- Concise overview of things learned
- Technical Area: I have learned a lot about R from the training sessions with Yves (thank you!). I learned the basics of how to use R Studio including defining variables, importing data, and installing and utilizing packages. We’ve also discussed how R can be used in bioinformatics to visualize and analyze gene expression by creating scatter plots, volcano plots, heat maps, etc. I also attended the Python training session for people with some experience as I have used it before and gained a better understanding of how to use pandas to work with data and seaborn to create plots as well as how object-oriented programming works in Python.
- Tools: R programming language, R Studio, and data visualization in Python
- Soft Skills: By attending team meetings and happy hours, I have gotten the chance to practice communicating and working with a team. I also learned some tips on professional etiquette from Debaleena and how to customize notifications to improve efficiency.
- Three achievement highlights
- Attended or watched all of the R trainings and learned how to use R, a program I’ve always wanted to learn but never have.
- Communicated with my team members and connected with some of them on LinkedIn.
- Read through the scientific paper to learn more about a practical application of R in bioinformatics.
- List of meetings/ training attended including social team events
- I attended or watched all team meetings and training meetings except for today’s
- I attended 2 R trainings and watched the recordings for the ones missed.
- I attended the Python session for those with some experience.
- I attended the second happy hour (painting session) and am looking forward to more!
- I attended the bioinformatics meeting with Debaleena
- Goals for the upcoming week
- My goal is to review all the material we’ve covered so far since a lot of it is new to me and try to work on more exercises to get more comfortable working with R. I also want to get started on the first R assignment early and try to attend office hours to get help. I also want to get to know my teammates better and attend happy hour again this week.
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7/3:
- Concise overview of things learned
- Technical Area: I have gained knowledge in working with gene expression data retrieved from the GEO database and utilizing the Bioconductor packages in R to analyze the data. In Week 3, I learned how to perform several different analysis steps in R including quality control (assessing RNA degradation, hybridization, and spike-in), data preprocessing (background correction and normalization), and principle component analysis to visualize the distinction between healthy and cancerous samples and identify outliers in the data. In Week 4, I learned how to use Bioconductor packages to annotate samples, filter genes, analyze gene expression, and create a volcano plot.
- Tools: Bioconductor, GEO, GEO2R, GitHub
- Soft Skills: While working on the weekly deliverables, I had the chance to work on my teamwork and communication skills by asking my teammates and other teams questions and collaborating on the report. I also strengthened my presentation skills since we had to present and explain our findings.
- Three achievement highlights
- I learned how to use several of the Bioconductor packages and functions.
- Yves told us that our team was one of the top two teams in Week 3.
- Connected with more of my team members on LinkedIn.
- List of meetings/ training attended including social team events
- I attended most team meetings and most R meetings (watched recordings for those I missed). I also attended two Python training sessions and training sessions for Asana and GitHub. I also attended one of the happy hours.
- Goals for the upcoming week
- I am leaving after this week, but my goal is to still help my team work on the Week 5 deliverables as needed and keep learning more about R.
- 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.
- In Week 3, I performed the quality control using affyQCReport and rma() for normalization with the help of the deliverable instructions. Yves’ training webinar helped with creating the PCA plot.
- In Week 4, I performed the sample annotation and gene filtering steps with the help of training webinars. The project leads better explained the thresholds question in the forums. Our team’s volcano plot was wrong the first time, but after comparing results with another team and using a resource they recommended (GEO2R), we were able to correct our code.
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Overall Self-Assessment:
- Concise overview of things learned
- Technical Area: Throughout this internship, I went from having never used to R to learning the basics of R Studio (defining variables, importing data, and installing packages) and visualizing data with scatter plots, volcano plots, and heat maps. I have also gained more advanced knowledge in working with gene expression data retrieved from the GEO database and utilizing the Bioconductor packages in R to analyze the data. In Week 3, I learned how to perform several different analysis steps in R including quality control (assessing RNA degradation, hybridization, and spike-in), data preprocessing (background correction and normalization), and principle component analysis to visualize the distinction between healthy and cancerous samples and identify outliers in the data. In Week 4, I learned how to use Bioconductor packages such as limma to annotate samples, filter genes, analyze gene expression, and create a volcano plot.
- Tools: R, R Studio, Python, Bioconductor, GEO, GEO2R, GitHub, Asana
- Soft Skills: While working on the weekly deliverables, I had the chance to work on my teamwork and communication skills by asking my teammates and other teams questions and collaborating on the report. I also strengthened my presentation skills since we had to present and explain our findings. I also practiced networking by connecting with my teammates on LinkedIn.
- Three achievement highlights
- I learned how to use R and several of the Bioconductor packages and functions for gene expression visualization and analysis.
- Yves told us that our team was one of the top two teams in Week 3.
- Gained a stronger understanding of the field of bioinformatics.
- List of meetings/ training attended including social team events
- I attended most team meetings and most R trainings (watched recordings for those I missed).
- I attended the Python training sessions for those with previous experience.
- I attended the second happy hour (painting session).
- I attended the Asana and GitHub training sessions.
- Goals for the upcoming week
- I am leaving after this week, but my goal is to use the knowledge I’ve gained and apply it in a bioinformatics position. I hope to apply to more bioinformatics jobs in the future and talk about my experience with STEM-Away. I also intend to keep in touch with all my new LinkedIn connections!
- 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.
- In Week 3, I performed the quality control using affyQCReport and rma() for normalization with the help of the deliverable instructions. Yves’ training webinar helped with creating the PCA plot.
- In Week 4, I performed the sample annotation and gene filtering steps with the help of training webinars. The project leads better explained the thresholds question in the forums. Our team’s volcano plot was wrong the first time, but after comparing results with another team and using a resource they recommended (GEO2R), we were able to correct our code.
- I performed the phenotypic analysis. Since I had trouble following the leads’ instructions and working with the data in Excel, I removed non-relevant columns within R itself.
Thank you to the incredible project leads for working hard to help us and making the experience enjoyable. I learned so much from this internship and am thankful I had the opportunity to not only learn about using R in bioinformatics, but apply that knowledge to practical problems.
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