Durberg7 - Bioinformatics Pathway

WEEK 2

Things I Learned
Technical Area

  • microarrays and RNA sequencing
  • PPI networks and KEGG pathway maps and analysis
  • volcano plots in R
  • refreshed R and Python skills

Tools

  • GEO database
  • Asana

Soft Skills

  • communication on StemAway platform, Slack, and Zoom

Achievement Highlights

  1. After reading the paper and attending meetings, I have a better understanding of the methods and data used.
  2. Complete R and Python exercises successfully
  3. Contacted subgroup to begin working on this week’s tasks

Meetings/ Trainings Attended

  • Logistic Webinar (10 June)
  • Technical Training (10 June)
  • Gene Team Meeting (11 June)
  • Welcome Session by Debaleena (12 June)
  • The Gene Team Happy Hour (12 June)
  • Asana Training (16 June)

Goals for Week of 15 June

  • complete the deliverables for next Monday
  • completely catch up with the webinars and trianings I have missed

Tasks Done

  • read/understood/analyzed research paper - it was challenging understanding some of the biological implications/ processes at first but the technical webinar (10 June) and the notes from the previous webinars helped clarify my understanding
  • all python and R trainings - no issues were encountered

WEEK 3

Things I Learned
Technical Area

  • object-oriented programming in Python
  • how to use .CEL files in R
  • gcrma normalization method
  • analysis of QC plot produced by simpleaffy
  • analysis of NUSE and RLE results from affyPLM
  • PCA in R

Tools

  • R bioconductor packages (simpleaffy, affyPLM, gcrma)
  • more in-depth Asana
  • Python pandas library

Soft Skills

  • LinkedIn (connecting, messaging, commenting, etc.)
  • cultural diversity in the workplace

Achievement Highlights

  1. Completed all Week 3 deliverables on time.
  2. Successfully troubleshooted teammates code and understood technical reasons behind errors.
  3. Connected with Stem-Away people and people of interest on LinkedIn

Meetings/ Trainings Attended

  • Asana Training (16 June)
  • Python and Pandas Webinar (16 June)
  • Technical Training (17 June)
  • Gene Team Meeting (18 June)

Goals for Week of 22 June

  • complete the deliverables for next Monday
  • meet with teammates (and another team) to discuss results before next Monday

Tasks Done

  • completed Week 3 deliverables and met with teammates to discuss results - ran into some unavoidable issues with not having enough RAM to do gcrma normalization
  • signed up for Asana - some connection issues were resolved by leads
  • connected with people of interest on LinkedIn

WEEK 4

Things I Learned
Technical Area

  • heatmaps in R
  • more about microarrays
  • annotating gene expression data
  • analyzing gene expression data in R (limma)

Tools

  • R bioconductor packages (limma)
  • R package (pheatmap)
  • GitHub

Soft Skills

  • presentation skills
  • tips for starting your “first day” at a job

Achievement Highlights

  1. Completed all Week 4 deliverables on time.
  2. Successfully troubleshooted teammates and my code and understood technical reasons behind errors.
  3. Obtained a better understanding of gene differential expression and analysis.

Meetings/ Trainings Attended

  • Gene Team Meeting (22 June)
  • Fireside Chat #1 (24 June)
  • GitHub Training (25 June)
  • Webinar for Bioinformatics (25 June)
  • Gene Team Meeting (25 June)
  • R Training (26 June)
  • Office Hours BI (26 June)

Goals for Week of 29 June

  • complete the deliverables for next Monday
  • complete the phenotype deliverables for Wednesday
  • meet with group 2 and 7 to prepare presentation for Thursday

Tasks Done

  • completed Week 4 deliverables and met with teammates to discuss results - teammates and I ran initially had different results, but we figured out our issues in our team meeting
  • signed up for Asana
  • provided GitHub username

WEEK 5

Things I Learned
Technical Area

  • how to extract phenotypic data from the GEO database
  • learned more about limma analysis from the mentors
  • gene ontology analysis
  • KEGG pathway analysis
  • wikiPathway analysis

Tools

  • R packages: GEOquery, topGO, cluserProfiler, and pathview
  • DAVID functional annotation tool for bioinformatics

Soft Skills

  • worked on presentation skills in office hours

Achievement Highlights

  1. Completed Python Exercises # 2
  2. Completed phenotypic data tasks
  3. Completed Week 5 Deliverables in R (still working on DAVID analysis)

Meetings/ Trainings Attended

  • GT Meeting (29 June)
  • GitHub Webinar (1 July)
  • GT Meeting (2 July)

Goals for Week of 6 July

  • complete DAVID analysis
  • prepare presentation for next week

Tasks Done

  • phenotypic data tasks - struggled to understand recommended line of code, but figured out it was a combination of two different methods and with help from Yves post
  • Python 2 exercises - struggled with Problem 8, the palindromic pyramid, but figured out a solution thanks to Goral, a technical lead
  • presentation for Thursday - struggled with coming up with a project hypothesis due to vague instructions, but Annie, a technical lead, was able to clarify at the end of the meeting
  • week 5 deliverables - still running into some inconsistencies in results with my teammates, but we are planning to troubleshoot these later today

WEEK 6

Things I Learned
Technical Area

  • learned how to interpret DAVID results
  • learned more about gene ontology and its importance
  • learned how to view related KEGG pathways in DAVID and interpret them

Tools

  • DAVID functional annotation tool for bioinformatics
  • STRING PPI database

Soft Skills

  • worked on elevator pitches
  • obtained better understanding of how to construct a resume

Achievement Highlights

  1. Completed DAVID analysis and interpretation from week 5 deliverables
  2. Prepared week 5 deliverables presentation for Monday
  3. Successfully led office hours for July session

Meetings/ Trainings Attended

  • GT Meeting (6 July)
  • My office hours (6,13 July)
  • BI Office Hours (7 July)
  • GT Meeting (8 July)
  • Python Training (9 July)
  • Leadership Training (10 July)

Goals for Week of 13 July

  • complete final deliverables for June
  • begin working on deliverables for July
  • prepare for July session

Tasks Done

  • DAVID analysis and interpretation for functional analysis
  • STRING PPI analysis
    *both these tasks/tools were fairly straightforward and had good manuals to help with interpretation
  • successfully held office hours for July session

WEEK 7

Things I Learned
This week, I didn’t really learn anything new in terms of technical skills and tools, but I became more confident in the skills that I have learned in previous weeks while preparing for the final presentation.

Soft Skills

  • practiced divergent thinking
  • learned more about presentation skills and will get to apply them in the final presentation

Achievement Highlights

  1. Successfully implemented the pipeline learned in previous weeks to a new dataset
  2. Prepared final presentation
  3. Started the July session as a lead - still working out some kinks, but overall it started pretty well

Meetings/ Trainings Attended

  • GT Meeting (13 July)
  • GT Meeting (15 July)
  • GT Meeting (21 July)
  • Happy Hour (22 July)

Goals for Week of 20 July

  • give a good presentation tomorrow
  • work out the kinks in the July session

Tasks Done

  • pipeline implementation with a new data set
  • presentation preparation

FINAL ASSESSMENT

Things I Learned
Technical Skills

  • microarray data collection and interpretation
  • PPI network and KEGG pathway maps and analysis
  • visualizations methods and interpretation: PCA, heatmaps, volcano plots, dotplots
  • GCRMA normalization
  • QC plot (simpleaffy) production and analysis
  • NUSE and RLE calculations and analysis
  • gene expression data annotation and filtering
  • differential expression gene (DEG) analysis
  • functional analysis (externally and in R)

Tools Skills

  • GEO database
  • various Bioconductor R packages
  • python programming
  • collaboration channel communication: STEM-Away forums, Asana, GitHub, Slack
  • External functional analysis: DAVID, STRING

Soft Skills

  • networking on Linkedin
  • cultural diversity in the workplace
  • presentation skills
  • elevator pitches
  • resume and CV construction tips and best practices
  • creativity and divergent thinking
  • communicating virtually across different time zones

Achievement Highlights

  1. Completed the June session with a deeper understanding of bioinformatics techniques, analysis methods, and tools used in researching genomics and transcriptomics

  2. Debugged and helped teammates troubleshoot programming errors thus improving my own confidence in programming and teaching others.

  3. Refined teamwork and collaboration skills especially when working across different time zones.

Final Word/ Goals for Future
I’ve really enjoyed my time as a participant in the Gene Team and getting to know everyone. Everyone I worked with was very passionate and dedicated in learning and making sure everyone understood what was going on. The leads, especially, were very helpful in troubleshooting and clarifying objectives. What I liked the most was being able to work in smaller groups and really get to know the people I was working with. I liked having smaller subgroups and then combining with another subgroup for presentations. I think getting to know a few people at a time was helpful in developing a sense of community within the larger team.

In the immediate future, I’ll be a lead for the BI pathway’s July session. This internship has definitely gotten me excited about Bioinformatics and, in the distant future, I’m thinking of pursuing the topic in higher education (grad school).

AnyaGreenberg_FinalPres.pptx (757.8 KB)