Interstitial Lung Disease Analysis Project- Kevin Lin

Presentation (PowerPoint):

** Relevant code is found in the document**

Challenges Faced:

  • Deciding on best data set to work with was the first issue that occurred. At first, I wanted to work with data regarding chronic obstructive pulmoary disease, but when I got to the limma analysis using the makeConstrasts function, I was not sure how to compare data between 3 different group types (smokers, nonsmokers, COPD patients). Thus, I decided to use more manageable data which only compared ILD cells with normal cells.
  • When it came to the functional analysis section of the final project, there was very few enriched terms to work with. Furthermore, differences in gene expression between ILD cells and normal cells almost seemed insignificant. However, this was overcome by doing extensive research on the molecular functions where upregulated and dowregulated genes differed.

Summary of Work:

  • After conducting background research on what interstitial lung diseases are, microarray data from the GEO website link was downloaded. The data’s series matrix was also downloaded and some of its sections were converted into metadata.
  • Quality control, background correction, and normalization was used on the downloaded data through R. A QC stat report, an arrayQualitymetrics report, two boxplots, and a heatmap were generated.
  • Annotations, gene filtering, and limma analysis was used to find the top DEGs which were later visualized with a heatmap and volcano plot.
  • Functional analysis was conducted on the DEGs, generating an upregulated gene enrichGO bar graph with MF ontology, an upregulated groupGO bar graph with MF ontology, a downregulated groupGO bar graph with MF ontology, a gene concept network/ cnet plot, and gene set enrichment analysis graph.
  • All generated reports and graphs were presented and discussed in a 15 minute presentation.

Further Notes:

  • Overall, I enjoyed conducting the research and preparing for the presentation. I would like to thank all the leads, mentors, and other bioinformatics interns that helped me throughout this experience, especially @Sarahrp,@Anca, and @ashlesha.patil. I would also like to thank @meenoti2001, @giabaot, and @cmikofsky for welcoming me into their charismatic team. I would also like to thank STEM-Away for providing me this opportunity to develop skills that I can use to further my STEM career.