**Boot Camp in
Quantitative Methods**

August 2018

# Course Materials

**How to use the problem set packages**

Each day we will provide you with a downloadable zip file that will contain the files you will need for the day. Each folder in the package addresses a different type of problem and contains a set of questions, the data that you need to solve those questions as well as a proposed solution for each of them. We recommend you to read the problem set first and try to figure out how to answer the questions using the tools we will teach you in class.

Throughout the boot camp we will often present you with real biological problems and will challenge you to think about the essence of the problem and how to break it down into a smaller set of computational experiments that you can perform with your newly acquired programming skills.

It can be very challenging, especially when just beginning to code, to tackle all levels of a problem, understand what way to analyze the data, determine what code is needed, and then implement the code. Because of this every problem has an "Abridged" version that breaks down the biologically part. Use this part if you can't figure out what the question is asking and want to move onto trying to implement the code.

Finally, after having come up with your own solutions to the problem you could compare your approach to the proposed solutions in the package.

- image.mat
- Day 1 Packet (zip)
- Contains the
**MATLAB Intro**and**Yeast Showdown 1: Competition between strains by microscopy**. - mysteryData.mat
- Day 1 Homework (zip)
- Contains
**Flow Cytometry Exercise**and**Day 1 Homework problems**. - Day 1 Solutions file (zip)
- Contains the solutions for Day 1 Homework
- Day 2 Homework (pdf)
- Contains exercises for Learning Catalytics Day 2 Homework
- Day 2 afternoon exercise data
- Day 2 Solutions file (zip)
- Contains the solutions for Day 2 Homework
- Data file for Homework 3 AneuploidStrains_RNAseq+gDNA_NormToEuploid.xlsx
- Statistics Exercises (zip)
- Contains
*Rattus Binomialis*and*Neuron showdown*. Solution code to both exercises will be provided after class on Monday. - The statistics homework will be on LearningCatalytics:
*Four-choice Probability*and*False Positive Statistics* - Solution code to today's exercises. (zip file)
- Solution code to the homework exercises. (zip file)
- prostate cancer data
- Intro example for class.
- Image Analysis for Biology (pdf)
- An introduction to image analysis with MATLAB.
- Image files for "Image Analysis for Biology" (116 MB)
- Contains images needed for the exercises in the above image analysis packet.
- Timelapse Microscopy Exercise (500MB zip)
- Contains the
**Timelapse Microscopy**exercise. - Homework Yeast Showdown 1.5: Cell segmentation (zip)
- Contains the
**Yeast Showdown 1.5**exercise, an extension to Yeast Showdown I that uses more advanced image analysis techniques. - False positives and "researcher degrees of freedom"
- Bioinformatics: Data import (zip)
- An introduction to importing data into MATLAB (used to be Bonus Bioinformatics).
- Bootstrap Bill (zip)
- Direction tuning data from an MT neuron: polar plots and circular statistics; permutation test and bootstrapping for confidence intervals.
- Calcium Imaging Exercise (zip)
- GCaMP5 data from neurons in the optic tectum of larval zebrafish: PCA/SVD to de-noise data; local pixel correlations to identify active neurons.
- Finding Lincoln (zip)
- Image processing from a psychophysical perspective: image filtering; edge detection; image analysis in the frequency domain (FFT2).
- Natural Images and your Brain (zip)
- Image processing from a neural perspective: statistics of natural images (spatial correlations and redundancy); retinal filtering; edge detection as “suspicious coincidence."
- Spike Sorting (zip)
- Time series data from an extracellular electrode: PCA/SVD to group different waveforms (i.e. sort spikes); 3D plotting; interspike interval (ISI) histograms.
- Spike-triggered Average (zip)
- Discovering the image features that make a neuron fire: event-triggered averages to find receptive fields; random permutation statistics to find the signifcant parts of images or results.
- Filezilla from our local server
- To upload and download files from the cluster
- Bioinformatics Exercise 2015
- All the data for the exercise

## Before the course

## Day 1

## Day 2

Excel file to be used in a demo (xlsx)

In class assignment

The Day 2 Homework also uses files from Yeast Showdown 1 which are located in the Day 1 Packet (link above)

## Day 3

## Day 4 Statistics Day (Mon. 20 Aug. 2018)

## Day 5

## Day 6

### Morning

### Neuroscience exercises for Friday, August 24, 2018

### Day 6 - Afternoon bioinformatics group

- Filezilla from our local server
- More things to get from the cluster
- Simbiology Intro (pdf)
- Marathon and Boston rain exercies(zip)
- Contains two exercises on basic data processing
- Neuroscience tutorials(zip)
- Contains .m files with tutorials on
**Choice and probability**,**Fourier Analysis**, and**Poisson processes**. - Ground Hog Day: Is the ground hog getting it right?
- Data on historical predictions and the weather for Grand Rapids, Michigan (together with a possible pathway for analysis) can be found in this paper
- Exercise and academic performance
- Raw data seems to be hard to come by, but check out this meta-study. Then again, check out this critical comment which raises questions about sample selection.
- Movie box office numbers and other information
- Box office mojo
- International Movie Database
- Baseball data
- Baseball databank
- Retrosheet
- Stock market data
- Yahoo finance

### Day 6 - Backup Download Bioinformatics group

### Afternoon - Pathway modeling group

## Bonus Exercises

### Old Non-science problems

## Note to instructors

This site contains .zip files that bundle the course materials for our students at the current (or most recent) offering of the Quantitative Methods Boot Camp. The latest version of our course materials can also be accessed on our GitHub repository.

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.