Package: INDEED 2.19.0

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INDEED: Interactive Visualization of Integrated Differential Expression and Differential Network Analysis for Biomarker Candidate Selection Package

An R package for integrated differential expression and differential network analysis based on omic data for cancer biomarker discovery. Both correlation and partial correlation can be used to generate differential network to aid the traditional differential expression analysis to identify changes between biomolecules on both their expression and pairwise association levels. A detailed description of the methodology has been published in Methods journal (PMID: 27592383). An interactive visualization feature allows for the exploration and selection of candidate biomarkers.

Authors:Yiming Zuo <[email protected]>, Kian Ghaffari <[email protected]>, Zhenzhi Li <[email protected]>

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# Install 'INDEED' in R:

install.packages('INDEED', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ressomlab/indeed/issues

Datasets:

Met_GU - GU cirrhosis (CIRR) and GU Hepatocellular carcinoma (HCC) data.
Met_Group_GU - Group label.
Met_name_GU - KEGG ID
pvalue_M_GU - P-values obtained by differential expression (DE) analysis.

On BioConductor:INDEED-2.19.0(bioc 3.20)INDEED-2.18.0(bioc 3.19)

bioconductor-package

4 exports 1.00 score 101 dependencies 3 mentions

Last updated 2 months agofrom:25eda6b02a

Exports:network_display non_partial_cor partial_cor select_rho_partial

Dependencies:askpass base64enc brew brio bslib cachem callr cli clipr commonmark cpp11 crayon credentials curl desc devtools diffobj digest downlit ellipsis evaluate fansi fastmap fontawesome fs gert gh gitcreds glasso glue highr htmltools htmlwidgets httpuv httr httr2 igraph ini jquerylib jsonlite knitr later lattice lifecycle magrittr Matrix memoise mime miniUI openssl pillar pkgbuild pkgconfig pkgdown pkgload praise prettyunits processx profvis promises ps purrr R6 ragg rappdirs rcmdcheck Rcpp rematch2 remotes rlang rmarkdown roxygen2 rprojroot rstudioapi rversions sass sessioninfo shiny sourcetools stringi stringr sys systemfonts testthat textshaping tibble tinytex urlchecker usethis utf8 vctrs visNetwork waldo whisker withr xfun xml2 xopen xtable yaml zip

INDEED R package for cancer biomarker discovery

Yiming Zuo and Kian Ghaffari

Rendered fromIntroduction_to_INDEED.Rmdusingknitr::rmarkdownon Jun 21 2024.

Last update: 2019-09-26
Started: 2018-07-31

Help page	Topics
Draw error curve	choose_rho
Compute the correlation	compute_cor
Calculate the differential network score	compute_dns
Compute the partial correlation	compute_par
INDEED: A network-based method for cacner biomarker discovery.	INDEED-package INDEED
Create log likelihood error	loglik_ave
Group label.	Met_Group_GU
GU cirrhosis (CIRR) and GU Hepatocellular carcinoma (HCC) data.	Met_GU
KEGG ID	Met_name_GU
Interactive Network Visualization	network_display
Non-partial correlaton analysis	non_partial_cor
Partial correlaton analysis	partial_cor
Permutations to build a differential network based on correlation analysis	permutation_cor
Permutations to build differential network based on partial correlation analysis	permutation_pc
Calculate the positive and negative thresholds based on the permutation result	permutation_thres
Obtain p-values using logistic regression	pvalue_logit
P-values obtained by differential expression (DE) analysis.	pvalue_M_GU
Scale list of numbers	scale_range
Data preprocessing for partial correlaton analysis	select_rho_partial

Package: INDEED 2.19.0

INDEED: Interactive Visualization of Integrated Differential Expression and Differential Network Analysis for Biomarker Candidate Selection Package

INDEED R package for cancer biomarker discovery

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Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)