You write your ggplot2 code as if you were putting all of the data onto one plot, and then you use one of the faceting functions to indicate how to slice up the graph. There are two main facet functions in the ggplot2 package: facet_grid(), which layouts panels in a grid. It crea...
In the below code, We will build three different histograms using the R’s in-built dataset iris and then assign one by one to an R object. Finally, we will use cowplot functionplot_grid()to combine the two plots of our interest. #building the first plot plot_histogram_SL <- ggplot(...
information into the message string, it should be easier to add details you care about. check_input() is now one of the helper functions in helper-functions.R. Error messages are hard to write well, and it's great that you've included some good input checking! I think you could make ...
Now, the level of significance into play to decide if we can allow 2% or p-value of 0.02. It can be said as a level of endurance of the null hypothesis. If our level of significance is 5% using a two tailed test, we can allow 2.5% on both ends of the distribution, we accept th...
For the gene expression analysis, pretreatment FFPE whole tissue sections from the 59 melanoma patients included in YTMA 376 were employed. Two slides from each patient were macrodissected and RNA was extracted. The mRNA transcripts were hybridized to 4-color, 6-spot optical barcodes, exclusive fo...
R and Excel go together like macaroni and cheese. There’s no need to choose one over the other, as there are numerous packages and extensions that allow them to work together. Just because you have an xlsx file doesn’t mean you can’t analyze it with R
return(transform(out,s=arclength/max(arclength))) ## If there are more variables we can enter into the regression, ## then see which one will cross the highest correlation line ## first, and record the alpha value of where the lines cross. ...
created to more easily implement DEB theory to animals. The major difference with the standard DEB model is the absence of a reserve compartment before separation into the two functional branches (i.e. κ split). The model used here is schematically represented inFig. 1and the parameters and ...
do the last two steps together. sapply(count_by_spray, mean) vapply(count_by_spray, mean, numeric(1)) We can do even better than that however. tapply, aggregate and by all provide a one-function solution to these S-A-C problems. with(InsectSprays, tapply(count, spray, mean)) ...
If you prefer making visualizations using the package ggplot2 , we recommend converting the data from "SpatialPointsDataFrames" to "sf" objects. #convert the object EX1 into an sf object named EX1sf library(sf) EX1sf<-st_as_sf(EX1) #plot the data using geom_sf and the ggplot2 default ...