I hope that you are doing well. I am currently trying to replicate a type of isotope plot that's common in my field. Essentially, it's the result of a compound-specific stable isotope analysis.
The x and y axes represent delta values that are plotted against isotopic references from animals (ellipses) to identify animals by their signature. The ellipses represent a 95% CI.
I'm a beginner in R. I've managed to get the scatter plot to work, but I don't understand how to create a CI ellipses with reference data. Would anyone here know how to do this?
enter image description here
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I have a fair amount of experience analyzing RNA-Seq data, but I am looking for new ways to visualize the data. I typically use heat maps and volcano plots, but I'd like to make this plot which is from this paper. I can make this type of plot with rlog transformed data before doing DEG analysis, but I want to color dots based on statistically significant expression differences.
I've search online and have not been able to find a good way to create this plot. Thanks in advance for any advice.
This question is more about bioinformatics so maybe it is better you can post it on biostar.
In any case, maybe you can draw a scatter plot with the package "ggscatter" or "ggplot2" and colour the statistically significant gene with an if else statement.
Please, provide sample of your data.
I've come up with a graph (a scatterplot) of the log(1+inf) (inf = number of people infected with a given disease on the y-axis against one of the explanatory variables, in this case, the populational density (pop./km²; x-axis) on my model. The log transformation was used merely for visualization, because it spreads the distribution of the data and allows for more aesthetically appealing plots. Basically, what I want is both axis to show the value of that same variable before the log transformation. The dots need to be plotted like plot(log(1+inf),log(populational_density), but the number on the axis should refer to plot(inf,populational_density). I've provided a picture of my graph with some manual editing on the y-axis to show you the idea of what I want.
The numbers in red would be the 'inf' values equivalent to log(inf);
Please, bear in mind that those values in red do not correspond to reality.
I understand the whole concept of y = f(x), but i've been asked to provide it. Is this possible? I'm using the ggplot2package for plotting.
I have gone through few tutorials and answers here in stackoverflow such as:
Overlap image plot on a Google Map background in R or
Plotting contours on an irregular grid or Geographical heat map of a custom property in R with ggmap or How to overlay global map on filled contour in R language or https://blog.dominodatalab.com/geographic-visualization-with-rs-ggmaps/
They either don't serve my purpose or consider the density of the data to create the image.
I am looking for a way to plot contour on a map of a certain data, and would expect the image to look something like this:
or something like this taken from https://dsparks.wordpress.com/2012/07/18/mapping-public-opinion-a-tutorial/:
I have a data here that gives a contour plot like this in plot_ly but i want this over the map given by latitudes and longitudes.
Please guide me on how this can be done. Any links to potential answers or codes would be helpful.
Ok I did some digging and figured that to plot the data -which in this case are point values randomly distributed across the Latitude and Longitude, one has to make it continuous instead of the discreetly distributed one. To do this I interpolated the data to fill in the gaps, this method is given in Plotting contours on an irregular grid and then take it from there. Now the interpolation here is done using a linear regression, one can use other methods such as IDW, Kriging, Nearest Neighbourhood etc for which R-packages are easily available. These methods are widely used in climatology and topographic analysis. To read more about interpolation methods see this paper.
I have a set of data that I'm trying to create a surface plot of. I have an x,y point and a to colour by.
I can create a xy plot with the points coloured but I can't find a way to create a surface plot with my data. The data isn't on a normal grid and I would prefer to not normalize it if possible (or I could just use a very fine grid).
The data won't be outside the a radius=1 circle so this part would need to be blank.
The code and the plot is shown below.
I've tried using contour, filled.contour as well as surface3d (not what I wanted). I'm not real familiar with many packages in R so I'm not even sure where to begin looking for this info.
Any help in creating this plot would be appreciated.
thanks,
Gordon
dip<-data.frame(dip=seq(0,90,10))
ddr<-data.frame(ddr=seq(0,350,10))
a<-merge(dip,ddr)
a$colour<-hsv(h=runif(nrow(a)))
degrees.to.radians<-function(degrees){
radians=degrees*pi/180
radians
}
a$equal_angle_x<-sin(degrees.to.radians(a$ddr))*tan(degrees.to.radians((90-a$dip)/2))
a$equal_angle_y<-cos(degrees.to.radians(a$ddr))*tan(degrees.to.radians((90-a$dip)/2))
plot(a$equal_angle_x,a$equal_angle_y,col=a$colour,lwd=10)
With regards to the plot I was trying to create is below. I believe the link in the first comment should get me where I'm trying to go.
I have a very basic grasp of stats, and a very basic grasp of R so please bear with me.
I have survey data which shows the weekly expenditure of a number of respondents. I have put this into a histogram, and have plotted a density function as well. So far so good.
How do I then apply this curve to a larger population? Say that I know that the population of my town is 25000. How can I apply that to the density curve to arrive at a new histogram and the data table behind it?
I hope this is an appropriate question, thank you.
It is not exactly clear what you want to do.
If you only have data on the sample then the best estimate that you have of the histogram/density for the population is the histogram/density of the sample, the only difference would be the scale on the y-axis. Personally I think the tick marks on the y axis should be ignored (and my preference would be that the tick labels were never plotted) since it is really the shape of the histogram/density that is important and the tick labels can change based on things that don't change the meaning. If you really feel the need to have the tick labels represent population values then see the axis function.
If you want something more than this then give us a better description of what you are trying to accomplish.