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A B C.......Q R S!. Coil ín Minto Department of Biology, Dalhousie University. Please note. Applied introductory class on use of the S language Procedures for a basic analysis of biological data My perspective. Questions please!. Class outline. Introduction to the software Workshop
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A B C.......Q R S! Coilín Minto Department of Biology, Dalhousie University
Please note • Applied introductory class on use of the S language • Procedures for a basic analysis of biological data • My perspective
Questions please! Class outline • Introduction to the software • Workshop • Biological example
Historical perspective • S language and environment developed by John Chambers and colleagues at Bell Laboratories (formerly AT&T, now Lucent Technologies) • S-Plus, a commercial version of S by Insightful Software since 1987, now at version 7 • R is a GNU project that started in the mid-1990s • Current production version released on June 20th is 2.2.1
What can S do for me? • Statistical and graphical capabilities • linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ... • Scatterplots, histograms, q-q plots, maps, … • A well-developed programming language (S) • Highly expandable through hundreds of packages
Why use S? • Incredibly flexible • Accessible/intuitive language • Well supported (especially R) • Powerful language capabilities
Calculations in S > 19*5 [1] 95 > log(2) [1] 0.6931472 > exp(2) [1] 7.389056 >seq(0,5) [1] 0 1 2 3 4 5 > plot(cos(seq(0,10,length=100)))
In the beginning <- 1. Create object (vector, matrix, list) > marsupial.vec <- c(“kangaroo”, “possum”, “koala”) # character > marsupial.vec [1] "kangaroo" "possum" "koala" > fib.vec <- c(0, 1, 1, 2, 3, 5, 8, 13) # numeric > fib.vec [1] 0 1 1 2 3 5 8 13 > unit.mat <- matrix(c(1,0,0,0,1,0,0,0,1),ncol=3) > unit.mat [,1] [,2] [,3] [1,] 1 0 0 [2,] 0 1 0 [3,] 0 0 1
In the beginning 2. Basic manipulations > length(fib.vec) [1] 8 > max(fib.vec) [1] 13 > dim(unit.mat) [1] 3 3 > diag(unit.mat) [1] 1 1 1
Use drop down # easier File: Load library # S-plus Packages: Load package # R Basic steps in an analysis Please refer to code on webpage 1. Import your data > read.table() 2. Plot your data > plot(), boxplot(), histogram() 3. Obtain suitable function a. Function available: call function b. Function not loaded in session: library(function) c. Function not downloaded: install.packages(package) then b. NB. Only in R (open source)
Basic steps in an analysis 4. Analyse / fit models > model1 <- lm(variable.y~variable.x) > summary(model1) > pca1 <- princomp(x, scores=T, cor = ) > summary(pca1) > dfa1 <- discrim(y~x, data= , family=) # S-plus > dfa1 <- lda(y~x, data=) # R > summary(dfa1) > pca1 <- princomp(x, scores=T, cor = ) > summary(pca1)
Help • ? function # brings up a help page • http://myweb.dal.ca/hwhitehe/BIOL4062/S-Plus_Intro.pdf • http://cran.r-project.org/ # manuals • http://www.biostat.wustl.edu/s-news/s-news-intro.html • This contains information on subscribing to S-news and sending messages to the list. • A searchable archive of recent messages is available at: http://www.biostat.wustl.edu/s-news/ • Modern Applied Statistics with S-PLUS Venables and Ripley : “The de facto "bible" of statistical analysis with S-PLUS”. This can be acce
Workshop steps • Vectors • Numeric, character • Sequences • Matrices • Plots • Scatter, box, histogram • Marsupial example (don’t worry about finishing this) # file:marsupial.code.txt. Written in R
