Is there any way to analyze the data within a GEOSoft file, from NCBI, in R? I've tried converting it to an expression set, fitting it with lmFit(), then using eBayes(), but when I use topTable() to look at the results, the adjusted P.Values are always constant throughout the column.
Any help, or even pointing in the right direction would be greatly appreciated.
Thank you so much in advance
Related
I just calculated several t-tests in R and would like to present them in a clearly arranged table. Does anyone know how to create a "result table"? Thank you!
haven't tried anything so far. Doesn't know the code and in general, i have barely knowledge about R.
I am trying to run stamppFst() and stamppConvert() with haplotype data. The data I have is a squence of nucleotides in a DNAbin. I have tried to find ways to turn it into a matrix but what I have read goes way over my head since this is the first time I have ever used R.
data
This is an example of one of the data sets I want to use.
I apologize if this is a very basic question. Thanks for any help!
I'm very new to R and pretty basic with analyses generally. I successfully ran a regression in R, but a lot of my data are missing. I'm fine with that because R just ignores the missing observations in the analyses and shows me the dfs in the summary. My problems is that I'd like to look more into the observations that are included in the analyses, but I'm not sure how to do that.
I tried to do na.omit, but R created a dataset with far fewer observations than it used in the regressions, so I think that takes it too far.
Basically, I'm trying to get the ages for the respondents that were included in the final analyses, not just the ages of the entire sample, many of whom were not included in the analyses.
Any advice you can give me would be very appreciated!! Please let me know if you need more information.
Thank you!
Edited to include Screenshot of data.
Cannot run an ICC analysis in R
I have loaded my data from excel spreadsheet and have tried the following:
ICC(CMI)
I have removed my row names. I am not sure if I need to convert my columns or use a difference approach. I have loaded the Psych package.
This is my code: ICC(Test)
This is what comes back:
Error in stack.data.frame(x) : no vector columns were selected
Not sure of what this means or how to fix this? Thanks in advance for any help. I really appreciate it.
I had the same problem with a dataset. I suggest you try:
ICC(as.matrix(Test))
. This worked for me. Otherwise, type help(ICC) and check the example and compare the procedure used there compared to your data.
Good luck!
I have a data set which contains 163 columns(variable) and 199566 rows(data).
So How can i eleminate redundant data ?
Can i do this by using normal distribution?
Maybe try dimensionality reduction methods such as PCA. It will help you reduce the amount of columns as if I understand correctly is what you want to achieve.
If you haven't used them before, you will probably have to read more about what these techniques exactly do but the above will get you started.