ChloeLi - Bioinformatics Pathway

Self assessment for week 6/7 - 6/13

Things learned:

  • Technical area: I learned the main idea of the CRC paper and picked up some related biology or genetics concepts. I also learned basic Python and enhanced my R skills that could be used toward the project.

  • Tools: R, Python, GEO database, Google Suite.

  • Soft skills: I learned a lot of useful virtual meeting etiquette from the logistic meeting. I also practiced communication skills with people that I never met before when the new team was formed and when we discussed the paper in breakout rooms. I got to know the functions of GSuite and the STEM-Away forum in more detail and can now use them wisely to manage notifications, calendars, etc.

Achievement highlights:

  • Re-familiarized myself with R and learned a lot more in-depth functions.

  • Learned Python quite quickly by transferring my Java knowledge.

  • Researched and studied the biological concepts behind the paper.

List of training and meetings attended:
6/1 technical webinar, 6/1 team meeting, 6/2 R training, 6/3 technical webinar, 6/5 R training, 6/6 Python training, 6/8 team meeting, 6/9 R training, 6/9 Python training, 6/10 logistic meeting, 6/10 technical webinar, 6/11 team meeting, 6/12 welcome session, 6/12 R training.

Tasks completed:
Completed all the R and Python training related exercises. Read and tried to understand the paper as well as studying the data that will be used for the project.

Goals for the upcoming week:
Continue to learn about the biology and techniques used behind the paper. Get started on quality control assessment of the data that we will be using for the project. Sharpen my R and Python skills and use them toward the project.

Switch of roles:
I would like to switch from an observer to a participant since I was enrolled in the July session as a participant and that is being pushed out.

Self assessment for week 6/14 - 6/20

Things learned:

  • Technical area: I learned how to use various packages and functions in R to examine the quality of set of microarray data. I also learned to interpret different kinds of QC plots generated by these functions and identify outliers in the dataset.
  • Tools: I practiced using RStudio in a lot more depth, learned about and signed up for Asana, and also tried out some more features of Slack.
  • Soft skills: I took the lead in reaching out to my teammates when forming subgroups, settling communication tools, and arranging team meetings. This experience reminded me the many detail I need to take care of when leading team communications, including always specifying the time zone and being aware of everyone’s role in the team.

Achievement highlights:

  • Took initiative to contact teammates and streamline the communication.
  • Understood the QC report for microarray data in more depth by reading the documentation.
  • Utilized many R commands learned in the past week in the tasks.

List of training and meetings attended:
6/15 team meeting, 6/16 Asana training, 6/16 Python webinar, 6/17 technical webinar, 6/18 team meeting, 6/18 sub-team meeting.

Tasks completed:
Completed all the assigned deliverables (including data loading, quality control, background correction and normalization, and visualization) with teammates and integrated the results into one document.

Goals for the upcoming week:

  • Compare our results with another team and give a presentation on the next team meeting.

  • Further familiarize myself with R/Python and the project pipeline by following this week’s deliverables.

  • Start using Asana for project management and progress tracking.

  • Continue to learn the fundamentals of bioinformatics by attending webinars and self-education.

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Self assessment for week 6/21 - 6/27

Things learned:

  • Technical area: I took a lead in starting working on the tasks in my group. I learned how to annotate the gene expression data with the respective metadata in R and how to perform differential gene expression analysis with the limma package. I also familiarized myself with the different tools to visualize a dataset in Python.
  • Tools: R, Python, Github, RStudio, Jupyter Notebook, Anaconda, GEO database, Slack, Asana, Google Suite.
  • Soft skills: I practiced the proper etiquette in virtual meetings and I took the chances to ask questions. I actively participated in the discussion with the other group for comparing our results and working on the presentation. I helped answer my teammates’ questions and clarify their confusions whenever I could.

Achievement highlights:

  • Gained a better understanding of differential gene expression analysis and applied the principals and tools toward analyzing our assigned dataset.
  • Became more comfortable contributing and asking questions in training, office hours, group meetings and team meetings.
  • I was the first one to start and complete all the tasks assigned in my group.

List of training and meetings attended:
6/22 team meeting, 6/23 Python training, 6/24 group meeting, 6/24 fireside chat, 6/25 Github training, 6/25 microarray training, 6/25 team meeting, 6/25 R training.

Tasks completed:

  • Completed all the assigned deliverables (including annotation, gene filtering, differential gene expression analysis, and volcano plot) on my own.

  • Compared my results with my teammates, and integrated the results into one document for submission.

  • Complete the second set of Python exercises.

  • Started to follow hashtags and making new connections on LinkedIn.

Goals for the upcoming week:

  • Communicate more frequently and efficiently with my teammates.
  • Have a more thorough understanding of all the steps we are taking for the project.
  • Start thinking creatively and critically about the potential sources of error and flaws in the project.
  • Focus more on soft-skill development.

Self assessment for week 6/28 - 7/4

Things learned:

  • Technical area: I practiced to use various R packages including clusterProfiler, topGO and pathview and their various functions to conduct gene ontology analysis and pathway analysis. I learned to analyze the different graphs produced in these analysis and extract meaning out of them. I also practiced using Github in submitting my assignment using my own personal branch and creating pull requests.
  • Tools: R, Python, Github, RStudio, Slack, Asana, Google Suite.
  • Soft skills: I took the lead to communicate and arrange meeting times with the other group that we were presenting with. I passed on information from the meeting to my teammates who were not able to make the meeting. I actively asked questions on our group Slack channel and on the forum as well.

Achievement highlights:

  • Took initiative to contact team members and arrange the time for discussion.
  • Turned to the leads and mentors when I had questions about the process and coding, which greatly speeded up my deliverables completion.
  • Compared and contrasted our results with another group, found differences and came up with hypotheses to explain them.

List of training and meetings attended:
6/29 group meeting, 6/29 team meeting, 6/29 Python training, 6/30 fireside chat, 7/1 Github training, 7/1 group meeting, 7/2 team meeting.

Tasks completed:

  • Completed the first 4 sections of the assigned deliverables (including preparing the packages, gene ontology analysis, KEGG analysis and WikiPathways analysis) on my own and still working on the next 2 sections.
  • Compared our results for last week with two other groups and put together a presentation.
  • Submitted all deliverables and exercises on Google Drive and Github.

Goals for the upcoming week:

  • Complete the week 5 deliverables by researching and reading the documentation of the functions used.
  • Study and reflect on the paper and the project pipeline.
  • Getting to know more participants in STEM-Away.

Self assessment for week 7/5 - 7/11

Things learned:

  • Technical area: I learned to perform WikiPathways analysis in R, specifically using the enricher() and GSEA() functions. I also explored various external tools for pathway analysis and protein-protein interactions such as DAVID and STRING, and read the instructions in order to understand and interpret the plethora of outputs correctly. I became more familiar with Github by submitting the assignments on time.
  • Tools: R, DAVID, STRING, Github, RStudio, Slack, Asana, Google Suite.
  • Soft skills: I responded promptly when other team members proposed for a meeting and then took the responsibility to survey everyone’s availability and set up the meeting over Zoom. As a representative, I explained to the other group we were working with what our group did and when different results arise, I was able to look at our code and resolve one group’s error by really understanding how the functions work

Achievement highlights:

  • Completed the deliverables on time in the difficult situation where only me and another participant remained in the group after the 5-week session ends.
  • Researched independently to understand the external tools used for function analysis, and troubleshot on the forum when I have additional questions.
  • Compared results with another group and was able to resolve the differences found on our own.

List of training and meetings attended:
7/6 team meeting with mentors, 7/8 team meeting, 7/9 Python training, 7/11 group meeting.

Tasks completed:

  • Completed the last 2 sections of the assigned deliverables (including using external tools DAVID and STRING to perform functional analysis) on my own.

  • Compared our functional analysis results with another group and put together a presentation detailing our findings.

  • Put the weekly results in the context of the overall pipeline and understood their significance, as well as compared our results and pipeline to those of the original paper.

  • Submitted all deliverables on Github.

Goals for the upcoming week:

  • Start looking at the new papers and design my own pipeline for the final project.
  • Complete the Python exercises and start working on the independent project.
  • Be more engaged with the July session and research about the unfamiliar parts of the new project.

Self assessment for week 7/12 - 7/18

Things learned:

  • Technical area: I revised the major functions used for the entire project when doing my individual project. I also looked into the other functions that our group was not assigned, such as mas5() and affyPLM() to have a more comprehensive review of the new data. I gained a better understanding of the original paper by applying what I have learned and practiced throughout the internship.
  • Tools: R, Github, RStudio, Slack, Google Suite.
  • Soft skills: I learned many effective presentation skills during our team meeting. Applying these skills, I put together a presentation about my independent project and will be presenting to the leads and mentors.

Achievement highlights:

  • Completed the independent project relatively smoothly by reviewing what I learned in the past few weeks.
  • Reviewed the original paper and understood much more of it.
  • Put together a presentation about my independent project and the internship experience.

List of training and meetings attended:
7/13 team meeting, 7/15 team meeting.

Tasks completed:

  • Completed the independent project using skills learned during the internship, including making heatmaps, volcano plots and performing functional analysis.
  • Compared my results to those of the paper and analyzed potential sources of error.
  • Put together a presentation about the project and my reflections of the internship experience.
  • Submitted the project and presentation on Github.

Goals for the upcoming week:

  • Complete the independent project presentation to the best of my ability.
  • Devote myself to the July session.

Final self assessment

Things learned:

Technical area:

  • Fundamental principles and procedures of microarray sequencing

  • Performing literature review

  • Accessing the GEO website to download data and metadata

  • Performing quality control of microarray data in R (affyQCReport, simpleAffy, affyPLM)

  • Normalizing microarray data (mas5, rma) and visualizing the data (PCA plot, volcano plot, heatmap)

  • Annotating and filtering the genes

  • Differential gene expression analysis using the limma package

  • Performing functional analysis including gene ontology enrichment, KEGG pathway analysis, WikiPathways analysis, and protein-protein interaction network construction

  • Basic data analysis and visualization in Python

  • Submitting the deliverables and code via GitHub


  • Google Suite, STEM-Away forum, Slack, Asana

  • RStudio, Anaconda, Jupiter Notebook, GitHub

  • GEO database, DAVID, STRING

Soft skills:

  • Taking initiative to connect with team members and arrange meetings

  • Proper etiquette in virtual meetings

  • Managing meetings using Google Suite

  • Presentation, networking and resume building skills

  • Keeping a lively atmosphere in virtual meetings

Achievement highlights:

  1. I was able to follow and eventually fully understand the whole project pipeline without any bioinformatics background.

  2. I took initiative in contacting team members, arranging meetings, completing the weekly deliverables and putting together the submission document.

  3. I presented our results with another team every week, and had an independent presentation for my final project to the leads and mentors.

Tasks completed:
I completed every set of deliverables and R/Python exercises, and I actively asked questions on the forum and during training/office hours.

Final presentation:
ChloeLi_FinalPres.pdf (1.4 MB)

Final remarks:
I really enjoyed the past 8 weeks, where I was able to learn about the exciting field of bioinformatics and connect with many passionate peers. Thank you all the leads and mentors who have been arranging all the training, meetings and webinars, as well as actively responding to our questions on the forum/Slack. You have done an amazing job and we couldn’t have learned so much without your hard work! Hope you all the best!