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https://github.com/mahshaaban/intro_data_r

A gentle introduction to data analysis in R
https://github.com/mahshaaban/intro_data_r

data-analysis image-analysis qpcr-analysis r

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A gentle introduction to data analysis in R

Host: GitHub
URL: https://github.com/mahshaaban/intro_data_r
Owner: MahShaaban
License: mit
Created: 2022-04-16T00:07:19.000Z (over 2 years ago)
Default Branch: master
Last Pushed: 2023-08-08T13:16:23.000Z (over 1 year ago)
Last Synced: 2023-08-08T14:57:16.971Z (over 1 year ago)
Topics: data-analysis, image-analysis, qpcr-analysis, r
Language: Dockerfile
Homepage: https://www.mahshaaban.com/courses/1116
Size: 4.51 MB
Stars: 5
Watchers: 2
Forks: 2
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

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README

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## Introduction to data analysis in R

### Description

This is a short course on data analysis in R. The goal is to get the 

participants familiar with R code and to appreciate it as a tool to handle

common experimental data. The materials are delivered in the form of 

lectures and interactive exercises.

### Objectives

- To get familiar with R as a tool for data analysis

- To apply basic arithmetic and statistics in R

- To learn to handle experimental data in R (qPCR and images)

### Format

Each module is delivered in three steps

- [`lectures/`](lectures/): slides discussing the main concepts

- [`practice/`](practice/): interactive exercises for practicing purposes

- [`homework/`](homework/): more exercises to test understanding

### Outline

- Getting started in R

    - Lecture ([Slides](lectures/lecture_1.pdf))

    - Practice ([Link](https://bcmslab.shinyapps.io/practice_1/))

    - Homework ([Link](https://bcmslab.shinyapps.io/homework_1/))

- Basic statistics in R

    - Lecture ([Slides](lectures/lecture_2.pdf))

    - Practice ([Link](https://bcmslab.shinyapps.io/practice_2/))

    - Homework ([Link](https://bcmslab.shinyapps.io/homework_2/))

- Quantifying mRNA using the `pcr` package

    - Lecture ([Slides](lectures/lecture_3.pdf))

    - Practice ([Link](https://bcmslab.shinyapps.io/practice_3/))

    - Homework ([Link](https://bcmslab.shinyapps.io/homework_3/))

- Quantifying protein co-localization in fluorescence images using the `colocr` package

    - Lecture ([Slides](lectures/lecture_4.pdf))

    - Practice ([Link](https://bcmslab.shinyapps.io/practice_4/))

    - Homework ([Link](https://bcmslab.shinyapps.io/homework_4/))

### Readings

- Tidy data by Hadley Wickham ([Link](https://www.jstatsoft.org/article/view/v059i10))

- Ahmed M, Kim DR. pcr: an R package for quality assessment, analysis and 

testing of qPCR data. PeerJ. 2018 Mar 16;6:e4473. 

doi: [10.7717/peerj.4473](https://pubmed.ncbi.nlm.nih.gov/29576953/).

- Ahmed M, Lai TH, Kim DR. colocr: an R package for conducting co-localization

analysis on fluorescence microscopy images. PeerJ. 2019;7:e7255.

doi:[10.7717/peerj.7255](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6612416/)

### Resources (what to learn next?)

- Introduction to R ([Data Camp Free Interactive Course](https://www.datacamp.com/courses/free-introduction-to-r))

- Intermediate R Course ([Data Camp Free Interactive Course](https://www.datacamp.com/courses/intermediate-r))

- R for Data Science ([Book](https://www.amazon.co.jp/-/en/Hadley-Wickham/dp/1491910399))