run_sequoia: Run Sequoia pedigree/parentage assignment with snpR

In hemstrow/snpR: Whole-Genome Analysis Tools for Use with Single Nucleotide Polymorphism Data

Run Sequoia pedigree/parentage assignment with snpR

Description

Runs the parentage assignment and pedigree construction tool from the sequoia package. Note that this function is not overwrite safe!.

Usage

run_sequoia(
  x,
  facets = NULL,
  run_dupcheck = FALSE,
  run_parents = FALSE,
  run_pedigree = FALSE,
  run_relatives = FALSE,
  min_maf = 0.3,
  min_ind = 0.5,
  ...
)

Arguments

x	snpRdata object.
facets	character, default NULL. Sample-specific facets over which the sequoia is called to run. See Facets_in_snpR.
run_dupcheck	FALSE or TRUE, default FALSE. Uses sequoia to check for duplicate samples in the dataset. Duplicate samples should not be included for parentage and pedigree construction.
run_parents	FALSE or TRUE, default FALSE. Runs parentage assignments for the samples. This runs quickly and is required before using the run_pedigree command.
run_pedigree	FALSE or TRUE, default FALSE. Runs pedigree construction for the samples. This process can take a long time.
run_relatives	FALSE or TRUE, default FALSE. Runs retrieval of other relatives which did not pass thresholds for assignment in the main pedigree construction model.
min_maf	numeric in 0.25:0.5, default 0.3. Minimum allele frequency cutoff for analysis. Sequoia requires high minor allele frequencies for parentage and pedigree construction.
min_ind	numeric in 0.5:1, default 0.5. Removes loci sequenced in less than this proportion of individuals. Note that individuals with genotypes for fewer than half of the loci will be automatically removed by sequoia.
...	Additional arguments passed tosequoia (during parentage and pedigree reconstruction).

Details

This is a limited integration of the program and package written by Jisca Huisman. Note that there are many more Sequoia specific arguments that can be added to change from the default settings (eg. ErrorM, Tassign, Tfilt, etc.) See documentation for sequoia. These can be passed to the pedigree and parentage reconstructions using the ... argument in run_sequoia. The sequoia package has many features, and snpR facilitates the use of a fraction of them. snpR users are encouraged to use the sequoia R package.

Value

A nested list with each facet specified containing sequoia output summary information.

Author(s)

William Hemstrom

Melissa Jones

References

Huisman,J. (2017) Pedigree reconstruction from SNP data: parentage assignment, sibship clustering and beyond. Mol. Ecol. Resour., 17, 1009–1024.

Examples

# to follow an example using the stickSNPs example dataset you need 
# to add some variables that don't exist in the actual dataset.
a <- 2013:2015 #create a vector of possible birthyears
b <- c("M", "F", "U") #create a vector of possible sexes
stk <- stickSNPs
set.seed(4865)
sample.meta(stk)$BirthYear <- sample(x = a, size = nsamps(stickSNPs), 
                                     replace = TRUE) #create birth years
sample.meta(stk)$ID <- 1:nsamps(stk) #create unique sampleID
sample.meta(stk)$Sex <- sample(x= b, size = nsamps(stk), 
                               replace = TRUE) # create sexes

# slow, so not run here
## Not run: 
dup <- run_sequoia(x = stk, run_dupcheck = TRUE, run_parents = FALSE, 
                   run_pedigree = FALSE, run_relatives = FALSE)
ped <- run_sequoia(x = stk, run_dupcheck = FALSE, run_parents = TRUE, 
                   run_pedigree = TRUE, run_relatives = FALSE)
rel <- run_sequoia(x = stk, run_dupcheck = FALSE, run_parents = FALSE, 
                   run_pedigree = FALSE, run_relatives = TRUE)
                   

## End(Not run)

hemstrow/snpR documentation built on March 20, 2024, 7:03 a.m.