pooledpeaks is designed for analyzing genetic data obtained from
Fragment Analysis output files (.fsa
) of pooled biological
samples. It provides functions for a comprehensive analysis pipeline
from processing .fsa
files, to cleaning the peak data, and
conducting population genetic analyses. Some features are listed below
and a usage example of the entire pipeline is included as a vignette.
Please check out the Contributing
Guidelines for information on how to add to this package.
You can install the package directly from GitHub using the following instructions:
Open R and copy the following code into your console
install.packages("devtools")
::install_github("kmkuesters/pooledpeaks") devtools
install.packages("pooledpeaks")
For a detailed example of how to apply the functions contained in
this package please see the Introduction
to Using the pooledpeaks Workflow. Example data can be found on
GitHub under the inst/extdata folder including .fsa
files
and a formatted “Multiplex_frequencies.txt” file for the Genetic
Analysis portion.
.fsa
files and
score peaks contained therein.check_fsa_v_batch()
fsa_metadata()
fsa_batch_imp()
associate_dyes()
score_markers_rev3()
clean_scores()
lf_to_tdf()
data_manipulation()
Rep_check()
PCDM()
LoadData()
Population Genetics Analysis:
Calculate Gene Identity Matrix and Genetic Distance Matrix
Calculate diversity indices
Calculate differentiation indices
Perform cluster analysis
TypedLoci()
GeneIdentityMatrix()
GeneticDistanceMatrix()
GST()
JostD()
cluster()
MDSplot()
The sample .fsa
files included in this package are
provided for demonstration purposes and originate from two sources:
pooledpeaks
workflow. These
data contain no identifiable or human subject information.These files are intended solely to demonstrate the functionality of
the pooledpeaks
package and are not for diagnostic or
clinical use.To access the example .fsa
files included with
the package, use the following path within R:
system.file("extdata", package = "pooledpeaks")
The pooledpeaks package was developed by the Blanton Lab as part of Kathleen Kuesters’ dissertation.