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Description

This method is described in the publication from Biorxiv, 2018 available at [https://www.biorxiv.org/content/10.1101/426593v2]

ICTD web application demo is available at : [https://shiny.ph.iu.edu/ICTD/]

ICTD web application tutorial is available at : [https://github.com/changwn/ICTD/blob/master/vignettes/ICTD_server_tutorial.md]

[image]

Backup link: [https://ictd.ccbb.iupui.edu]

ICTD Framework

[fig1]

Installation

#install dependent pkg
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("impute", version = "3.8")
BiocManager::install("GO.db", version = "3.8")
BiocManager::install("sva", version = "3.8")
BiocManager::install("preprocessCore", version = "3.8")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)
#install ICTD
install.packages("devtools")
devtools::install_github("changwn/ICTD")

Note : For old R version which cannot install 'BiocManager', please use below command to install the dependency.

source("https://bioconductor.org/biocLite.R")
biocLite("impute")
biocLite("GO.db")
biocLite("sva")
biocLite("preprocessCore")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)

Example

library(ICTD)
data_bulk = GSE72056_diri_example[[1]]
ictd_result <- ICTD(data_bulk)
#Return value is a list, which the first element is the predicted proportion and #the second element is the predicted markers of ICTD

Questions & Problems

If you have any questions or problems when using ICTD, please feel free to open a new issue here. We will fix the new issue ASAP. You can also email the maintainers and authors below.

PhD candidate at BDR group, Indiana University School of Medicine

Assistant Professor

Department of Medical & Molecular Genetics, Indiana University School of Medicine

Dependencies

We also provide a Docker image to recreate the compute environment. See the Dockerfile for more details.

[https://hub.docker.com/r/wnchang/ictd]

Using the Docker image could void the conflict issue that R version and several R packages version confict.

For more details about the Docker, please see Docker documentation page [https://docs.docker.com/].

About

A semi-supervised cell type identification and deonvolution method for multi-omics data https://shiny.ph.iu.edu/ICTD/

zcslab.github.io/ICTD/

Resources

Readme
Activity
Custom properties

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1 star

Watchers

2 watching

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GitHub - zcslab/ICTD: A semi-supervised cell type identification and deonvolution method for multi-omics data https://shiny.ph.iu.edu/ICTD/ · GitHub
Skip to content
BranchesTags
Repository files navigation
Description
This method is described in the publication from Biorxiv, 2018 available at [https://www.biorxiv.org/content/10.1101/426593v2]
ICTD web application demo is available at : [https://shiny.ph.iu.edu/ICTD/]
ICTD web application tutorial is available at : [https://github.com/changwn/ICTD/blob/master/vignettes/ICTD_server_tutorial.md]
[image]
Backup link: [https://ictd.ccbb.iupui.edu]
ICTD Framework
[fig1]
Installation
#install dependent pkg
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("impute", version = "3.8")
BiocManager::install("GO.db", version = "3.8")
BiocManager::install("sva", version = "3.8")
BiocManager::install("preprocessCore", version = "3.8")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)
#install ICTD
install.packages("devtools")
devtools::install_github("changwn/ICTD")

Note : For old R version which cannot install 'BiocManager', please use below command to install the dependency.
source("https://bioconductor.org/biocLite.R")
biocLite("impute")
biocLite("GO.db")
biocLite("sva")
biocLite("preprocessCore")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)

Example
library(ICTD)
data_bulk = GSE72056_diri_example[[1]]
ictd_result <- ICTD(data_bulk)
#Return value is a list, which the first element is the predicted proportion and #the second element is the predicted markers of ICTD

Questions & Problems
If you have any questions or problems when using ICTD, please feel free to open a new issue here. We will fix the new issue ASAP. You can also email the maintainers and authors below.
PhD candidate at BDR group, Indiana University School of Medicine
Assistant Professor
Department of Medical & Molecular Genetics, Indiana University School of Medicine
Dependencies
We also provide a Docker image to recreate the compute environment. See the Dockerfile for more details.
[https://hub.docker.com/r/wnchang/ictd]
Using the Docker image could void the conflict issue that R version and several R packages version confict.
For more details about the Docker, please see Docker documentation page [https://docs.docker.com/].
About
A semi-supervised cell type identification and deonvolution method for multi-omics data https://shiny.ph.iu.edu/ICTD/
zcslab.github.io/ICTD/
Resources
Readme
Activity
Custom properties
Stars
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Watchers
2 watching
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0 forks
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, 'i');
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GitHub - zcslab/ICTD: A semi-supervised cell type identification and deonvolution method for multi-omics data https://shiny.ph.iu.edu/ICTD/ · GitHub
Skip to content
BranchesTags
Repository files navigation
Description
This method is described in the publication from Biorxiv, 2018 available at [https://www.biorxiv.org/content/10.1101/426593v2]
ICTD web application demo is available at : [https://shiny.ph.iu.edu/ICTD/]
ICTD web application tutorial is available at : [https://github.com/changwn/ICTD/blob/master/vignettes/ICTD_server_tutorial.md]
[image]
Backup link: [https://ictd.ccbb.iupui.edu]
ICTD Framework
[fig1]
Installation
#install dependent pkg
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("impute", version = "3.8")
BiocManager::install("GO.db", version = "3.8")
BiocManager::install("sva", version = "3.8")
BiocManager::install("preprocessCore", version = "3.8")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)
#install ICTD
install.packages("devtools")
devtools::install_github("changwn/ICTD")

Note : For old R version which cannot install 'BiocManager', please use below command to install the dependency.
source("https://bioconductor.org/biocLite.R")
biocLite("impute")
biocLite("GO.db")
biocLite("sva")
biocLite("preprocessCore")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)

Example
library(ICTD)
data_bulk = GSE72056_diri_example[[1]]
ictd_result <- ICTD(data_bulk)
#Return value is a list, which the first element is the predicted proportion and #the second element is the predicted markers of ICTD

Questions & Problems
If you have any questions or problems when using ICTD, please feel free to open a new issue here. We will fix the new issue ASAP. You can also email the maintainers and authors below.
PhD candidate at BDR group, Indiana University School of Medicine
Assistant Professor
Department of Medical & Molecular Genetics, Indiana University School of Medicine
Dependencies
We also provide a Docker image to recreate the compute environment. See the Dockerfile for more details.
[https://hub.docker.com/r/wnchang/ictd]
Using the Docker image could void the conflict issue that R version and several R packages version confict.
For more details about the Docker, please see Docker documentation page [https://docs.docker.com/].
About
A semi-supervised cell type identification and deonvolution method for multi-omics data https://shiny.ph.iu.edu/ICTD/
zcslab.github.io/ICTD/
Resources
Readme
Activity
Custom properties
Stars
1 star
Watchers
2 watching
Forks
0 forks
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, 'i');
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} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - zcslab/ICTD: A semi-supervised cell type identification and deonvolution method for multi-omics data https://shiny.ph.iu.edu/ICTD/ · GitHub
Skip to content
BranchesTags
Repository files navigation
Description
This method is described in the publication from Biorxiv, 2018 available at [https://www.biorxiv.org/content/10.1101/426593v2]
ICTD web application demo is available at : [https://shiny.ph.iu.edu/ICTD/]
ICTD web application tutorial is available at : [https://github.com/changwn/ICTD/blob/master/vignettes/ICTD_server_tutorial.md]
[image]
Backup link: [https://ictd.ccbb.iupui.edu]
ICTD Framework
[fig1]
Installation
#install dependent pkg
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("impute", version = "3.8")
BiocManager::install("GO.db", version = "3.8")
BiocManager::install("sva", version = "3.8")
BiocManager::install("preprocessCore", version = "3.8")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)
#install ICTD
install.packages("devtools")
devtools::install_github("changwn/ICTD")

Note : For old R version which cannot install 'BiocManager', please use below command to install the dependency.
source("https://bioconductor.org/biocLite.R")
biocLite("impute")
biocLite("GO.db")
biocLite("sva")
biocLite("preprocessCore")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)

Example
library(ICTD)
data_bulk = GSE72056_diri_example[[1]]
ictd_result <- ICTD(data_bulk)
#Return value is a list, which the first element is the predicted proportion and #the second element is the predicted markers of ICTD

Questions & Problems
If you have any questions or problems when using ICTD, please feel free to open a new issue here. We will fix the new issue ASAP. You can also email the maintainers and authors below.
PhD candidate at BDR group, Indiana University School of Medicine
Assistant Professor
Department of Medical & Molecular Genetics, Indiana University School of Medicine
Dependencies
We also provide a Docker image to recreate the compute environment. See the Dockerfile for more details.
[https://hub.docker.com/r/wnchang/ictd]
Using the Docker image could void the conflict issue that R version and several R packages version confict.
For more details about the Docker, please see Docker documentation page [https://docs.docker.com/].
About
A semi-supervised cell type identification and deonvolution method for multi-omics data https://shiny.ph.iu.edu/ICTD/
zcslab.github.io/ICTD/
Resources
Readme
Activity
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2 watching
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, 'i');
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(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
GitHub - zcslab/ICTD: A semi-supervised cell type identification and deonvolution method for multi-omics data https://shiny.ph.iu.edu/ICTD/ · GitHub
Skip to content
BranchesTags
Repository files navigation
Description
This method is described in the publication from Biorxiv, 2018 available at [https://www.biorxiv.org/content/10.1101/426593v2]
ICTD web application demo is available at : [https://shiny.ph.iu.edu/ICTD/]
ICTD web application tutorial is available at : [https://github.com/changwn/ICTD/blob/master/vignettes/ICTD_server_tutorial.md]
[image]
Backup link: [https://ictd.ccbb.iupui.edu]
ICTD Framework
[fig1]
Installation
#install dependent pkg
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("impute", version = "3.8")
BiocManager::install("GO.db", version = "3.8")
BiocManager::install("sva", version = "3.8")
BiocManager::install("preprocessCore", version = "3.8")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)
#install ICTD
install.packages("devtools")
devtools::install_github("changwn/ICTD")

Note : For old R version which cannot install 'BiocManager', please use below command to install the dependency.
source("https://bioconductor.org/biocLite.R")
biocLite("impute")
biocLite("GO.db")
biocLite("sva")
biocLite("preprocessCore")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)

Example
library(ICTD)
data_bulk = GSE72056_diri_example[[1]]
ictd_result <- ICTD(data_bulk)
#Return value is a list, which the first element is the predicted proportion and #the second element is the predicted markers of ICTD

Questions & Problems
If you have any questions or problems when using ICTD, please feel free to open a new issue here. We will fix the new issue ASAP. You can also email the maintainers and authors below.
PhD candidate at BDR group, Indiana University School of Medicine
Assistant Professor
Department of Medical & Molecular Genetics, Indiana University School of Medicine
Dependencies
We also provide a Docker image to recreate the compute environment. See the Dockerfile for more details.
[https://hub.docker.com/r/wnchang/ictd]
Using the Docker image could void the conflict issue that R version and several R packages version confict.
For more details about the Docker, please see Docker documentation page [https://docs.docker.com/].
About
A semi-supervised cell type identification and deonvolution method for multi-omics data https://shiny.ph.iu.edu/ICTD/
zcslab.github.io/ICTD/
Resources
Readme
Activity
Custom properties
Stars
1 star
Watchers
2 watching
Forks
0 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
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function tryTheater() {
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(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - zcslab/ICTD: A semi-supervised cell type identification and deonvolution method for multi-omics data https://shiny.ph.iu.edu/ICTD/ · GitHub
Skip to content
BranchesTags
Repository files navigation
Description
This method is described in the publication from Biorxiv, 2018 available at [https://www.biorxiv.org/content/10.1101/426593v2]
ICTD web application demo is available at : [https://shiny.ph.iu.edu/ICTD/]
ICTD web application tutorial is available at : [https://github.com/changwn/ICTD/blob/master/vignettes/ICTD_server_tutorial.md]
[image]
Backup link: [https://ictd.ccbb.iupui.edu]
ICTD Framework
[fig1]
Installation
#install dependent pkg
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("impute", version = "3.8")
BiocManager::install("GO.db", version = "3.8")
BiocManager::install("sva", version = "3.8")
BiocManager::install("preprocessCore", version = "3.8")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)
#install ICTD
install.packages("devtools")
devtools::install_github("changwn/ICTD")

Note : For old R version which cannot install 'BiocManager', please use below command to install the dependency.
source("https://bioconductor.org/biocLite.R")
biocLite("impute")
biocLite("GO.db")
biocLite("sva")
biocLite("preprocessCore")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)

Example
library(ICTD)
data_bulk = GSE72056_diri_example[[1]]
ictd_result <- ICTD(data_bulk)
#Return value is a list, which the first element is the predicted proportion and #the second element is the predicted markers of ICTD

Questions & Problems
If you have any questions or problems when using ICTD, please feel free to open a new issue here. We will fix the new issue ASAP. You can also email the maintainers and authors below.
PhD candidate at BDR group, Indiana University School of Medicine
Assistant Professor
Department of Medical & Molecular Genetics, Indiana University School of Medicine
Dependencies
We also provide a Docker image to recreate the compute environment. See the Dockerfile for more details.
[https://hub.docker.com/r/wnchang/ictd]
Using the Docker image could void the conflict issue that R version and several R packages version confict.
For more details about the Docker, please see Docker documentation page [https://docs.docker.com/].
About
A semi-supervised cell type identification and deonvolution method for multi-omics data https://shiny.ph.iu.edu/ICTD/
zcslab.github.io/ICTD/
Resources
Readme
Activity
Custom properties
Stars
1 star
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
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(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - zcslab/ICTD: A semi-supervised cell type identification and deonvolution method for multi-omics data https://shiny.ph.iu.edu/ICTD/ · GitHub
Skip to content
BranchesTags
Repository files navigation
Description
This method is described in the publication from Biorxiv, 2018 available at [https://www.biorxiv.org/content/10.1101/426593v2]
ICTD web application demo is available at : [https://shiny.ph.iu.edu/ICTD/]
ICTD web application tutorial is available at : [https://github.com/changwn/ICTD/blob/master/vignettes/ICTD_server_tutorial.md]
[image]
Backup link: [https://ictd.ccbb.iupui.edu]
ICTD Framework
[fig1]
Installation
#install dependent pkg
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("impute", version = "3.8")
BiocManager::install("GO.db", version = "3.8")
BiocManager::install("sva", version = "3.8")
BiocManager::install("preprocessCore", version = "3.8")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)
#install ICTD
install.packages("devtools")
devtools::install_github("changwn/ICTD")

Note : For old R version which cannot install 'BiocManager', please use below command to install the dependency.
source("https://bioconductor.org/biocLite.R")
biocLite("impute")
biocLite("GO.db")
biocLite("sva")
biocLite("preprocessCore")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)

Example
library(ICTD)
data_bulk = GSE72056_diri_example[[1]]
ictd_result <- ICTD(data_bulk)
#Return value is a list, which the first element is the predicted proportion and #the second element is the predicted markers of ICTD

Questions & Problems
If you have any questions or problems when using ICTD, please feel free to open a new issue here. We will fix the new issue ASAP. You can also email the maintainers and authors below.
PhD candidate at BDR group, Indiana University School of Medicine
Assistant Professor
Department of Medical & Molecular Genetics, Indiana University School of Medicine
Dependencies
We also provide a Docker image to recreate the compute environment. See the Dockerfile for more details.
[https://hub.docker.com/r/wnchang/ictd]
Using the Docker image could void the conflict issue that R version and several R packages version confict.
For more details about the Docker, please see Docker documentation page [https://docs.docker.com/].
About
A semi-supervised cell type identification and deonvolution method for multi-omics data https://shiny.ph.iu.edu/ICTD/
zcslab.github.io/ICTD/
Resources
Readme
Activity
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2 watching
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filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
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filter: invert(1) hue-rotate(180deg) !important;
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filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
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::-webkit-scrollbar-thumb { background: #444 !important; }
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/* Selection */
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::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
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removeDarkMode();
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applyDarkMode();
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if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
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observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
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GitHub - zcslab/ICTD: A semi-supervised cell type identification and deonvolution method for multi-omics data https://shiny.ph.iu.edu/ICTD/ · GitHub
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Description
This method is described in the publication from Biorxiv, 2018 available at [https://www.biorxiv.org/content/10.1101/426593v2]
ICTD web application demo is available at : [https://shiny.ph.iu.edu/ICTD/]
ICTD web application tutorial is available at : [https://github.com/changwn/ICTD/blob/master/vignettes/ICTD_server_tutorial.md]
[image]
Backup link: [https://ictd.ccbb.iupui.edu]
ICTD Framework
[fig1]
Installation
#install dependent pkg
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("impute", version = "3.8")
BiocManager::install("GO.db", version = "3.8")
BiocManager::install("sva", version = "3.8")
BiocManager::install("preprocessCore", version = "3.8")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)
#install ICTD
install.packages("devtools")
devtools::install_github("changwn/ICTD")

Note : For old R version which cannot install 'BiocManager', please use below command to install the dependency.
source("https://bioconductor.org/biocLite.R")
biocLite("impute")
biocLite("GO.db")
biocLite("sva")
biocLite("preprocessCore")
rforge <- "http://r-forge.r-project.org"
install.packages("estimate", repos=rforge, dependencies=TRUE)

Example
library(ICTD)
data_bulk = GSE72056_diri_example[[1]]
ictd_result <- ICTD(data_bulk)
#Return value is a list, which the first element is the predicted proportion and #the second element is the predicted markers of ICTD

Questions & Problems
If you have any questions or problems when using ICTD, please feel free to open a new issue here. We will fix the new issue ASAP. You can also email the maintainers and authors below.
PhD candidate at BDR group, Indiana University School of Medicine
Assistant Professor
Department of Medical & Molecular Genetics, Indiana University School of Medicine
Dependencies
We also provide a Docker image to recreate the compute environment. See the Dockerfile for more details.
[https://hub.docker.com/r/wnchang/ictd]
Using the Docker image could void the conflict issue that R version and several R packages version confict.
For more details about the Docker, please see Docker documentation page [https://docs.docker.com/].
About
A semi-supervised cell type identification and deonvolution method for multi-omics data https://shiny.ph.iu.edu/ICTD/
zcslab.github.io/ICTD/
Resources
Readme
Activity
Custom properties
Stars
1 star
Watchers
2 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages