Tanish Kumar - Bioinformatics - Self Assessment

Things Learned:

  • Technical Area - Learned how to generate and Affy QC Report, Learned how to create boxplots of raw and normalized data, Learned how to use ComBat to perform Batch Correction, Learned how to use prcomp() to generate PCA Plots of raw, normalized, and batch corrected data, Learned how to create Heat Maps using pheatmap(),
  • Tools - RStudio, Stem-Away Platform(Discourse), GSuite tools(Gmail, Drive, Calendar, etc.), Slack
  • Soft Skills - The importance of networking, Setting up Group Chats, Collaborating with a team in an online environment, Creating and giving a presentation in an online environment

Achievement Highlights:

  1. Was able to complete all of the deliverables on time.
  2. Was able to work with my team and present our deliverables
  3. Became Task Lead for this week

List of meetings/trainings attended:

  • Week 1 - 7/20: Team Meeting, 7/28: Team Presentation Meeting,

Goals for upcoming week

  • Make sure to complete DEG analysis deliverables on time.
  • Work with my team to troubleshoot and present.

Tasks Completed

  • Used ReadAffy() to read in datasets GSE 32323 and GSE 8671
  • Used rma() to normalize data
  • Used QCReport() for quality control
  • Used prcomp() to generate all three PCA Plots
  • Used pheatmap to generate the two heat maps
  • Used ComBat to perform batch correction

Things Learned:

  • Technical Area - Learned how to use collapseRows(), Learned about how to create a proper Contrast Matrix, Learned how to create a Heat Map of the expression values of highly differentially expressed genes in each sample,
  • Tools - RStudio, Stem-Away Platform(Discourse), GSuite tools(Gmail, Drive, Calendar, etc.), Slack
  • Soft Skills - Learned how to be culturally aware and competent,

Achievement Highlights:

  1. Was able to complete all of the deliverables on time.
  2. Was able to work with my team and present our deliverables
  3. I learned a few new things and was able to use the things I learned last session to help me complete the deliverables for this session

List of meetings/trainings attended:

  • Week 5 - 8/3: Team Meeting, 8/4: Team Meeting,

Goals for upcoming week

  • Make sure to complete deliverables on time and create a presentation with my team.
  • Understand what I am doing when coding for these deliverables especially on the biological side.

Tasks Completed

  • Used select() and collapseRows() to annotate the genes
  • Used na.omit() and completed Gene Filtering
  • Used model.matrix() to find highly differentially expressed genes.
  • Used EnhancedVolcano() to generate volcano plot.
  • Used pheatmap to generate the one heat map based on gene expression values.

Things Learned:

  • Technical Area - Learned how to use cnetplot(), Learned how to use MSigDB - GSEA, Learned how to use the msdigdbr package,
  • Tools - RStudio, Stem-Away Platform(Discourse), GSuite tools(Gmail, Drive, Calendar, etc.), Slack, GitHub, Spacetime.am,
  • Soft Skills - How to work with a team in an online environment, How to troubleshoot in an online environment

Achievement Highlights:

  1. Was able to complete half of the deliverables without too much trouble
  2. Was able to work with teammates to troubleshoot and clarify deliverables
  3. Was able to understand what I was doing from a biological perspective

List of meetings/trainings attended:

  • Week 6 - 8/10: Team Meeting

Goals for upcoming week

  • Make sure to complete deliverables on time and create a presentation with my team.
  • Understand what I am doing when coding for the rest of these deliverables especially on the biological side.

Tasks Completed

  • Used select() to convert gene symbols to gene IDs
  • Used enrichGO() and barplot() to generate bar plots
  • Used groupGO() and barplot() to generate bar plots
  • Used enrichKEGG() and dotplot() to generate dot plot
  • Used cnetplot()
  • Used STRING to generate PPI network

Things Learned:

  • Technical Area - Learned how to choose Log Fold Change Threshold for Gene Enrichment Analysis, Learned how to generate the appropriate metadata for the dataset,
  • Tools - RStudio, Stem-Away Platform(Discourse), GSuite tools(Gmail, Drive, Calendar, etc.), Slack, GitHub, Spacetime.am,
  • Soft Skills - Learned how to time manage to complete deliverables independently, Practice with troubleshooting problems individually,

Achievement Highlights:

  1. Was able to complete all final project deliverables
  2. Was able to successfully push a dataset through a custom bioinformatics analysis pipeline
  3. Was able to troubleshoot(Especially with Transcriptional Factor Analysis and GSEA)

List of meetings/trainings attended:

  • Week 6 - 8/14: Team Meeting, 8/17: Team Meeting

Goals for upcoming week

  • Complete Presentation slides
  • Nail the presentation itself!

Tasks Completed

  • Used ReadAffy() to read in GSE22598
  • Used rma() to normalize data
  • Used QCReport() for quality control
  • Used prcomp() to generate PCA Plots
  • Used pheatmap to generate heat maps
  • Used select() and collapseRows() for gene annotation
  • Used varFilter() for gene filtering
  • Used model.matrix() and EnhancedVolcano() to generate volcano plot and perform limma analysis
  • Used groupGO(), setReadable(), enrichGO(), select(), dotplot(), barplot(), plotGOgraph(), enrichKEGG(), cnetplot(), GSEA(), msigdbr(), read.gmt(), heatplot(), enricher() to perform Gene Ontology and Transcriptional Factor Analysis