Bioinformatics - Level 1 Module 1 - Brian Caballo

Technical Area

  • Coding with R on R studio

  • Coding basics such as syntax, variables, data structures, functions

  • Utilized visualizing package to create charts (ggplot2)

  • Consolidated skills in reading difficult research papers

Tools

  • Learned the core areas of R Studio to effectively code and analyze data

  • Looked into Github as a tool for sharing code

  • Stem-away website as a reference for better understanding

  • GEO2R to access genetic data

Soft Skills

  • Paying attention and retaining information: When going through the module, I found myself constantly having to go back and check how to do something code-wise, so I had to truly grasp the information I was reading

  • Independence: Learning by myself is not the easiest thing and I constantly feel that I aim going off track, but I managed to push through

  • Focus: I shunned all distractions to stay engaged

Achievement Highlights:

  • Understood the navigation of the Stem-Away website; it was quite difficult on the first encounter

  • Getting a decent grasp of the R language; it felt good to know what I was doing with the language

  • Reached out to my mentor and got the help I needed; I recognized when I needed assistance

Tasks Completed:

  • In order to understand how to navigate Stem-Away, I just spent time exploring the pathways and clicking around until I got a decent grasp

  • Downloading R and R Studio was a bit confusing because I have Mac and I had to find a different version, but I reached out to my mentor who was able to help

  • I was a little confused with the code syntax for graphs initially, but I reread and looked at examples online to get a better understanding

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Overview

Technical Area

  • Going more in-depth with R: using packages such as affy, pheatmap, and affyPLM

  • Familiarizing with GEO: GEO2R analysis, GEO databases

  • Utilizing metadata: importing and manipulating data

Tools

  • Built upon knowledge of R Studio

  • Stem-away website as a reference

  • GEO database to access data

  • Google to help me get help in some areas

  • Excel for metadata

Soft Skills

  • Application of information: putting Module 1 into use, which was not easy at first

  • Time management: spending time effectively

  • Independence: getting things done alone

Achievement Highlights:

  • Gaining a better understanding of GEO, and successfully utilizing to get data

  • Working with metadata files, learning about its purpose and how it works

  • Getting a better feel of different R packages and what they can be used for

Tasks Completed

  • At first, I was struggling a bit with getting the data from GEO, which I was able to resolve by searching up help

  • I initially used the browser version of Excel, but went through the process of downloading it and using it correctly to organize metadata

  • I was a little confused with the merging function to batch, but I eventually understood that by looking over the resources and used it correctly on the data

Overview

Technical Area

  • Utilizing Bioconductor packages: quality control, identifying outliers in data, data analysis
  • Creating appropriate visuals for data
  • Data organization/normalization

Tools

  • Built upon knowledge of R Studio
  • Stem-away website as a reference
  • Google to help me get help in some areas
  • Excel
  • Github

Soft Skills

  • Application of information: putting previous modules to use
  • Time management: spending time effectively
  • Independence: getting things done alone
  • Knowing when to get help

Achievement Highlights:

  • Using R packages more effectively and independently
  • Successfully carried out Quality Control despite some difficulties
  • Successfully obtained data outliers
  • Effectively visualized data

Tasks Completed

  • I had some difficulty trying to execute certain methods because of different data formats; I realized how important it was to pay extremely close attention to directions and when to use different formats such as AffyBatch
  • I had a difficult time when I was first getting into PCA. I had multiple errors when it came to successfully creating the visualizations, which I spent a lot of time going through, searching up certain things like errors, and more. In the end, it felt like an accomplishment to get it done.
  • As with Module 2, I had a few troubles with the metadata that I was able to solve and eventually make the correct metadata file. I believe this had something to do specifically with my computer, which I have fixed.