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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/