R-tutorial
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- Install R & RStudio on your home computer
- R from this website: https://mirrors.nics.utk.edu/cran/
- R studio from this website: https://www.rstudio.com/
- Create a new project by navigating: File | New Project | New Directory. Name it project file "genes"
- Import abalone data set: Tools | Import DataSet | From Web URL, copy & paste this address: http://diverge.hunter.cuny.edu/~weigang/data-sets-for-biostat/hg.tsv2
- Select "Yes" for column heading. Rename the data set if you wish (short but informative names, e.g., human.genes). Do not use spaces, use dot or underscore as name delimiters (e.g., "human.genes" or "human_genes", but never "human genes") Same rule for column or row names
hg.len <- hg$Gene.End - hg$Gene.Start + 1 # calculate gene length; access variables by pressing "Tab" (auto-completion)
hist(hg.len, br = 200) # plot gene-length distribution. Not normal: mostly genes are short, few very long
mean(hg.len) # not representative, super-long genes carry too much weight to the average length
median(hg.len) # More representative. Use median for a variable not normally distributed
summary(hg.len) # Show all quartiles
IQR(hg.len) # 3rd Quartile - 1st Quartile, the range of majority data points, even for skewed distribution
log.len <- log10(hg.len); hist(log.len, br=200) # Log of gene length is more normally distributed
mean(log.len); median(log.len) # They should be similar, since log.len is normal
boxplot(hg$Gene.End-hg$Gene.Start+1 ~ hg$Chromosome)
write.csv(hg, "hg.csv", row.names = FALSE) # save into a file
hg <- read.csv("hg.csv") # read back into R
boxplot(Gene.End - Gene.Start + 1 ~ Chromosome, data = hg) # show gene length by chromosomes- Export a PDF or image
- Open a new R script, name it as "hg.R"
- Select commands and save to script
- Retrieve and edit a command by pressing "up" or "down" arrows
- Retrieve commands by using the search box on the "History" table