Tanishk - Bioinformatics Pathway

Things Learned:

  • Technical Area - Became familiar with using bioinformatics analysis packages in R, Revisited Python syntax and concepts, Gained understanding of plots(Heat maps, Volcano plots, PCA plots, etc.), Learned more about the biological side to bioinformatics(gene expression, biological processes in cells, protein-protein interaction, etc.),

  • Tools - RStudio, Asana, Stem-Away Platform(Discourse), GSuite tools(Gmail, Drive, Calendar, etc.), Jupyter, Slack

  • Soft Skills - Online team communication and collaboration, Online meeting etiquette, Giving feedback in a professional and compassionate way, Practice in reaching out to mentors/leads for help,


Achievement Highlights:

  1. Understood how R can be utilized to serve Bioinformatics purposes and completed all Python Exercises (Still working on R exercises)

  2. Have a good idea of the process(es) involved in collecting and analyzing gene data (Pipeline)

  3. Have a solid foundation in gene expression and related cell processes


List of meetings/trainings attended:

  • Week 1 - 5/29: Kick-Off Meeting, 6/1: Bioinformatics Webinar, 6/2: R Training, 6/3 Bioinformatics Webinar, 6/5: R Training, 6/6: Python Training

  • Week 2 - 6/8: Team Meeting, 6/9: R Training, 6/9: Python Training, 6/10: Logistical Webinar, 6/10: Technical Training, 6/11: Team Meeting, 6/12: Welcome Session, 6/12: R Training, 6/12: Team Happy Hour

  • Week 3 (so far) - 6/15: Team Meeting, 6/16: Asana Training


Goals for upcoming week

  • Keep working on understanding the paper and figures

  • Becoming more confident in using R to analyze gene datasets

Things Learned:

  • Technical Area - Generated and gained a deeper understanding of PCA plots, Worked with the affyPLM and ggplot2 packages, Worked with following functions: fitPLM, mas5, ReadAffy, RLE, and NUSE, Familiarity with .CEL, .gz, and .tar files, Worked with following data structures: matrix/data frame and AffyBatch
  • Tools - Became more familiar with Juypter Notebooks, Asana, GEO, and RStudio,
  • Soft Skills - What is means and how to become culturally competent, How to network and the importance of it, Teamwork in an online setting

Achievement Highlights:

  1. Created a PCA plot as well as RLE and NUSE Box Plots and Histograms
  2. Communicated with team to divide up the deliverables and complete tasks by deadline
  3. Have a solid foundation in quality control as well as normalization and correction of gene data.

List of meetings/trainings attended:

  • Week 3 - 6/15: Team Meeting, 6/16: Asana Training, 6/16: Python and Pandas Webinar, 6/17: Technical Training Webinar, 6/18: Gene Team Meeting

Goals for upcoming week

  • Make sure to understand what I am doing and why when using R to complete deliverables
  • Work with my team and get all the Week 4 deliverables done by Monday

Detailed Statement of Tasks Done

  • Used ReadAffy to import .CEL.gz files into RStudio
  • Created a PCA plot as well as RLE and NUSE Box Plots and Histograms using mas5 and fitPLM
  • I had trouble installing some of the packages, so I contacted one of the mentors who quickly sent a response to help.

Things Learned:

  • Technical Area - Became familiar with using the “limma” R package, Deeper understanding of Volcano Plots, Learned how to annotate gene data, Learned how the combination of P-values and Log Fold Change give us the important differentially expressed genes, Learned what a model matrix is and how it made and used,
  • Tools - GitHub, Asana, Python(Jupyter Notebooks), Excel
  • Soft Skills - The importance of creativity, Contributing in group presentations

Achievement Highlights:

  1. Generated Volcano Plot
  2. Got a deeper understanding of how microarrays work
  3. Worked with phenotypic data and understood the importance of it.

List of meetings/trainings attended:

  • Week 4 - 6/22: Team 2 Meeting, 6/22: Gene Team Meeting, 6/24: Fireside Chat, 6/25: GitHub Training Webinar, 6/25: Training Webinar, 6/25: Gene Team Meeting,

Goals for upcoming week

  • Make sure to complete Week 5 deliverables by next Monday
  • Complete Python exercises

Detailed Statement of Tasks Done

  • Completed phenotypic deliverables using Excel to clean up series matrix and R to apply data.
  • Using the correct R package and the merge function, I converted Probe IDs into gene symbols.
  • I created a document where my team could compile the deliverables.

Things Learned:

  • Technical Area - Learned how to use the clusterProfiler package, groupGO(), enrichGO(), setReadable(), enrichKEGG(), enricher(), and GSEA(), Became familiar with the Enrichr website,
  • Tools - GitHub, RStudio, Stem-Away Platform, GroupMe, Slack, Google Suite Tools,
  • Soft Skills - Strategies for writing resumes, How to give an elevator pitch,

Achievement Highlights:

  1. I was able to complete deliverables 5.1 - 5.4
  2. I was able to transition smoothly between teams
  3. I was able to troubleshoot both using the forums and by working with my team.

List of meetings/trainings attended:

  • Week 5 - 6/29: Gene Team Meeting, 6/30: Fireside Chat, 7/2: Gene Team Meeting

Goals for upcoming week

  • Get a deeper understanding of what I am doing when I am completing the deliverables
  • Complete Week 6 deliverables on time

Detailed Statement of Tasks Done

  • Loaded all the necessary packages and created gene vector as well as data frames with the ENTREZIDS and EMSEMBLs
  • Used groupGO() and used the results to generate bar plots
  • Used enrichGO() and setReadable() to plot dot plot, bar plot, and GOgraph
  • Used enrichKEGG() and used to results to generate dot plot
  • Used enricher() and GSEA() for the WikiPathways Analysis

Things Learned:

  • Technical Area - Learned how to use the Enrichr website, Understood how to choose results from the Enrichr website and how to interpret them, Learned how to use the STRING website,
  • Tools - GitHub, RStudio, Stem-Away Platform, GroupMe, Slack, Google Suite Tools,
  • Soft Skills - Learned how to give a excellent presentation, Worked on public speaking skills

Achievement Highlights:

  1. I was able to generate the Wikipathway result through Enrichr
  2. I was able to generate a plot using the STRING website
  3. I was able to work with my team and Team 6 to complete presentation

List of meetings/trainings attended:

  • Week 6 + 7 - 6/6: Gene Team Meeting, 6/8: Team 4 Meeting, 6/8: Gene Team Meeting, 6/12: Team 4 + 6 Meeting, 6/13: Gene Team Meeting, 6/15: Gene Team Meeting

Goals for upcoming week

  • Complete Final Deliverables on Time
  • Work on my presentation for the Final Deliverables

Detailed Statement of Tasks Done

  • Created the Enrichr website input and generated results
  • Created the STRING website input and generated results

Things Learned:

  • Technical Area - Learned how to use Metascape, Learned how to use affyQCReport, Worked more on using a correlation matrix to generate a heatmap, Learned how to use pheatmap,
  • Tools - GitHub, RStudio, Stem-Away Platform, GroupMe, Slack, Google Suite Tools,
  • Soft Skills - Gained a deeper understanding of why networking is important and how it can be beneficial

Achievement Highlights:

  1. I was able to run the data successfully through my pipeline
  2. I was able to finish all the final deliverables on time
  3. I was able to troubleshoot with the help of mentors and other interns

List of meetings/trainings attended:

  • Week 8 - 6/17: R Office Hours, 6/21: Gene Team Meeting

Goals for upcoming week

  • Finish off last few minor details for the Final Deliverables presentation
  • Make sure to nail the presentation itself!

Detailed Statement of Tasks Done

  • Loaded GSE21510 data into R
  • Created heatmaps, RLE and NUSE plots, PCA plot, Volcano Plot, GO plot, dot plots, and bar plots.
  • Used model.matrix() to generate differentially expressed genes.
  • Used Metascape for functional analysis
  • Used STRING to generate PPI Network

Final Self-Assessment

Things Learned:

  • Technical Area - Became familiar with using bioinformatics analysis packages in R, Revisited Python syntax and concepts, Gained understanding of plots(Heat maps, Volcano plots, PCA plots, etc.), Learned more about the biological side to bioinformatics(gene expression, biological processes in cells, protein-protein interaction, etc.), Worked with the affyPLM and ggplot2 packages, Worked with following functions: fitPLM, mas5, ReadAffy, RLE, and NUSE, Familiarity with .CEL, .gz, and .tar files, Worked with following data structures: matrix/data frame and AffyBatch, Became familiar with using the “limma” R package, Deeper understanding of Volcano Plots, Learned how to annotate gene data, Learned how the combination of P-values and Log Fold Change give us the important differentially expressed genes, Learned what a model matrix is and how it made and used, Learned how to use the clusterProfiler package, groupGO(), enrichGO(), setReadable(), enrichKEGG(), enricher(), and GSEA(), Became familiar with the Enrichr website, Learned how to use the Enrichr website, Understood how to choose results from the Enrichr website and how to interpret them, Learned how to use the STRING website, Learned how to use Metascape, Learned how to use affyQCReport, Worked more on using a correlation matrix to generate a heatmap, Learned how to use pheatmap,
  • Tools - RStudio, Asana, Stem-Away Platform(Discourse), GSuite tools(Gmail, Drive, Calendar, etc.), Jupyter, Slack, GitHub, Excel, GroupMe, Zoom, Google Meet,
  • Soft Skills - Online team communication and collaboration, Online meeting etiquette, Giving feedback in a professional and compassionate way, Practice in reaching out to mentors/leads for help, Online team communication and collaboration, Online meeting etiquette, Giving feedback in a professional and compassionate way, What is means and how to become culturally competent, How to network and the importance of it, Teamwork in an online setting, The importance of creativity, Contributing in group presentations, Strategies for writing resumes, How to give an elevator pitch, Learned how to give a excellent presentation, Worked on public speaking skills, Gained a deeper understanding of why networking is important and how it can be beneficial

Achievement Highlights:

  • Understood how R can be utilized to serve Bioinformatics purposes and completed all Python Exercises (Still working on R exercises)
  • Have a good idea of the process(es) involved in collecting and analyzing gene data (Pipeline)
  • Have a solid foundation in gene expression and related cell processes
  • Created a PCA plot as well as RLE and NUSE Box Plots and Histograms
  • Communicated with team to divide up the deliverables and complete tasks by deadline
  • Have a solid foundation in quality control as well as normalization and correction of gene data.
  • Generated Volcano Plot
  • Got a deeper understanding of how microarrays work
  • Worked with phenotypic data and understood the importance of it. 1. I was able to complete deliverables 5.1 - 5.4
  • I was able to transition smoothly between teams
  • I was able to troubleshoot both using the forums and by working with my team.
  • I was able to complete deliverables 5.1 - 5.4
  • I was able to transition smoothly between teams
  • I was able to troubleshoot both using the forums and by working with my team.

List of meetings/trainings attended:

  • Week 1 - 5/29: Kick-Off Meeting, 6/1: Bioinformatics Webinar, 6/2: R Training, 6/3 Bioinformatics Webinar, 6/5: R Training, 6/6: Python Training
  • Week 2 - 6/8: Team Meeting, 6/9: R Training, 6/9: Python Training, 6/10: Logistical Webinar, 6/10: Technical Training, 6/11: Team Meeting, 6/12: Welcome Session, 6/12: R Training, 6/12: Team Happy Hour
  • Week 3 - 6/15: Team Meeting, 6/16: Asana Training, 6/16: Python and Pandas Webinar, 6/17: Technical Training Webinar, 6/18: Gene Team Meeting
  • Week 4 - 6/22: Team 2 Meeting, 6/22: Gene Team Meeting, 6/24: Fireside Chat, 6/25: GitHub Training Webinar, 6/25: Training Webinar, 6/25: Gene Team Meeting,
  • Week 5 - 6/29: Gene Team Meeting, 6/30: Fireside Chat, 7/2: Gene Team Meeting
  • Week 6 + 7 - 6/6: Gene Team Meeting, 6/8: Team 4 Meeting, 6/8: Gene Team Meeting, 6/12: Team 4 + 6 Meeting, 6/13: Gene Team Meeting, 6/15: Gene Team Meeting
  • Week 8 - 6/17: R Office Hours, 6/21: Gene Team Meeting

Detailed Statement of Tasks Done

  • Used ReadAffy to import .CEL.gz files into RStudio
  • Created a PCA plot as well as RLE and NUSE Box Plots and Histograms using mas5 and fitPLM
  • I had trouble installing some of the packages, so I contacted one of the mentors who quickly sent a response to help.
  • Completed phenotypic deliverables using Excel to clean up series matrix and R to apply data.
  • Using the correct R package and the merge function, I converted Probe IDs into gene symbols.
  • I created a document where my team could compile the deliverables.
  • Loaded all the necessary packages and created gene vector as well as data frames with the ENTREZIDS and EMSEMBLs
  • Used groupGO() and used the results to generate bar plots
  • Used enrichGO() and setReadable() to plot dot plot, bar plot, and GOgraph
  • Used enrichKEGG() and used to results to generate dot plot
  • Used enricher() and GSEA() for the WikiPathways Analysis
  • Created the Enrichr website input and generated results
  • Created the STRING website input and generated results
  • Loaded GSE21510 data into R
  • Created heatmaps, RLE and NUSE plots, PCA plot, Volcano Plot, GO plot, dot plots, and bar plots.
  • Used model.matrix() to generate differentially expressed genes.
  • Used Metascape for functional analysis
  • Used STRING to generate PPI Network

Final Deliverables - Tanish Kumar.docx (936.4 KB)
Final Deliverables Presentation - Tanish Kumar.pptx (2.8 MB)