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Canadian Bioinformatics Workshops Series
Toronto, May 20 2015
Introduction to R
Faculty: Boris Steipe boris.steipe@utoronto.ca
Module 3: Data Analysis
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“for” loop
convert columns to numeric
str(sup3)
str(sup3[,2])
sup3[ ,2] <- as.numeric(sup3[ ,2])
for (i in 1:10) {
print(i*i)
}
for (i in 2:ncol(sup3)) {
sup3[,i] <- as.numeric(sup3[ ,i])
}
Filtering data
Task: find the top 30 most differentially enriched
genes in the Mo cells. Hint: you will need to sort
results … but sort() is not the function you need,
you need order().
Then find the same for Mf cells.
Then find the union of the two sets. Plot the differential enrichment of one against the other.
Basic plots and slightly more advanced plots
Task: Plot boxplots for the different cell-types, then plot the actual values of requested genes.
Task: show the differential expression as a barplot.
Barplots are bad. Improve according to Weissgerber et al.’s ideas
More plotting topics
Integrating data
Task:
1 - For the top 10 Monocy.
2 - translate their gene symbols to Entrez IDs using http://biodbnet.abcc.ncifcrf.gov/
3 - see whether they are co-expressed (i.e. presumably coregulated) at http://coxpresdb.jp/