R

I've been spending more and more time learning R because a lot of the statistical procedures used in bioinformatics are being made available (most times exclusively) via R and Bioconductor. As I keep learning more about R, I'm continually impressed with its capabilities and wondered why I didn't learn it earlier. Don't make the same mistake, learn R as soon as possible if you're serious about data analysis!

For those coming from a biological background (like myself) and want to learn R with respect to data analysis and visualisation of high throughput sequence data, have a look at the material presented at this course; I found it extremely useful. I have also written a short post on doing simple stuff in R. This book, Bioinformatics Data Skills, also has a nice chapter on getting started with R (among other bioinformatic topics).

You can click on the R tag, to retrieve most of my posts related to R. I say most because I'm sure I've forgotten to add the R tag to a few posts. Lastly, as with the rest of my site, I use this site as a learning tool for myself so please view everything with a grain of salt (and please let me know where I have erred!).

Must read

There are some must read articles available at the R Manuals page, such as "An Introduction to R" and "R Data Import/Export".

Links to R resources

A bunch of useful R commands that I've aggregated at my R wiki.

DataCamp for learning R interactively online.

swirl is a software package for the R statistical programming language. Its purpose is to teach users statistics and R simultaneously and interactively.

A course on data Analysis and visualisation course

Tutorials from Sean Davis

A Survival Guide to Data Science with R

Nice R Code

A gentle introduction to R

Some R packages that I have found useful

R

#Bioconductor packages
source("http://bioconductor.org/biocLite.R")
biocLite("ctc")
biocLite("edgeR")
biocLite("DESeq")
biocLite("baySeq")
biocLite("GO.db")
biocLite("GOstats")
biocLite("biomaRt")
biocLite("Ringo")
biocLite("ShortRead")
biocLite("org.Hs.eg.db")
biocLite("goseq")
biocLite("Rsamtools")
biocLite("GenomicRanges")
biocLite("IRanges")
#CAGE analysis
biocLite("CAGEr")
#R packages
install.packages("gplots")
install.packages("ggplot2")
install.packages("snow")
install.packages("RSvgDevice")
install.packages("reshape")
#text mining
install.packages("tm")
install.packages("wordcloud")
#Twitter related
install.packages("ROAuth")
install.packages("twitteR")
#analysing sequences
install.packages("seqinr")
#Enhanced data.frame
install.packages("data.table")
#For the Riemann's Zeta function
#http://rss.acs.unt.edu/Rdoc/library/VGAM/html/zeta.html
install.packages("VGAM")
#Nonlinear regression with R
install.packages("nlrwr")
#Analysis of dose-response curves
install.packages("drc")
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6 comments Add yours
    1. Hi Siewfong,

      Glad it helped! A PCA is not the easiest thing to grasp; sometimes I have to look back at the post to remind myself.

      Cheers,

      Dave

  1. 100 percent agree with you !
    R is pretty suitable for us who are biological background like you and me, help us to avoid taking a roundabout course both in our study and work .
    however, It's really not easy for most of us to learn it well by ourselves, we should keep practice and communicate with each other.
    I am lucky to see you blog, Thank you again .

    Call me Jimmy

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