| Title: | Iterative Pruning Population Admixture Inference Framework |
| Version: | 0.1.2 |
| Description: | A data clustering package based on admixture ratios (Q matrix) of population structure. The framework is based on iterative Pruning procedure that performs data clustering by splitting a given population into subclusters until meeting the condition of stopping criteria the same as ipPCA, iNJclust, and IPCAPS frameworks. The package also provides a function to retrieve phylogeny tree that construct a neighbor-joining tree based on a similar matrix between clusters. By given multiple Q matrices with varying a number of ancestors (K), the framework define a similar value between clusters i,j as a minimum number K* that makes majority of members of two clusters are in the different clusters. This K* reflexes a minimum number of ancestors we need to splitting cluster i,j into different clusters if we assign K* clusters based on maximum admixture ratio of individuals. The publication of this package is at Chainarong Amornbunchornvej, Pongsakorn Wangkumhang, and Sissades Tongsima (2020) <doi:10.1101/2020.03.21.001206>. |
| Depends: | R (≥ 3.5.0) |
| Imports: | stats,treemap,ape |
| URL: | https://github.com/DarkEyes/ipADMIXTURE |
| BugReports: | https://github.com/DarkEyes/ipADMIXTURE/issues |
| Language: | en-US |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| LazyData: | true |
| Suggests: | knitr, rmarkdown |
| VignetteBuilder: | knitr |
| RoxygenNote: | 7.3.2 |
| NeedsCompilation: | no |
| Packaged: | 2025-05-06 08:50:24 UTC; zero |
| Author: | Chainarong Amornbunchornvej
 [aut, cre] |
| Maintainer: | Chainarong Amornbunchornvej <grandca@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2025-05-06 09:50:01 UTC |
A list of Q matrices of simulation of 20 populations
Description
A dataset containing admixture ratios of 1200 individuals from 20 simulation populations where the number of ancestors ranges from 2 to 18. This dataset was the result of running LEA library developed by Frichot, E., & François, O. (2015). LEA: An R package for landscape and ecological association studies. Methods in Ecology and Evolution, 6(8), 925-929. on the 20-simulation-population dataset published by Limpiti, T., et al. (2014). iNJclust: iterative neighbor-joining tree clustering framework for inferring population structure. IEEE/ACM transactions on computational biology and bioinformatics, 11(5), 903-914.
Usage
UD1_Qmat
Format
A list of Q matrices of 1200 individuals from 20 populations. There are Q matrices that have the number of ancestors ranges from from 2 to 18.
- UD1_Qmat
It is list of Q matrices that contains admixture ratios of 1200 individuals from the 20-population dataset.
UD1_Qmat[[k]][i,j]is the admixture ratio of jth ancestor for ith individual in the (k+1)-ancestor Q matrix.
...
Labels of 20 simulation populations
Description
Labels of 20 simulation populations
Usage
UD1labels
Format
Labels of 20 populations. :
- UD1labels
It is a vector of labels of 1200 individuals. There are 20 populations.
...
biclustFunc function
Description
biclustFunc is a binary clustering function using hierarchical clustering.
Usage
biclustFunc(Qmat, admixRatioThs = 0.5, method = "average")
Arguments
Qmat |
is a Q matrix that contains admixture ratios of all individuals where the |
admixRatioThs |
is a threshold to determine that if a cluster has |
method |
is a method parameter of |
Value
This function returns binary clustering results.
heteroFlag |
is a flag that represents a status whether a given cluster is heterogeneous (having sub-clusters). It is TRUE if |
clusterInx |
is a vector of clustering assignment where |
meanDiffAdmixRatio |
is a vector of magnitude-difference of admixture ratios. It is calculated by splitting a given cluster into two sub-clusters. Then, we take the absolute on the difference between mean admixture ratios of sub-clusters. |
Qmat1 |
is a Q matrix of sub-cluster #1 after splitting a given cluster into two sub-clusters that contains admixture ratios of all individuals where the |
Qmat2 |
is a Q matrix of sub-cluster #2 after splitting a given cluster into two sub-clusters that contains admixture ratios of all individuals where the |
maxDiffAdmixRatio |
is a maximum of magnitude-difference of admixture ratios for a given cluster before splitting into two sub-clusters. |
Examples
# Running biclustFunc on Q matrix of 27 human population dataset where K = 12
obj<-biclustFunc(Qmat=ipADMIXTURE::human27pop_Qmat[[11]], admixRatioThs =0.15)
getPhyloTree
Description
getPhyloTree is function that reports a phylogenetic tree of clusters based on admixture analysis.
The phylogeny tree that construct a neighbor-joining tree based on a similar matrix between clusters.
By given multiple Q matrices with varying a number of ancestors (K), the framework define a similar value between clusters i,j as a minimum number K that makes majority of members of two clusters are in the different ancestor groups.
This K reflexes a minimum number of ancestors we need to splitting cluster i,j into different clusters if we assign K clusters based on maximum admixture ratio of individuals.
Usage
getPhyloTree(QmatList, indexClsVec)
Arguments
QmatList |
is list of Q matrix where |
indexClsVec |
is a vector of clustering assignment where |
Value
This function returns an object of nj tree as well as a matrix minDiffAncestorClsMat that is used as a similarity matrix.
tree |
is an object of nj tree calculated by ape::nj() function on a dissimilarity version of |
minDiffAncestorClsMat |
is a minimum-ancestor-number matrix in the group level where |
minDiffAncestorMat |
is a minimum-ancestor-number matrix in the individual level where |
Examples
# Running ipADMIXTURE on Q matrices (K=2-12) of 27 human population dataset.
h27pop_obj<-ipADMIXTURE(Qmat=ipADMIXTURE::human27pop_Qmat[[11]], admixRatioThs =0.15)
out<-ipADMIXTURE::getPhyloTree(ipADMIXTURE::human27pop_Qmat,h27pop_obj$indexClsVec)
plot(out$tree)
A list of Q matrices of 27 human populations
Description
A dataset containing admixture ratios of 544 individuals from 27 human populations where the number of ancestors ranges from 2 to 12. This dataset was the result of running ADMIXTURE software developed by Zhou, H., et al. (2011). A quasi-Newton acceleration for high-dimensional optimization algorithms. Statistics and computing, 21(2), 261-273. on the 27-human-population dataset published by Xing, J., Watkins, W. S. et al. (2009). Fine-scaled human genetic structure revealed by SNP microarrays. Genome research, 19(5), 815-825.
Usage
human27pop_Qmat
Format
A list of Q matrices of 544 individuals from 27 human populations. There are 2-12 ancestors in the list.
- human27pop_Qmat
It is list of Q matrices that contains admixture ratios of 544 individuals from the 27 population human dataset.
human27pop_Qmat[[k]][i,j]is the admixture ratio of jth ancestor for ith individual in the (k+1)-ancestor Q matrix.
...
Labels of 27 human populations
Description
Labels of 27 human populations
Usage
human27pop_labels
Format
Labels of 27 human populations. :
- human27pop_labels
It is a vector of labels of 544 individuals. There are 27 populations.
...
Iterative Pruning Population Admixture Inference Framework (ipADMIXTURE)
Description
A data clustering package based on admixture ratios (Q matrix) of population structure.
The framework is based on iterative Pruning procedure that performs data clustering by splitting a given population into subclusters until meeting the condition of stopping criteria the same as ipPCA, iNJclust, and IPCAPS frameworks. The package also provides a function to retrieve phylogeny tree that construct a neighbor-joining tree based on a similar matrix between clusters. By given multiple Q matrices with varying a number of ancestors (K), the framework define a similar value between clusters i,j as a minimum number K that makes majority of members of two clusters are in the different clusters. This K reflexes a minimum number of ancestors we need to splitting cluster i,j into different clusters if we assign K clusters based on maximum admixture ratio of individuals.
Usage
ipADMIXTURE(Qmat, admixRatioThs, method = "average")
Arguments
Qmat |
is a Q matrix that contains admixture ratios of all individuals where the |
admixRatioThs |
is a threshold to determine that if a cluster has |
method |
is a method parameter of |
Value
This function returns clustering results in a form of an object of ipADMIXTURE class. The object contains the following items.
indexClsVec |
is a vector of clustering assignment where |
homoClusters |
is a list of cluster objects where each object contains member indices, cluster's |
maxDiffAdmixRatioVec |
is a vector of |
Qmat |
is a Q matrix that contains admixture ratios of all individuals where the |
admixRatioThs |
is a threshold to determine that if a cluster has |
Author(s)
Chainarong Amornbunchornvej, chai@ieee.org
Examples
# Running ipADMIXTURE on Q matrix of 27 human population dataset where K = 12
h27pop_obj<-ipADMIXTURE(Qmat=ipADMIXTURE::human27pop_Qmat[[11]], admixRatioThs =0.15)
plotAdmixClusters
Description
plotAdmixClusters is function that plots admixture ratios where the x axis represents individuals with cluster labels and y axis represents admixture ratios.
Usage
plotAdmixClusters(obj)
Arguments
obj |
is an object of ipADMIXTURE class. |
Examples
h27pop_obj<-ipADMIXTURE(Qmat=ipADMIXTURE::human27pop_Qmat[[11]], admixRatioThs =0.15)
ipADMIXTURE::plotAdmixClusters(h27pop_obj)
plotClusterLeaves
Description
plotClusterLeaves is function that plots clusters in a form of treemap plot. Subsquares represent clusters. Each subsquare contains cluster label (ID), number of members (N), and a maximum of manitude-difference of admixture ratios (md). A size of each subsquare represents a ratio of member numbers compared to other clusters. A color represents an md value of cluster.
Usage
plotClusterLeaves(obj)
Arguments
obj |
is an object of ipADMIXTURE class. |
Examples
h27pop_obj<-ipADMIXTURE(Qmat=ipADMIXTURE::human27pop_Qmat[[11]], admixRatioThs =0.15)
ipADMIXTURE::plotClusterLeaves(h27pop_obj)
printClustersFromLabels
Description
printClustersFromLabels is function that reports that clustering results in text mode.
Usage
printClustersFromLabels(obj, labels)
Arguments
obj |
is an object of ipADMIXTURE class. |
labels |
is a vector of labels of all individuals. |
Examples
h27pop_obj<-ipADMIXTURE(Qmat=ipADMIXTURE::human27pop_Qmat[[11]], admixRatioThs =0.15)
ipADMIXTURE::printClustersFromLabels(h27pop_obj,ipADMIXTURE::human27pop_labels)