAffy function, but I understood what to do after Anya helped me during the meeting
  • Figured out that .txt file doesn’t open in Chrome, and opened it successfully in Edge
  • Made a metadata table in Excel and saved it as a .csv file.

@anya

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Shannon Saad - Self-Assessment - Module 3

  1. Things Learned:
  • Technical Area:
    • GEO: using colorectal cancer data (genes expression levels for both cancerous and normal tissues
    • Rstudio: Learned how to do quality control,background correct, 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.
  • 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 better make a graph by making the PCA graph.
  • Learned how to upload and did upload deliverables to Github.
  • Learned how to do background correction and normalization of data.
  1. Tasks Completed & Hurdles:
  • Did quality control of gene data, and visualized the data using different packages and functions in Rstudio.
  • Batch corrected and normalized data using an affy object.
  • Initially, I had trouble making the PCA graph and heatmap, but after looking up various errors on Google and asking Anya for clarification, I was able to make these visualizations.
    • Note: I had a specific problem with making annotations on the heatmap, but figured it out.

@anya