Ernest - Bioinformatics Pathway

Things Learned:

–Technical Area:

I studied the ins and outs of a research paper that looked at the correlation between expression of certain genes/miRNA/RNA to determine prognostic markers for colorectal cancer, familiarized myself with their data and the way it was structured, refreshed myself on how to code in Python and learned more about R, and familiarized myself with Slack/Calendar/etc… to help me know what I must do (still working on mastering navigating the Stem Away Website).

–Tools:

R, Python, Slack, Calendar, Stem-Away forums, and Critical analysis of scientific work.

–Soft Skills:

I explored Slack and Stem Away forums and learned how to effectively communicate across said modes of communication. I have not really talked with team members due to the fact that I do not have a mic compatible with my desktop, but I worked at communicating with the built in text services that Zoom and Meets have. I will work towards finding a mic in which I can use on the desktop so I can become more involved with the group.

Achievement Highlights:

  • Completed the basics of Python with little difficulty and completed R exercises and gained a better understanding.
  • Read through the paper and understood the fundamentals and worked towards a comprehensive understanding of it.
  • I set up all my accounts on my desktop so that I can be informed and aware of events

Meetings Attended:

  • Attended all the team meetings (team 4 then gene team)
  • Attended all the technical training sessions
  • Attended/watched all the R training sessions
  • Missed the Python training but watched the videos
  • Attended logical webinar 6/10, and office hours 6/11
  • Attended the welcome session 6/12

Tasks Completed:

  • The Python and the R exercises that were given

-Technical Area:

Furthered knowledge in R and practiced applying it to tasks in the week one deliverable. Finished the week one deliverable which required understanding of the figures generated using arrayqualitymetrics().

-Tools:

R, Python, Slack, Calendar, and Stem-Away forums.

-Soft Skills:

I got a mic and began to participate more within the small teams that the leads split us into. I also began to talk in the big group meetings. I will work forth to participate more because while I am beginning to participate, I am not contributing as much as I could.

Achievement Highlights:

  • Successfully applied the R training to the quality control of the data.
  • Began to collaborate with the team members
  • Completed the week one deliverable

Meetings Attended:

  • All gene team meetings
  • Python and pandas
  • Asana Training
  • Technical training webinar
  • Team 4 meetings

Task completed:

  • week one deliverable
  • Qc report based on arrayqualitymetrics()
  • PCA plots for normalized and non-normalized data

-Technical Area:

Learned how to use the limma package and learned transformations of the data matrix.

-Tools:

R, Python, Slack, GitHub, Calendar, and Stem-Away forums.

-Soft skills:

Participated more within the group discussions and I participated within the larger group discussions. Communicated on the forums for help.

Achievement Highlights:

  • Successfully applied the information from limma documentation and instruction
  • Collaborated with the groups to verify and generate the required data
  • Completed the week 4 deliverable

Meetings Attended:

  • all Gene Team meetings
  • GitHub training
  • R training
  • Group 4 meetings

Tasks completed:

  • use limma to analyze the data
  • created a presentable document
  • created a volcano plot with the data generated using lmfit
  • determined thresholds using the volcano plot
  • looked at some genes of interest that pass the thresholds

-Technical Area:

Learned more about coding with python using pandas, seaborn, and matplotlib.

-Tools:

R, Python, Slack, GitHub, Calendar, and Stem-Away forums.

-Soft Skills:

Worked with a new group to make a presentation where we all talked.

Achievement Highlights:

  • completed python exercise #2
  • processed the gene data using limma
  • isolated the phenotypic data
  • created a presentation to inform fellow group members of our analysis

Meetings Attended:

  • all gene team meetings
  • github webinar
  • office hours
  • R office hours

Tasks Completed:

  • week 4 deliverable
  • processed data using limma
  • presentation for the other groups within gene team
  • separated the phenotypic data.

-Technical Area:

Learned to use the cluster profiler package in R and used enrichR website to do gene clustering.

-Tools:

R, Python, Slack, GitHub, Calendar, and Stem-Away forums.

-Soft Skills:

Continued to work with group 6 to make a new presentation for the week 5 deliverable.

Achievement Highlights:

  • Processed genes using cluster profiler
  • Used enrichR website to
  • created a presentation to inform fellow group members of our analysis

Meetings Attended:

  • all gene team meetings
  • meeting with mentors

Tasks Completed:

  • week 5 deliverable
  • generated figures that describe the functions of the genes
  • presentation for the other groups within gene team
  • used the website to verify said functions

-Technical Area:

Pooled previous knowledge to create the final deliverable

-Tools:

R, Python, Slack, GitHub, Calendar, and Stem-Away forums.

-Soft Skills:

Worked more independently but still collaborated to finish the final deliverable.

Achievement Highlights:

  • Completed final deliverable
  • generated volcano plot for the new data set
  • generated enrichR figures for the new data set

Meetings Attended:

  • all gene team meetings

Tasks Completed:

  • final deliverable
  • generated figures that describe the functions of the genes of the new data set
  • generated a volcano plot to describe the new data set

Final Self Assessment

-Technical Area:

  • analyzed and understood a scientific paper on the potential of prognostic markers within the expression of genes for colorectal cancer
  • Learned the fundamentals of R code and the various packages that where used to analyze the data (ex: Limma, ggplot, enhancedvolcanoplot, affy, annotationdbi, and etc…)
  • Learned the fundamentals of Python to construct plots using Pandas, seaborn, and matplotlib
  • Understood and created plots that aided us in our analysis (ex: NUSE, PCA, volcano plots, heatmaps, and etc…)
  • Used existing databases to further look into the interactions and purposes the deferentially expressed gene have within our bodies

Tools:

R, Python,Jupyter Notebook, Slack, GitHub, EnrichR database, DAVID database, String analysis, Asana, Google Calendar, and Stem-Away forums.

Soft Skills:

  • Learned how to network through the use of LinkedIn, verbal, and written communication
  • Worked in small groups in an online environment
  • Learned to communicate effectively with team mates in order to finalize an interpretation of a concept
  • Worked on presentation skills

Achievements:

  • Contributed to the group effort of understanding bioinformatics
  • Developed skills that facilitate the expression of ideas and acquisition of mentorship within a growing field
  • Developed technical skills such as the use of R code, Python, and R packages
  • Exercised and improved skills pertaining to research and understanding scientific language
  • Honed skills that help communication and team work
  • Learned the methods and structure of gene analysis (ex: quality control, filtering, and etc…)

finalpres.pdf (637.1 KB)
FinalDeliverable -Ernest wang.pdf (279.1 KB)