Etulsian - Bioinformatics Pathway

Certificates June 2020 Certificates Bioinformatics Workflow Self-Assessments
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1
  • Concise overview of things learned
    • Technical Area: I have attended or watched all the R trainings so far. Through which, I have gained a better knowledge of R and the relevant libraries or packages (ggplot to create bar plots, volcano plots, and heat maps to name a few) necessary to better visualize data. Thank you so much Yves! I also attended the python training for people with experience as I have had previous experience with the basics of python. Through that, I got a better understanding on how to use pandas to work with dataframes and numpy. I also learned to how to perform data visualization on python.
    • Tools: better data visualization skills in R and Python
    • Soft Skills: Through the intro team meetings, happy hours, and meetings with Debaleena, I have been able to improve on my communication and get to know my team better. I hope as the project progresses I get to meet and get to know more people not only in my team but also from other teams.
  • Three achievement highlights
    • Attending almost all the meetings even happy hours and if I could not attend I watched the recordings
    • Trying to understand as much as I can from the scientific paper we will be using
    • Communicating and getting to know my team better whether through meetings or LinkedIn
  • List of meetings/ training attended including social team events
    • I have attended all team and training meetings
    • I attended 3 out of the 4 R trainings but I watched the recording of the one I could not attend
    • I attended the happy hours and can’t wait for more!
    • I also attended the two meetings with Debaleena - one just for bioinformatics pathway and the other for all pathways
    • I also attended the Welcome webinar with Stephanie and Katie
  • Goals for the upcoming week
    • My goal is to stay on top of all the assignments and finish them before the deadline, so I can ask any questions if I have any. I also hope to get comfortable with and get better understanding of the first part of the project: data quality control. Another of my goals is to meet more people from my team.
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2
  • Concise overview of things learned
    • Technical Area: Using the knowledge gained from the R trainings and Week 3 Deliverable Tasks documents, I learned how to work with and perform quality control methods on microarray data. I also understood and created my own histograms and PCA to better visualize the data. By creating my own visuals, I also learned how to better interpret them and the importance of normalizing data.
    • Tools: R
    • Soft Skills: I have attended the team meetings and happy hours to meet more of my team members. After splitting up into a smaller group, I worked and communicated with my team regularly, improving my collaboration skills. I have also been networking through LinkedIn.
  • Three achievement highlights
    • I got to know my team member’s better
    • I learned how to interpret the plots (PCA) I produced, which I found a bit difficult initially
    • I made multiple (more than 10) new LinkedIn connections by following people in my area of interest and STEM-away.
  • List of meetings/training attended
    • I attended all 3 of the team meetings
    • I attended the python training
    • I attended the Asana Training and Technical Training
    • I attended our “Family Feud” Happy Hour, which was a lot of fun!!
  • Goals for the upcoming week
    • This week I hope to complete my tasks early and making sure I ask for help whenever I need, and I also want to be available to help my team members with any questions they might have. I will communicate with my team and check Asana and Google Drive to know what tasks are due. I will also continue to network through LinkedIn.
  • Detailed statement of tasks done. State each task, hurdles faced if any and how you solved the hurdle. You need to clearly mark whether the hurdles were solved with the help of training webinars, some help from project leads or significant help from project leads.
    • I completed the 5 steps for the Week 3 deliverables with my team. I followed the guide on the Google Drive. The steps were installing and loading necessary libraries, loading and creating csv of the data, performing quality control, normalizing data, and creating a PCA plot. At each of my small team’s meetings, we would do our own research to understand how to do each task. We would complete the tasks individually, but would have meetings to compare our answers and help each other. I made sure whichever tasks I understood better I would explain to them like how to download the data and creating a csv. We had a bit of trouble when we performed a quality control method on our data as something didn’t seem right, so one of my team members contacted Yves and got us some clarification on our issue. We also had trouble understanding how to analyze the PCA plot, so we used online resources for a better understanding.
    • My team and I submitted the Week 3 deliverables on time. We used online resources from Google Drive and Technical Training to produce the deliverable.
    • Team Communication: I was on a different time zone as compared to other member’s in my group. However, that did not pose as a big problem as we communicated well with each other and were able to have efficient meetings when all of us were available.
    • I completed the R Exercises
    • I joined Slack and Asana.
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3

Self Assessment #3:

  • Concise overview of things learned
    • Technical Area: After understanding the Week 3 Tasks, I gave a presentation about everything that I learned and any challenges or interesting results I found. Using the Week 4 Deliverables document, I understood how to annotate data, gene filter, and analyze volcano plots. I also began working on the Python Problem Set #2. I have also begun to understand GitHub and Asana better.
    • Tools: R, Python, GitHub, Asana
    • Soft Skills: I have continued to attend all of the team meetings and happy hours to meet more of my team members. I even lead the most recent happy hours with a few of my team members. I have continued working and communicating efficiently with my team, allowing us to finish our tasks on time and well. I have also been networking through LinkedIn.
  • Three achievement highlights
    • I lead the most recent happy hours and had fun!
    • I learned how to annotate and filter the data set. Thus, improving my R skills.
    • I responded and helped my team members on the Forum and through email on problems they had while doing Week 4 Deliverables
  • List of meetings/training attended
    • I attended all of the team meetings (2 since last Tuesday)
    • I attended the Python Training #5
    • I attended 2 Fireside Chats (one by Jennifer McLamb and the other by Alex Liang)
    • I lead the last happy hour, where we played Skribbl.io
    • I attended the Technical Webinar held by Ali
    • I attended the R training
    • I attended Office Hours
    • I attended the GitHub Intro Session
  • Goals for the upcoming week
    • This week I will complete my tasks early and attend office hours to get a better understanding of the deliverables. I will continue working well with my team on our deliverables for Week 5. I will continue to check Asana and Google Drive to know what tasks are due. I will also continue to network through LinkedIn. I will set up my GitHub more, so I can submit my deliverables on there.
  • Detailed statement of tasks done. State each task, hurdles faced if any and how you solved the hurdle. You need to clearly mark whether the hurdles were solved with the help of training webinars, some help from project leads or significant help from project leads.
    • For Week 3, my team (Team Enchanted) and Team Hufflepuff presented our findings with the rest of our group. We communicated really well. The biggest hurdle was meeting up together as our timezones and schedules were different, but we made sure to pick a time that worked for most of us.
    • I completed all the tasks for Week 4 Deliverables. First, I had to annotate the normalized data. I changed the rownames to the gene symbols and removed any duplicate or NA data. Then, I filtered out the data. My other team members had a bit trouble in this part, so I walked through my code and answered any questions they had. Next, I analyzed the data using the limma package in R. While analyzing, I realized that the data I was getting was not right. So, asked my team for help and they very patiently explained what they did. I also referenced back to the R trainings to see why my code was not working. After fixing my code, I created multiple volcano plots, analyzing the data at multiple thresholds. I had a bit difficulty analyzing it, so I referenced back to the R trainings and online resources to get a better understanding. My team and I submitted the Week 4 deliverables on time. We used online resources from Google Drive and Technical Training to produce the deliverables.
    • Team Communication: My team continued to communicate efficiently. When working on the presentations, both teams created a GroupMe, so we could communicate well and ask any questions we would have. This also helped in comparing our differentially expressed genes for Week 4 Deliverables.
    • I am working on the Python Problem Set #2 and referenced past Trainings and online resources.
    • I created my own GitHub account.
    • I have begun to use Asana and mark tasks as For Approval.
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4

Self Assessment #4 (7/7):

  • Concise overview of things learned
    • Technical Area: After understanding the Week 4 and Phenotypic Analysis Tasks, I gave a presentation about everything that I learned and any challenges or interesting results. Using the Week 5 Deliverables document, I am understanding how to analyze the data using the Gene Ontology (GO) analysis, KEGG analysis, WikiPathways analysis, and analysis using external tools like EnrichR and STRING.
    • Tools: R, Github, EnrichR, and STRING
    • Soft Skills: I have continued to attend all of the team meetings and happy hours to meet more of my team members. I have continued working and communicating efficiently with my team, allowing us to finish our tasks on time and well. I have also been networking through LinkedIn.
  • Three achievement highlights
    • I understood Week 4 and Phenotypic data tasks and fixed the errors in my code, improving my R skills.
    • I set up GitHub and uploaded my team’s past deliverables and python problem set #2
    • I have attended office hours more frequently to get help in coding and understanding the importance of each Week’s deliverables
  • List of meetings/training attended
    • I attended all of the team meetings (1 since last Tuesday)
    • I attended the Happy Hours where we played skribbl.io and Secret Hitler
    • I attended the meeting with the mentors
    • I attended Office Hours
    • I attended the GitHub Webinar #2
  • Goals for the upcoming week
    • This week I hope to get a better understanding of the deliverables by going to office hours and doing my own research. I will continue working well with my team on our deliverables for Week 5. I will continue to check Asana and Google Drive to know what tasks are due. I will also continue to network through LinkedIn.
  • Detailed statement of tasks done. State each task, hurdles faced if any and how you solved the hurdle. You need to clearly mark whether the hurdles were solved with the help of training webinars, some help from project leads or significant help from project leads.
    • For Phenotypic Data Analysis, I had to get the series matrix file from GEO and obtain the phenodata. We then added the phenodata to the expressionSet that had outliers removed and was normalized.
    • For Week 4 Deliverables and Phenotypic Data Analysis, my team (Team Enchanted) and Team Abracadabra presented our findings with the rest of our group. We communicated really well. The biggest hurdle was meeting up together as our timezones and schedules were different, but we made sure to pick a time that worked for most of us. Both teams also worked together to complete the Phenotypic Data Analysis.
    • I am working on the tasks for Week 5 Deliverables. My team has met once to start the deliverables and will meet again soon to compare our results.
    • Team Communication: My team continued to communicate efficiently. When working on the presentations, both teams created a groupchat, so we could communicate well and ask any questions we would have.
    • I have begun to use Asana and mark tasks as For Approval.
    • I have imported previous deliverable files and my Python Problem Set #2 to GitHub.
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5

Self Assessment #5 (7/14)

  • Concise overview of things learned:
    • Technical Area: I finished the Week 5 Deliverables, where I performed Gene Ontology analysis, KEGG analysis, WikiPathways analysis, EnrichR analysis, and STRING analysis. After finishing up and turning in the Week 5 deliverables, I continued to explore the STRING tool to better understand the analysis. I gave a presentation about Week 5 Deliverables and challenges/interesting results.
    • Tools: R Studio, R, GitHub, EnrichR, and STRING
    • Soft Skills: I have continued to attend all of the team meetings and happy hours to keep in touch with team members. I have continued working and communicating efficiently with my team, allowing us to finish our tasks on time and well.
  • Three achievement highlights
    • I completed the Week 5 Deliverables and went back to parts I did not understand well.
    • I continued to communicate efficiently with my team and Team Ravenclaw for our deliverables and presentation
    • I attended office hours to better understand the technical side that is not coding
  • List of meetings/training attended
    • The BI team meetings (last week on Wednesday and yesterday)
    • Python training #6
    • Happy hour (last week on Friday)
  • Goals for the upcoming week
    • This week I hope to get a better understanding of bioinformatics as a whole through the individual deliverables for Week 7/8. I will try to go to office hours and do my own research. I will continue to check Asana and Google Drive to know what tasks are due. I will also continue to network through LinkedIn.
  • Detailed statement of tasks done.
    • For Week 5 Deliverables, I performed Gene Ontology (GO) analysis, enriched GO analysis, KEGG analysis, and WikiPathways analysis. I also used external tools such as EnrichR and STRING. Through the resources the project leads shared, I got a better understanding of the code and each method shown. I also performed my own research to understand why we were performing these analyses. I had a bit of a challenge with R as clusterProfiler would not work, but I looked up online and tried to change how I was downloading the package. I also ran into some issues while performing WikiPathways analysis, but I went to office hours and asked some team members for help. Fortunately, I was able to complete all the task necessary.
    • For the team presentations, my team (Team Enchanted) worked with Team Ravenclaw to present our Week 5 findings. The biggest hurdle was comparing our findings as we had differing results. To combat this issue, we each shared our code and results, so we were able to compare our answers and determined that the error might be because we used different normalization methods and set different thresholds. Otherwise, we all worked very well together.
    • Team Communication: My team continued to communicate efficiently. When working on the presentations, both teams created a groupchat, so we could communicate well and ask any questions we would have.
    • I uploaded all Week 5 Deliverables to GitHub
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6

Self Assessment #6 (7/21)

  • Concise overview of things learned:
    • Technical Area: I worked on the Week 7/8 Deliverables, where I applied everything I learned to a new GEO set: GSE21510. I also analyzed the paper.
    • Tools: R Studio and R
    • Soft Skills: I have continued to attend all of the team meetings to keep in touch with team members. I have continued working and communicating efficiently with my team, allowing us to finish our tasks on time and well.
  • Three achievement highlights
    • I applied everything I learned to GSE21510 to complete the deliverables.
    • I continued to communicate efficiently with my team
    • I managed to complete my deliverables while also leading the Vaping Detection & Mitigation team.
  • List of meetings/training attended
    • The BI team meetings (last week on Thursday and today)
  • Goals for the upcoming week
    • This week I hope to get a better understanding of bioinformatics as a whole through the individual deliverables for Week 7/8. I hope to deliver an effective presentation for leads and mentors. I will also continue to network through LinkedIn.
  • Detailed statement of tasks done.
    • For Week 7/8 Deliverables, I performed quality control metrics like array quality metrics and affy qc report to figure out the outliers in GSE21510. I then normalized the data using mas5. I also annotated, performed gene filtering, and performed LIMMA analysis on the data. I made plots similar to the ones shown in the paper like the volcano plot and heatmap. I then performed enriched GO analysis to understand which gene ontology terms were more expressed. Aside from the coding, I analyzed the paper and the similarities and differences between what I had learned and methods used in the paper. I had a bit of a challenge with R as my heatmap was not coming out like the paper, but my team members helped me understand how they go it to work.
    • Team Communication: My team continued to communicate efficiently. Even though we didn’t need to work together, we decided to work together on the deliverables, so we all can get a better understanding of the deliverables and compare our answers.
7

Final Self Assessment (7/24)

  • Concise overview of things learned:
    • Technical Area: Through analyzing the paper and attending the technical webinars, I have learned a lot about the bioinformatics field. Additionally, through the R trainings, I have gotten a better understanding of R applications in bioinformatics. I came in with very minimal experience using R, but I have truly learned a lot. Throughout the internship, I learned about bioinformatics project pipeline and how to analyze microarray data.
    • Tools: R, R studio, Zoom, Google Meet, Slack, Asana, GitHub, STEM-Away forums, STRING, EnrichR
    • Soft Skills: I learned how to develop present myself in an effective manner in front of leads and mentors. I went to all team bonding meetings to get to know my team members better. I have also improved my networking in LinkedIn. I am very fortunate to have had such a wonderful deliverables group, who I was able to meet regularly and finish tasks together.
  • Three achievement highlights
    • I am really proud of everything I have learned in Bioinformatics and R. I came in with very limited experience in both, but I am leaving with a better understanding in both. I completed all the deliverables and went to all the meetings to improve my learning.
    • STEM-Away really emphasized soft skills and networking. I am proud of my improvement in my networking skills. I did not have a LinkedIn before this internship, but, once I did, I started making multiple connections and tried reaching out to people I didn’t know. I still have a lot to improve on my networking, but I am really proud of how much I have begun to get out of my comfort zone.
    • Finally, I am really proud of my improvement in teamwork and leadership skills. Getting to know my teammates and leads whether in team meetings or in happy hours was really nice. I am proud how I made an effort to meet people and would be the one to reach out to others if I needed help or wanted to work on the team presentations together. I used the forum frequently whether to ask questions or to help others in my team with their questions. I am so glad to have gotten to know such nice group of people!
  • List of meetings/training attended
    • I attended most of the meetings for this internship and watched the recordings for any I had missed. I attended all the happy hours and got to know my team better.
  • Goals for the upcoming week
    • I will reflect on the information I have learned!
  • Detailed statement of tasks done.
    • I learned how to analyze microarray data. First, I got the datasets and performed quality control methods to remove outliers. I then normalized the data. I annotated the data to get gene symbols, filtered the genes, and performed LIMMA analysis. Then, I performed phenotypic analysis to get the metadata. Finally, I performed multiple analyses like GO, KEGG, Wikipathways, EnrichR, and STRING to analyze the data. For Week 7/8 deliverables, I followed a similar pipeline for another microarray dataset. I read the paper and compared the two pipelines. I improved my analysis skills to better interpret the graphs the paper had as well as my own plots I made. Throughout this internship, I am able to see how interdisciplinary bioinformatics truly is!

Final presentation: EshaTulsian_Week7_8Deliverables.pdf (2.6 MB)

Thank you so much @egunduz, @Isha, and @yvesgaetan for such a wonderful experience!

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