R package citation, R package reverse dependencies, R package scholars, install an r package from GitHub hy is package acceptance pending why is package undeliverable amazon why is package on hold dhl tour packages why in r package r and r package full form why is r free why r is bad which r package to install which r package has which r package which r package version which r package readxl which r package ggplot which r package fread which r package license where is package.json where is package-lock.json where is package.swift where is package explorer in eclipse where is package where is package manager unity where is package installer android where is package manager console in visual studio who r package which r package to install which r package version who is package who is package deal who is package design r and r package full form r and r package meaning what r package has what package r what is package in java what is package what is package-lock.json what is package in python what is package.json what is package installer do r package can't install r packages r can't find package r can't load package can't load xlsx package r can't install psych package r can't install sf package r Write if else in NONMEM pk pd
asmbPLS
View on CRAN: Click
here
Download and install asmbPLS package within the R console
Install from CRAN:
install.packages("asmbPLS")
Install from Github:
library("remotes")
install_github("cran/asmbPLS")
Install by package version:
library("remotes")
install_version("asmbPLS", "1.0.0")
Attach the package and use:
library("asmbPLS")
Maintained by
Runzhi Zhang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-04-17
Latest Update: 2023-04-17
Description:
Adaptive Sparse Multi-block Partial Least Square, a supervised algorithm, is an extension of the Sparse Multi-block Partial Least Square, which allows different quantiles to be used in different blocks of different partial least square components to decide the proportion of features to be retained. The best combinations of quantiles can be chosen from a set of user-defined quantiles combinations by cross-validation. By doing this, it enables us to do the feature selection for different blocks, and the selected features can then be further used to predict the outcome. For example, in biomedical applications, clinical covariates plus different types of omics data such as microbiome, metabolome, mRNA data, methylation data, copy number variation data might be predictive for patients outcome such as survival time or response to therapy. Different types of data could be put in different blocks and along with survival time to fit the model. The fitted model can then be used to predict the survival for the new samples with the corresponding clinical covariates and omics data. In addition, Adaptive Sparse Multi-block Partial Least Square Discriminant Analysis is also included, which extends Adaptive Sparse Multi-block Partial Least Square for classifying the categorical outcome.
How to cite:
Runzhi Zhang (2023). asmbPLS: Predicting and Classifying Patient Phenotypes with Multi-Omics Data. R package version 1.0.0, https://cran.r-project.org/web/packages/asmbPLS. Accessed 21 Nov. 2024.
Previous versions and publish date:
No previous versions
Other packages that cited asmbPLS R package
View asmbPLS citation profile
Other R packages that asmbPLS depends,
imports, suggests or enhances
Complete documentation for asmbPLS
Functions, R codes and Examples using
the asmbPLS R package
Some associated functions: asmbPLS-package . asmbPLS.cv . asmbPLS.example . asmbPLS.fit . asmbPLS.predict . asmbPLSDA.cv . asmbPLSDA.example . asmbPLSDA.fit . asmbPLSDA.predict . asmbPLSDA.vote.fit . asmbPLSDA.vote.predict . mbPLS.fit . meanimp . plotCor . plotPLS . plotRelevance . quantileComb . to.categorical .
Some associated R codes: KM.estimator.R . RcppExports.R . asmbPLS.cv.R . asmbPLS.example.R . asmbPLS.fit.R . asmbPLS.predict.R . asmbPLSDA.cv.R . asmbPLSDA.example.R . asmbPLSDA.fit.R . asmbPLSDA.predict.R . asmbPLSDA.vote.fit.R . asmbPLSDA.vote.predict.R . mbPLS.fit.R . meanimp.R . plotCor.R . plotPLS.R . plotRelevance.R . quantileComb.R . to.categorical.R . Full asmbPLS package functions and examples
Downloads during the last 30 days
Get rewarded with contribution points by
helping add
Reviews / comments / questions /suggestions ↴↴↴
Today's Hot Picks in Authors and Packages
RcppHNSW
'Hnswlib' is a C++ library for Approximate Nearest Neighbors.
This package provides a minimal R int ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: James Melville (view profile)
kgschart
Restore underlining numeric data from rating history graph of
KGS (an online platform of the game o ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Kota Mori (view profile)
r2resize
Automatic resizing toolbar for containers, images and tables. Various resizable or expandable contai ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Obinna Obianom (view profile)
SCBiclust
Identifies a bicluster, a submatrix of the data such that the features and observations within the s ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Erika S. Helgeson (view profile)
crossrun
Joint distribution of number of crossings and the
longest run in a series of independent Bernoulli ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Tore Wentzel-Larsen (view profile)
pkgdepends
Find recursive dependencies of 'R' packages from various
sources. Solve the dependencies to obtain ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Gábor Csárdi (view profile)