Ethanlau - Bioinformatics Pathway

Things Learned
Technical Area: I learned the main idea of the paper and the basic skills of coding in R. I also brushed up on my python skills.
Tools: R, Jupyter Notebook, Slack, Asana
Soft Skills: Learning how to work in groups on an online platform.

Achievement highlights
Read through the paper and understood the fundamentals of it. Completed all assignments in a timely manner.

List of training and meetings attended:
6/1 Team meeting, 6/2 R training, 6/5 R training, 6/9 R training, 6/9 Python training, 6/10 logistical meeting, 6/10 technical webinar, 6/11 Office Hours, 6/11 team meeting, 6/12 welcome session, 6/12 R training, 6/12 Happy Hour, 6/15 Team Meeting, 6/15 Python Office Hours, 6/16 Asana Training

Goals for the upcoming week:
Continue to build my skills in R and Python and apply what I learned to the data.
Further my understanding of the paper and produce results.

Tasks Completed
All R Exercises
All Python Exercises.
Read the paper Construction and Analysis of a ceRNA Network Reveals Potential Prognostic Markers in Colorectal Cancer.
One of the main hurdles I faced when completing the tasks was the difficulty of understanding many of the figures and what those figures represented. I solved this problem by asking questions and looking up what those figures represent.

Things Learned
Technical Area: I learned how to create PCA plots and quality control plots in R. I also learned how to conduct normalizations and preliminary analysis.
Tools: affy, affyPLM, and affyQCReport, Asana
Soft Skills: Learning how to work in groups on an online platform.

Achievement highlights
Completed Week 3 Deliverables and learned how to use Asana.

List of training and meetings attended:
6/16 Asana Training, 6/16 Python and Pandas Webinar, 6/17 Technical Training Webinar, 6/18 Gene Team Meeting, 6/19 Gene Team Happy Hour, 6/19 Office Hours

Goals for the upcoming week:
Continue to build my skills in R and Python and apply what I learned to the data. Starting the week 4 deliverables ahead of time.

Tasks Completed
Completed PCA plot
Completed NUSE and RLE boxplots and histograms of medians.
One of the main hurdles I faced when completing the tasks was the difficulty of getting the code to work due to my inexperience in R. I overcame this by asking questions and googling.

Things Learned
Technical Area: Learned how to annotate genes in R
Preliminary understanding of Limma (package in R)

Tools: Limma, Annotation Packages, Pandas, Seaborn, Matplotlib, Github
Soft Skills: Learning how to work in groups on an online platform.

Achievement highlights
At first, I was very confused on how to complete the week 4 deliverables. After communicating with my group, we collectively completed the Week 4 Deliverables.

List of training and meetings attended:
6/24 Office Hours, 6/24 Fireside Chat, 6/25 Bioinformatics Webinar, 6/25 Gene Team Meeting, 6/29 Gene Team Meeting,

Goals for the upcoming week:
Continue to build my skills in R and Python and apply what I learned to the data. Starting the week 5 deliverables earlier so I can ask questions.

Tasks Completed
Completed Week 4 Deliverables
Presented on Week 3 Deliverables
Compiled Phenotypic Data

Final Self-Assessment

What I Have Learned:

  • Understanding scientific writing (figures and methodology)
  • Analysis of microarray data using R
  • Downloading GEO datasets from online databases
  • Running quality control assessments in R
  • Understanding and creating PCA plots, heat maps, and volcano plots using microarray data
  • Differential expression analysis
  • Determining gene ontology
  • Creating plots in python using seaborn and matplotlib
  • Other packages in R (affy, affyPLM, etc.)

Tools:

  • Asana
  • G-Suite
  • Jupyter Notebook
  • R Studio
  • Github
  • STEM-Away forum
  • Slack

Soft Skills:

  • Connecting with people on linkedin
  • Working in both small and groups in an online environment
  • Improving my presentational skills
  • Helping others perform tasks

Achievements:
Over the course of this 8-week internship, I learned many things related to field of Bioinformatics. I learned how to extract and analyze data using R packages, despite my limited prior knowledge of the topic. I learned how control the quality of data and how to find trends in differentially expressed genes. On top of the technical skills I learned at this internship, I gained valuable soft-skills involving communication and teamwork. I hope to use the skills and knowledge I learned from this internship to future positions in the classroom and in the workplace.

EthanLau.pdf (65.2 KB)