Functions: Theory and Application (in R)
Athit Kao, PhD
UCI Bioinformatics Support Group - April 25, 2018
whoami
Prerequisites
Understand content from previous deck: http://learn.athitkao.com/presentation_functions1.html
Basic programming experience necessary
R and RStudio installed
Consider a simple use case for programming in your field, e.g.:
- Filter specific data from file
- Munge proprietary data format into CSV
- Calculating RPKM for sequencing data
Readability, part II
- Encapsulation via functions is an aspect of code legibility
- Others include:
- Documentation (comments and READMEs)
- Formatting (indentation and line wrapping)
- Variable naming (obvious and consistent names)
- There is a balance appropriate for you/your audience:
Generalized Concept of Functions
Function Argument Order
- If argument names aren't specified (e.g. “first = first”), then they must be in order
- https://www.safaribooksonline.com/library/view/r-in-a/9781449358204/ch09s05.html
Anonymous Functions (in lapply)
- Function without a name that is evaluated without need of assigning it to a variable
- A.k.a. lambda expression
- https://lukesingham.com/anonymous-functions-in-r-python/
Multiple Arguments (in lapply)
- First argument always the iterated variable
- Must explicitly name additional arguments
The Assignment Operator
- Use “<-” or “=”?
- I use “=” for consistency (with other programming languages) with no issues
- Consistency even within R
Environments and Variable Scoping in R
- Scoping refers to the visibility of variables in different environments
- Global: Can be referenced from anywhere
- Local: Accessible only within its environment
- http://adv-r.had.co.nz/Environments.html
- R uses “lexical” (a.k.a. static) scoping rules
Microsoft Excel
Pros
- Quick editing and prototyping
- WYSIWYG plots
- Widely known and used program
- Many similar alternatives (e.g. Sheets, Calc, Numbers, etc.)
- Programming/automation with Visual Basic
R Programming Language
Pros
- Quick prototyping towards minimum viable product
- Can generate complex interactive visualizations (plots, reports, etc.)
- No practical limit on data size
- Easily reproduce results and adapt code to changes
- You can do almost anything purely in R
Split-Apply-Combine Paradigm
Multithreading Split-Apply-Combine
Pre-loaded Data Sets in R
- E.g. iris, mtcars, airquality, faithful, etc.
- https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/00Index.html
Toy Example: Split...
Toy Example: ..Apply and Combine
Summarize for me...
- Good and bad of spreadsheet programs?
- What is scoping?
- What is an anonymous function?
- T/F: You must comment all code.
- T/F: You can't return a function from a function.
- T/F: Split-Apply-Combine is exclusive to R.
- #4, FALSE; #5, FALSE; #6, FALSE
Questions?
- Just try new code and see what happens; this isn't wet lab
- Google: Don't just search with “R”, use “R language”
- Stack Overflow: Use tag “[r]”
Keep going, you got this!
Previous deck: http://learn.athitkao.com/presentation_functions1.html
This deck: http://learn.athitkao.com/presentation_functions2.html
Contact: https://www.linkedin.com/in/atetkao
App: Scoping (cont.)
App: do.call(rbind, list)
- lapply( ) applies given function to each list element, iteratively
- do.call( ) applies given function to the list as a whole, once
App: NIH Proficiency Scale
- 1. Fundamental Awareness (basic knowledge): Common knowledge/understanding of basic techniques/concepts
- 2. Novice (limited experience): Expected to need help when performing this skill
- 3. Intermediate (practical application): Able to successfully complete tasks; expert required occasionally
- 4. Advanced (applied theory): Able to successfully complete tasks without assistance
- 5. Expert (recognized authority): Can provide guidance, troubleshooting, and answers related to this skill
- Source: https://hr.nih.gov/working-nih/competencies/competencies-proficiency-scale