assocModelFitter.Rd
This function acts as a front-end for TASSEL's extensive association analysis methods. Using this function, users can run the following TASSEL association methods:
best linear unbiased estimates (BLUEs)
generalized linear model (GLM)
mixed linear model
Fast association (Shabalin 2012)
assocModelFitter(
tasObj,
formula,
fitMarkers = FALSE,
kinship = NULL,
fastAssociation = FALSE,
maxP = 0.001,
maxThreads = NULL,
minClassSize = 0,
outputFile = NULL,
biallelicOnly = FALSE,
appendAddDom = FALSE
)
An object of class TasselGenotypePenotype
.
An R-based linear model formula. The general layout of this
formula uses the following TASSEL data scheme:
<data> ~ <factor> and/or <covariate>
. If all traits in a Phenotype
object should be ran, a simplified formula (. ~ .
) can be used.
This scheme can also be used for running all <data>
or
<factor>
and/or <covariate>
data as well. Single variables
are separated witha +
operator. See vignette for further
clarification.
Should marker data be fitted? If TRUE
, GLM
analysis will be executed. If FALSE
, BLUEs will be calculated.
Defaults to FALSE
.
Should kinship data be accounted for in the model? If so,
a TASSEL kinship matrix object of class TasselDistanceMatrix
must
be submitted. Defaults to NULL
.
Should TASSEL's Fast Association plugin be used?
Consider setting to TRUE
if you have many phenotypes in your
data set.
Maximum p-value (0 - 1) to be reported. Currently works with
fast association only. Defaults to a p-value of 0.001
will be used as a threshold. Note: p-value parameter will
not be used for BLUE analysis.
Maximum threads to be used when running fast association.
If NULL
, all threads on machine will be used.
The minimum acceptable genotype class size. Genotypes in a class with a smaller size will be set to missing. Defaults to 0.
Output file prefix to be specified in case you want
to write data directly to disk. Highly recommended for large datasets.
If NULL
, no data will be saved to disk. If a character
Only test sites that are bi-allelic. The alternative is
to test sites with two or more alleles. Defaults to FALSE
If true, additive and dominance effect estimates will
be added to the stats report for bi-allelic sites only. The effect will
only be estimated when the data source is genotype (not a probability).
The additive effect will always be non-negative. Defaults to FALSE
.
Returns an R list containing DataFrame
-based data frames