Commit f2f7610c authored by Vallo Varik's avatar Vallo Varik
Browse files

Add third task

parent 5127a271
......@@ -23,10 +23,6 @@ steps is visualization i.e. making graphs.
## Explore
1. Plot growth curves following raw OD in time. [Input
data](doc/tasks/01_dat.csv) and [expected output](doc/tasks/01_out.pdf)
plot are provided. The data is for azithromycin
against _S. flexneri_ M90T from day 2022-05-04 (first replicate). _A tip: Use `facet_wrap` with `ncol = 1` argument to have different concentrations on separate plots._
1. Plot growth curves following raw OD in time. Input
[data](doc/tasks/01_dat.csv) and expected [output](doc/tasks/01_out.pdf)
plot are provided. The data is for azithromycin against _S. flexneri_ M90T
......@@ -35,8 +31,13 @@ steps is visualization i.e. making graphs.
2. Try again, now with [data](doc/tasks/02_dat.csv) from two days (let us plot
days in different color). In addition, transform the y-axis to logarithmic
scale. [Expected output](doc/tasks/02_out.pdf). _A tip: you need to turn
the `Date` variable into a factor.`
scale. Expected [output](doc/tasks/02_out.pdf). _A tip: you need to turn
the `Date` variable into a factor._
3. Once more, now with [data](doc/tasks/03_dat.csv) from three days. Expected
[output](doc/tasks/03_out.pdf). You will encounter an issue because there
were two biological replicates on that day. There are multiple ways to
overcome this, but for now, I recommend to solve by issuing `group =
WellID` to `aes` of `ggplot`.
overcome this, but for now, I recommend to solve by using `group` parameter
of `aes` e.g. `ggplot(aes(..., group = Plt))`.
......@@ -23,3 +23,10 @@ both steps is visualization i.e. making graphs.
to logarithmic scale. Expected [output](doc/tasks/02_out.pdf). *A
tip: you need to turn the `Date` variable into a factor.*
3. Once more, now with [data](doc/tasks/03_dat.csv) from three days.
Expected [output](doc/tasks/03_out.pdf). You will encounter an issue
because there were two biological replicates on that day. There are
multiple ways to overcome this, but for now, I recommend to solve by
issuing `group = WellID` to `aes` of `ggplot`.
using `group` parameter of `aes`
e.g. `ggplot(aes(..., group = Plt))`.
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