Week 1 Self-Assessment:
Overview:
Technical Area:
- Installing RStudio, along with packages in R
- Familiarizing myself with basic R fundamentals, such as: coding, debugging, and syntax
- Understanding how to read scientific papers
- Getting a brief understanding of R Shiny and its features
Tools:
- STEM-Away
- RStudio
- R
- R Shiny
Soft Skills:
- Time Management - learning how to efficiently progress through the module, while still being able to get a good grasp of the material.
- Perseverance - Since I had no prior knowledge using RStudio or coding in R, I had to learn to persist in completing the module with the help of STEM-away and my basic coding knowledge.
Achievement Highlights:
- Successfully downloaded R v4.0.0, RStudio, and the two packages needed
- I wad able to learn and practice navigating R.
- Able to get a basic understanding of bioinformatics and reading scientific papers.
- I was successfully able to get a little bit familiar with R Shiny
Difficulties Completing Tasks:
- I had a little bit of trouble using the STEM-away website and locating different pathway hubs, but I eventually was able to get the hang of using this site.
- While trying to download R, I was initially downloading R v4.1.0, as it is the latest version. Eventually, I was able to figure out the issue and download to correct version, R v4.0.0.
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Week 2 Self-Assessment
Overview:
Technical Area:
- Understanding the purposes of the GEO Database
- Learned how to input and manage data in the GEO Database
Tools:
- STEM-Away
- RStudio
- R
- R Shiny
- GEO Database
- Github
- Trello
- Slack
Soft Skills:
- Time Management - Once again, I was able to figure out how to understand the material from the module at a quick pace
- STEM-Away Website - Learning how to use the STEM-Away website for future purposes
- Communication - It took a while, but I was able to organize myself and get familiar with the different communication tools we will be using and what we will use them for
Achievement Highlights:
- I was able to easily download the dataset needed for this week
- Learning how to navigate the GEO Database and Github
- Got more familiar with the STEM-Away website
- Getting comfortable to reach out to the leads for help
Difficulties Completing Tasks:
- I had a little bit of trouble organizing and setting myself up to complete tasks, as I was a little bit unsure about what tasks I needed to complete and how to achieve them.
- At the start, I was confused on how to put data into Rstudio, but after a lot of trouble shooting, I was able to get it loaded
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Week 3 Self-Assessments:
Overview:
Technical Area:
- Installing multiple necessary libraries
- Creating a QC plot with the GSE 19804 dataset
- Using the GSE 19804 Dataset to create a PCA Plot and Correlation Heatmap
Tools:
- RStudio
- R
- R Shiny
- Github
- Trello
- Slack
- Bioconductor website
- Simpleaffy
Soft Skills:
- Time Management - being able to efficiently manage completing all of the tasks, while still
- Perseverance - It took me a very long time to understand how to use the functions needed to complete this weeks tasks, but I was able to achieve goals with perseverance
- Communication - after having some problems with my QC Stats output, I was able to reach out to a team lead to get some advice
Achievement Highlights:
- I was successfully able to create a QC Stats output, correlation heatmap, and a PCA plot
- I was able to understand how, using the outputs created, I could determine potential outliers and identify influential data points
- Understanding the output of the heatmap and how it compares raw and normalized data
Difficulties Completing Tasks:
- I ended up spending a lot of time looking up how to use the different functions needed to graph the plots, but at the end I was successfully able to figure it out
- I had some problems with my QC Stats output, and it took me a long time to figure out how to correct it. With the help of a team lead, I was able to solve the issue.
Week 4 Self-Assessments:
Overview:
Technical Area:
- Installing multiple necessary libraries
- Normalizing data
- Limma Analysis
- Volcano Plot
Tools:
- RStudio
- R
- R Shiny
- Slack
- Websites for research
Soft Skills:
- Time Management - being able to efficiently manage completing all of the tasks
- Presentational Skills - Creating a insightful presentations in a limited amount of time
- Communication - Working with group members to complete shared tasks in a timely manner
- Research Skills - Finding important and relevant information
Achievement Highlights:
- Although it took me longer than expected, I was successfully able to complete all the module tasks
- I was able to take initiation for collaboration and communication among my subgroup
- Contributing to group calls by presenting my ideas and findings.
Difficulties Completing Tasks:
- I had a lot of trouble following the instructions for the module tasks, so I spent a lot of time researching the steps to find more information about the tasks we were completing
Week 5 Self-Assessments:
Overview:
Technical Area:
- Module 5 Tasks such as creating a GSEA plot to understand DEGs, gene ontology using Transcription factor analysis, and KEGG analysis
- Met with Ashlesha and Mark to understand some web based tools for functional analysis (such as EnrichR, David, and Metascape)
Tools:
- RStudio
- R
- R Shiny
- Web based tools (EnrichR, David, and Metascape)
- Slack
- Websites for research
- STEM-away website for resources
Soft Skills:
- Time Management - being able to efficiently manage completing all of the tasks
- Perseverance - It took me a very long time to understand how to use the functions needed to complete this weeks tasks, but I was able to achieve goals with perseverance
- Research Skills - Finding important and relevant information
Achievement Highlights:
- Successfully created a GSEA plot, after a little bit of troubleshooting with my code
- Got a better understanding of R syntax
- Met with team 2 to discuss web based tools we could use for functional analysis
Difficulties Completing Tasks:
- I was struggling with understanding the functional purposes of the web based tools, but after Mark shared a list of basic uses, I was able to do more research and get a better understanding.
- The module took me much longer than expected, with unfortunately left me a bit behind the rest of my teammates, but with their help, I was able to catch up.
Final Bioinformatics Presentation:
Final Bioinformatics STEM-Away Sneha.pdf (318.3 KB)