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In the ‘2.Setup’ section, you downloaded 3 nfcore/sarek runs to H:/workshop/sarek/runs. These represent sarek variant calling results from the 3 exercises run in session 2:

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SNPeff creates its own variant analysis reports (html reports) for each sample, which can be seen here:

H:/workshop/sarek/runs/run2_trio/results/reports/snpeff/haplotypecaller

We’ll be creating our of reports, with some additional functional information, using R.

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Click ‘Knit’ to generate the report. It will ask you to name the file and ask where to save the file. Call it ‘test’ and save it in H:/workshop

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You will see it generates the test html report.

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To do this we will use the R clusterProfiler package, which examines enrichment of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and Gene Ontology (GO) terms, based on a set of input genes. In this case, the genes associated with the SNPeff variants.

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Creating the

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report

The R script and R Markdown scripts have already been created, so you’ll just need to open them in RStudio.

In RStudio, select ‘File’ → “Open File”

Browse to H:/workshop/sarek/runs/run3_liver

Select the ‘modify.R’ file and click ‘Open’.

Open the ‘function_report.Rmd’ file in the same way (it’s in the same location as modify.R)

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To run the scripts, you just need to change/update (and run) 3 lines in the modify.R file.

These are:

• Line 8: setwd("H:/workshop/sarek/runs/run3_liver")

This sets the working directory you want to run the analysis from. This needs to be the same directory where you ran your sarek script from, i.e. where the sarek ‘results’ directory is.

IMPORTANT: while the modify'R script can be run from anywhere, you'll need to copy the function_report.Rmd script to this working directory, because that R markdown script calls to subdirectories from its location.

• Line 69: maingroup <- "C1"

This tells the script which sample to run the analysis on. Choose a sample from the list of available samples (which are shown if you run the line above this: dir("./results/reports/snpeff/haplotypecaller/"))

• Line 78: variant_type <- "variants_impact_HIGH"

This tells the script which category of variant results you want to analyse. SNPeff groups results by ‘impact’ and variety of other categories. To see which categories you can analyse, run the three lines above the ‘variant_type’ line:

library(data.table)

genetable <- fread(paste0("./results/reports/snpeff/haplotypecaller/", maingroup, "/", maingroup, ".haplotypecaller.filtered_snpEff.genes.txt"), skip = 1, stringsAsFactors = F)

gsub("variants_effect_", "", colnames(genetable))[5:length(colnames(genetable))]

Now just run the rmarkdown::render(.... line to automatically generate the report.

You will now see the HTML report in the working directory you defined in setwd(...). This is a single file, a self-contained report with all the tables and figures you added to it. It can be opened in a web browser, emailed to colleagues or published as a web page.