Dealing with NAs in genomic data statistics I have done a GC content (counting C and G in genomes) and GC variation within genomes, in a slide-window (1000 pb-base pairs). I have each genomic data separated in tsv files. When I work with pandas and merge all data by columns, I got a lot of lines with NAs because each species has a different genome size. Pandas works well with this data, because I have means and all other statistics working fine, I can even plot the data with no problem.
But my doubt is this, I can keep the data merged as it is or it is BETTER (statistically speaking) to drop all lines with NAs?
I ask that because I would like to use R, but I cant merge the data because R complains about the different column sizes.
Any tip or commentary about this subject would be very appreciate! Even a good reading about the subject.
Thank you all by your time.
Paulo

Is this actually a missing data problem?
Technically, missing values are values we could have observed but didn't get recorded for one reason or another. (The reason for the missingness is crucial as data can be omitted in a biased way, eg, wealthier households may be less likely to report their income.)
However, in you case species have different genome size because they have evolved differently. (I have only basic knowledge of biology but I read a bit about genome size in Wikipedia.)
So if a species has lost or gained a gene (a chromosome?), the gene isn't really missing and there is nothing to be imputed. To align the genomic data for multiple species, you can replace the NA's with 0s or perhaps -1s.
The important question is how does the analysis take into consideration the fact that not all species have all the same genes. This is a science question (how to align and compare genomes with different size) or perhaps a data structure question (how to put together sequences of different length), not a statistics question.
