Ashlesha.patil - Bioinformatics (Level 2) Pathway

Week 1 Self-Assessment

Things Learnt:

Technical Skills

  • Refreshing my skills in R, R studio and basics of GitHub
  • Reading and evauluating the Long et al., 2019 paper on lung cancer
  • Understanding how R shiny works and the key features of this web application

  • Tools:

  • R, R Studio
  • R shiny basics
  • STEM-Away platform

  • Soft Skills

  • Learning more about my team members and fellow leads
  • Collaboration with leads to present first team meeting
  • Time Management, with STEM-Away and my other commitments

  • Achievement highlights

  • Getting started with STEM-Away and Level 2 project, familiarising myself with new format and structure of my Dashboard and STEM-Away forum
  • Hosting first team meeting with my co-lead and PM lead, with icebreakers to introduce all team members and a presentation to get the team introduced to the project and journal club
  • Going back to using R and R Studio along with learning about R Shiny and its components and structure
  • Week 2 Self-Assessment

    Things Learnt:

    Technical Skills

    • Working in R Studio further in the transcriptomics pipeline and deliverables for Module 2
    • Going ore in depth into R Shiny, and successfully managing to make my first Shiny App, called BMI calculator, while learning more about R Shiny themes, adding text, images, sliding bars to input data, and getting an output.
    • Also refreshed my GitHub basic knowledge, watching Collin’s tutorials and help from the mentors and technical leads.

    Tools:

    • R, R Studio
    • R shiny
    • STEM-Away platform
    • Trello
    • GitHub

    Soft Skills

    • Collaboration with leads within my team to organise the team meeting for the week, and also collaborating with leads across other teams to successfully complete the week’s deliverables before presenting to team members
    • Producing my first R Shiny product, knowing to get help from the technical lead, and using additional resources available to me
    • This was followed by presenting and showcasing my application to rest of the Bioinformatics team on a technical training session.

    Achievement highlights

    • Successfully completing the week’s deliverables before the team meeting, and helping other team leads to prepare the presentations for the meeting, even though I was not able to make it.
    • Studying R Shiny in more depth, and creating my first R Shiny app
    • Understanding the new proposed project workflow, and also collaborating with team members from the UX pathway to organise interviews for next week and fill in google surveys.

    Week 3 Self-Assessment

    Things Learnt:

    • Module 3 deliverables: using all 4 of the quality control packages: simpleaffy, ArrayQualityMetrics, AffyQCReport and affyPLM, to run quality checks on the genomic data and identify potential outliers
    • Worked with @irock194 to produce plots of the data output of affyPLM, creating RLE and NUSE boxplots, heat maps and also understanding the meaning of the clusters and the scales
    • For principal component analysis (PCA), managed to generate plots of PC1 vs PC2 and also ellipses around two clusters of normal and cancer groups to also identify further outliers

    Tools:

    • R, R Studio
    • Collaboration tools for communication

    Soft Skills

    • Collaboration with team members and other leads
    • Time Management and prioritisation of tasks
    • Presentation skills
    • Leadership

    Achievement Highlights

    • Collaborating with another team member to complete the week’s deliverables together, and also troubleshooting and reaching out to mentor when required
    • Presenting these deliverables alongside with introducing the team to next week’s deliverables and working on those as well
    • Working on Stemaway tasks along with other commitments, and producing deliverables in time

    Week 4 Self-Assessment

    Things Learnt:

    • Module 4 deliverables: successfully managing to run Limma statistical analysis on the cleaned dataset and generate topTable of differentially expressed genes. Also generated a volcano plot with similar results to the initial research paper.
    • R Shiny: Worked with Sneha in group B2 to develop a layout for our section in the app, which includes the sections of Quality Control and Normalisation.

    Tools:

    • R, R Studio
    • Collaboration tools for communication
    • Figma for R Shiny Layout designing

    Soft Skills

    • Collaboration with team members and other leads
    • Time Management and prioritisation of tasks
    • Presentation skills
    • Leadership

    Achievement Highlights

    • Keeping up with the modules and weekly deliverables, and going to Lead OH to help when required.
    • Introducing the team to next week’s deliverables along with other team leads
    • Working on R Shiny and using figma to design a layout for QC and normalisation section of app

    Week 5 Self-Assessment

    Things Learnt:

    • Module 5 deliverables: Taking the top differentially expressed genes from last week’s deliverables and understanding their functional implications using many Bioconductor packages in R
    • Functional analysis included Gene Ontology in all three areas of Molecular Functions, Biological Processes and Cellular Components
    • Also worked on GSEA cnet plot, and dotplots for enrichKEGG

    Soft Skills

    • Collaboration with team members and other leads
    • Collaboration with other pathways
    • Presentation skills
    • Leadership

    Achievement Highlights:

    • Completed the week’s deliverables in time before presenting them to interns at the weekly team meetings
    • Worked to understand designing layout of the app further, using figma and presenting these to the UX team and getting their inputs

    Week 6 Self-Assessment

    Things Learnt:

    • Module 6 deliverables: Functional analysis of top DGE genes using web-based tools including EnrichR, David, Metascape, GEPIA and StringDB
    • Explored GEPIA further to generate survival analysis plots for AGER and other top genes
    • Understood the many functional analysis plots generated by Metascape, how the genes are clustered together in their common functions

    Soft Skills

    • Collaboration with team members and other leads
    • Collaboration with other pathways
    • Presentation skills
    • Leadership

    Achievement Highlights:

    • Completed the week’s deliverables in time before presenting them to interns at the weekly team meetings
    • Worked alongside Marc and Sneha to use three of the functional deliverable tools in the web, Metascape, EnrichR and GEPIA and analysing the results from these
    • Wrapping up final team meeting for the capstone project and the transcriptomics pipeline