RNA-seq, end to end

The same in R →

A notebook, not a graded lab: run the cells in order, then change anything you like and run it again. The Python kernel keeps its state between cells, exactly like Jupyter, so a variable you define up here is still around further down. Press Ctrl/Cmd + Enter to run a cell.

Start by loading the counts table for six genes across two samples.

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The treated sample was sequenced deeper, so normalise to counts per million before comparing anything.

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Now the honest comparison: which genes truly rose in the treated sample?

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And the picture: a fold-change bar chart, teal up and rose down.

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