2021 Summer – Neurology Research Orientated Coding and Data Analysis

data-analysis-blog

Skills taught: Experimental Biology, Fiji, ImageJ, Python, Excel, R Studio 

Prerequisites: Any type of coding familiarity and any biology class at school 

Purpose:This camp will teach you skills to set yourself apart when looking for a research lab to work in. You will learn how to use coding to automate research-oriented data analysis as well as get an introduction to problem solving in a research lab.


Microscopes are the most important instrument of all molecular biology labs, and data gathering from these images is menial labor that is always thrown at undergraduate researchers.

In this class, students will learn:

  • how to use code to automate data gathering, saving hundreds of hours of manual work. 
  • how to efficiently analyze the data gathered using Python, Excel, and R Studio to draw conclusions on our experiments.
  • working with real multi-channel images of primary rat neurons collected from Coach Josh’s lab. His lab focuses on the molecular pathway behind ALS disease and why it does what it does to neurons.
  • No experiment is completed without improvisation. Students will go into potential problems that could skew the data and learn how to fix them.

NOTE: All coding projects in class will be done in a small group with minimal instructor aid as to avoid mindless copying of code. This gives the students more opportunities to engage their minds. 


Class schedule: 

Day 1

  • Introductions, objectives of class outlined 
  • Install needed software 
  • Brief introduction into the experiment and analysis we will be conducting Overview of the workflow of data gathering and analysis 

 

Day 2:  

  • Theory into the science behind the experiment and what the multi-image channels represent Gene engineering, antibody staining, neuron transfection, fluorescent microscopy Introduction into how to use Fiji and imageJ to gather data from images More depth on how to manipulate images on Fiji 
  • Background subtraction, thresholding, marking regions of interest (ROIs) Measuring ROIs to acquire intensity data 
  • Introduction into scripts and automation of data collection using ImageJ 

 

Day 3:  

  • More depth into script automation for data collection  
  • First glimpse into data analysis 
  • Importing data into excel 
  • Learning how to use some advanced Excel formulas 
  • Pseudo-coding for next day’s project

 

Day 4: 

  • Code day: Write code with your groups to automate data collection on the experimental  images 

 

Day 5: 

  • Learning Python basics 
  • Focus on for-loop iteration and Pandas library for csv manipulation 
  • Pseudo-coding for next day’s project 

 

Day 6: 

  • Learn how to manipulate out experimental data using Python and Pandas into more usable  data 
  • Code day: Write code with groups to automate data manipulation of our experimental data 

 

Day 7:  

  • Introduction to R Studio 
  • Learn some basic statistical tests and their uses 
  • T-test, P-test, ANOVA 
  • Basic data manipulation in R Studio and how to make plots and graphs 

 

Day 8:  

  • Importing our experimental data into R Studio and examining our results Error analysis of data that doesn’t look good or match the pictures 
  • Think of ways to fix these problems

 

Course Features

  • Grade G10-G12
  • Max Enroll 8
  • Class Time 3:00 pm – 5:00 pm EST, 6/29-7/22 Tue & Thur (4 weeks, 8 sessions)
  • Class Location Online
$220

Josh Zhe is a rising Junior at the University of Michigan. He is studying Neuroscience, Computer Science, and Music. Josh has worked two years in the Barmada Lab which focuses on the pathology of ALS, and one summer at the Xiang Neurosurgery lab. Currently he is working on a project studying the detection and localization of TDP-43 and s(short)TDP-43 in neurons. He is on the premed track, and previously worked with mYe as a premed workshop presenter.