edited readme

README.md

@@ -48,6 +48,29 @@ You can install `litterDiallel` using the following steps. First, please make su
     browseVignettes("litterDiallel")
     ```
 
+## Analysis Summary
+
+The included data file, `litter-diallel.csv`, has the following column names, where each of 4,448 observed litters is represented by a single row. All counts represent animals that are observed at the time of weaning (~ 3 weeks after birth):
+
+- `Dam_Founder` (factor): The inbred mouse strain name of the female parent, where the following abbreviations are used: A/J (AJ), C57BL/6J (B6), 129S1/SvImJ (129S1), NOD/ShiLtJ (NOD), NZO/HlLtJ (NZO), CAST/EiJ (CAST), PWK/PhJ (PWK), and WSB/EiJ (WSB).
+- `Sire_Founder` (factor): The inbred mouse strain name of the male parent.
+- `PupGeno` (factor): The strain-cross name of the F1 offspring, given as their dam-by-sire cross (strainDam x strainSire).
+- `WeanDate` (factor): The date (DD/MM/YY) that animals were weaned into new cages and separated from their parents. 
+- `YearMonth` (factor): The date (YearMonth-YYYY-MM) of weaning.
+- `litterorder` (factor): The parity, or litter birth order based on dam, is provided as a factor.
+- `litternum` (integer): The litter number (litterorder - 1) is provided as an integer, where the first litter is 0, and each subsequent litter is numbered starting at 1.
+- `First_Litter` (integer): A binary variable taking the values 0 or 1, indicating whether it is the first litter born to the given dam.
+- `Males` (integer): The number of male pups in the litter.
+- `Females` (integer): The number of female pups in the litter.
+- `Weaned` (integer): The total number of (male and female) pups in the litter.
+- `Male_Prop` (numeric): The proportion of male pups to overall pups in the litter.
+
+The order of the columns in the data set does not matter.
+
+We use the functions `diallelMatrixMaker` and `diallelMatrixMakeAndRotate` to generate design matrices for modeling the different classes of effects. After reading in the data, these functions expect: the name of the data frame object, the dam column name, the sire column name, and two random effect (`batch`, `batch.1`) column names. 
+
+We then the `MCMCglmm` function from the [`MCMCglmm` package](https://github.com/cran/MCMCglmm) (version 2.25) to analyze our data by fitting (generalized) linear mixed models, including the overdispersed zero-truncated Poisson, binomial, or Gaussian model.
+
 ## Notes
 
 - [ ] For the model inclusion probability analysis, BayesDiallel and BayesSpike must be installed. The instructions are [here](http://valdarlab.unc.edu/software/bayesdiallel/BayesDiallel.html).