How to analyze percent data when most of the data is 0%? I have a set of percent data on histological abnormalities in fish gills and I need to compare the results between two sites A and B. We analyzed abnormalities in lamellae of a particular gill arch. For example for fish 1 we counted 500 lamellae and noted the number that had abnormality Y. The majority of the data is 0%. That is, in most fish, the lamellae counted had no such abnormality present. Obviously when I try different transformations the distribution does not change because of all the 0s (I have attached a graph of the distribution of the data). I do not know how to analyze this data. 

 A: It seems like you'd want to convert it to a binary variable (mutations vs not), then compare frequencies between sites with Logistic Regression or similar.
A: Fish are measurement units. Each fish has own total. Proportions may be modeled by the beta distribution. In particular this data may be modeled with the beta[0,1) distribution; where 0 is included and 1 is not. Analysis can proceed in to steps:
1) Estimate the proportions of 0s and >0 by a finite mixture. See SAS manual for the FMM procedure. For a similar case I used this code:
proc fmm data=ddd componentinfo technique=trureg;
   class case;
   model percent = case / noint dist=beta k=1;
   model         +  /  dist=constant k=2;
   probmodel ;
   run;
Instead of k=2, you might need to use k=1.
2) Using DOI: 10.1037/1082-989X.11.1.54 and these 2 references you would be able to ascertain differences among sites:
http://support.sas.com/resources/papers/proceedings11/335-2011.pdf
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.470.7064&rep=rep1&type=pdf
Also (not tested) could use module 'metamix' for STATA or Package ‘zoib’ in R
