vignettes/ReferenceManual.md
In bigomics/SPACEconnect: Stratified Perturbation Analysis by Correlation Enrichment of connectivity
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\title{SPACEconnect Reference Manual}
\author{Ivo Kwee and Layal Abo Khayal \thanks{funded by the BigOmics}}
\maketitle
Januar 03, 2022
DESCRIPTION
Package: SPACEconnect
Title: Stratified Perturbation Analysis by Correlation Enrichment of
connectivity
Version: 0.0.0.9000
Authors@R: c(
person("IVO", "KWEE", , "kwee@bigomics.ch", role = "aut", comment = c(ORCID = "0000-0002-2751-4218")),
pperson("Layal", "Abo Khayal", , "Layal.abo.khayal@gmail.com", role = "cre")
)
Description: 'SPACEconnect' calculate and visualise the correlations
between expermental gene expresion profiles and the signatures from
databases that have focused on detailing gene expression profiles
based on the exposure of different cell lines to various perturbagen,
such as varying concentration of various compounds, or identifying
signatures that correlate with drug responses, or even the alteration
in gene expression profile caused by silencing or activating a gene or
a set of genes.
License: GPL (>= 3)
URL: https://public.bigomics.ch/app/omicsplayground_contrib
Imports:
corrplot,
fgsea,
gplots,
graphics,
Matrix,
qlcMatrix,
stats,
utils,
uwot,
WGCNA
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
LazyDataCompression: bzip2
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.2
computePeturbEnrichment
Compute drug Enrichment, drugs activity or drugs sensitivity based on database and annotation provided as input parameter
Description
Compute drug Enrichment, drugs activity or drugs sensitivity based on database and annotation provided as input parameter
Usage
computePeturbEnrichment(
mFC,
mDrugEnrich,
DrugsAnnot,
methods = c("GSEA", "cor"),
nmin = 15,
nprune = 0,
contrast = NULL
)
Arguments
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Argument | Description |
+===============+============================================================================================================================================================================================================+
| mFC | = A matrix of differential gene expression fold-change of own experiment, the rows name of the matrix must be the genes names |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| mDrugEnrich | = a large matrix represents the gene expression fold change in the presence of different perturbations, either various drugs concentrations or other genetic engineering techniques as gene-knock-in etc.. |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| DrugsAnnot | =is matrix represents the drugs annotation that contains the targets, mechanism of action , clinical phase, disease area, and indication |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| methods | the computation methods of Enrichment, either using GSEA algorithm or the rank correlation. |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| nmin | the minimum number of drugs |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| nprune | takes only the (nprune) top matching drugs for each comparison to reduce the size of the matrix. default is 0 to take the full matrix |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| contrast | is a character string represent the two compared conditions(contrast) as it is provided from the fold-change matrix |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
Value
drugs a list of drugs enrichment stats and annotations
Examples
# from the data-sets provided as examples within the package load the .rda files
# DrugsAnnot, mDrugEnrich, mFC
drugs <- computePeturbEnrichment(
mFC = mFC, mDrugEnrich = mDrugEnrich, DrugsAnnot = DrugsAnnot,
methods = "GSEA", nprune = 250, contrast = NULL
)
DrugsAnnot
Annotation of a set of drugs
Description
This data set is a matrix represents the drugs annotation that contains drugs' names, targets, mechanism of action , clinical phase, disease area, and indication.
Format
A data frame with 6125 observations on the following 6 variables. "pert_iname","clinical_phase", "moa", "target", "disease_area" and indication
Usage
data("DrugsAnnot")
Details
L1000 repurposing drugs . For research use only. Do not use the Repurposing Hub to make clinical treatment decisions. BROAD DOES NOT GUARANTEE OR WARRANT THE ACCURACY OF THE DATA WITHIN THE REPURPOSING HUB.
References
Corsello SM, et al. Nature Medicine. 2017 Apr 7;23(4):405-408. doi: 10.1038/nm.4306
Examples
data(DrugsAnnot)
## maybe str(DrugsAnnot) ; plot(DrugsAnnot) ...
dseaPlotActmap
Plot drug Activity Map
Description
Plot drug Activity Map
Usage
dseaPlotActmap(dsea, drugs, method = "GSEA", contr, nterms = 50, nfc = 20)
Arguments
+------------+---------------------------------------------------------------------------------------------------------------------+
| Argument | Description |
+============+=====================================================================================================================+
| dsea | drugs set enrichment analysis object as output of getActiveDSEA |
+------------+---------------------------------------------------------------------------------------------------------------------+
| drugs | a list of drugs enrichment stats and annotations the output of computePeturbEnrichment() |
+------------+---------------------------------------------------------------------------------------------------------------------+
| method | the computation methods of Enrichment, either using GSEA algorithm or the rank correlation. |
+------------+---------------------------------------------------------------------------------------------------------------------+
| contr | is a character string represent the two compared conditions(contrast) as it is provided from the fold-change matrix |
+------------+---------------------------------------------------------------------------------------------------------------------+
| nterms | integer |
+------------+---------------------------------------------------------------------------------------------------------------------+
| nfc | integer |
+------------+---------------------------------------------------------------------------------------------------------------------+
Value
plot of drug activity map
Examples
# from the data-sets provided as examples within the package load the .rda files
#DrugsAnnot, mDrugEnrich, mFC
dsea = getActiveDSEA(mDrugEnrich, DrugsAnnot, mFC, contr = colnames(mFC)[1])
drugs= computePeturbEnrichment(mFC = mFC, mDrugEnrich = mDrugEnrich, DrugsAnnot = DrugsAnnot,
methods = "GSEA", nprune = 250, contrast = NULL)
dseaPlotActmap (dsea, drugs, method = "GSEA", contr=colnames(mFC)[1], nterms = 50, nfc=20)
getActiveDSEA
Create the drug set enrichment object that is used in the visualization
Description
Create the drug set enrichment object that is used in the visualization
Usage
getActiveDSEA(mDrugEnrich, DrugsAnnot, mFC, contr = NULL)
Arguments
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Argument | Description |
+===============+========================================================================================================================================================================+
| mDrugEnrich | a large matrix represents the gene expression fold change in the presence of different perturbations, either various drugs concentrations or other genetic engineering |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| DrugsAnnot | is matrix represents the drugs annotation that contains the targets, mechanism of action , clinical phase, disease area, and indication |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| mFC | A matrix of differential gene expression fold-change of own experiment, the rows name of the matrix must be the genes names |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| contr | is a character string represent the two compared conditions(contrast) as it is provided from the fold-change matrix |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
Value
drug set enrichment object
Examples
# from the data-sets provided as examples within the package load the .rda files
# DrugsAnnot, mDrugEnrich, mFC
dsea <- getActiveDSEA(mDrugEnrich, DrugsAnnot, mFC, contr = colnames(mFC)[1])
getMOA
Get the mechanism of action object
Description
Get the mechanism of action object
Usage
getMOA(dsea)
Arguments
+---------------+------------------------------------------------------------------------------+
| Argument | Description |
+===============+==============================================================================+
| dsea | is a drug set enrichment object as an output of the function getActiveDSEA() |
+---------------+------------------------------------------------------------------------------+
Value
MoA Mechanism of Action object
Examples
# from the data-sets provided as examples within the package load the .rda files
# DrugsAnnot, mDrugEnrich, mFC
dsea <- getActiveDSEA(mDrugEnrich, DrugsAnnot, mFC, contr = colnames(mFC)[1])
Moa <- getMOA(dsea)
mDrugEnrich
The drugs activity on 1001 genes
Description
a large matrix represents the gene expression fold change of 1001 genes in the presence of 20220 different drugs concentrations and working time.
Format
The format is: num [1:1001, 1:20220] -12.7 0.82 -1.48 -1.89 4.02 ... - attr(*, "dimnames")=List of 2 ..\$ : chr [1:1001] "PSME1" "CISD1" "SPDEF" "ATF1" ... ..\$ : chr [1:20220] "crizotinib_HEPG2_10um_24h" "avicin-d_JURKAT_10um_24h" "BRD-K35716340_WSUDLCL2_10um_6h" "trequinsin_HCC515_0.4um_24h" ...
Usage
data("mDrugEnrich")
Details
The LINCS L1000 project has collected gene expression profiles for thousands of perturbagens at a variety of time points, doses, and cell lines. A full list of the chemical and genetic perturbations used can be found on the CLUE website along with their descriptions.
References
Duan Q et al. LINCS Canvas Browser: interactive web app to query, browse and interrogate LINCS L1000 gene expression signatures. Nucleic Acids Res. 2014 Jul;42 (Web Server issue):W449-60.
Examples
data(mDrugEnrich)
## maybe str(mDrugEnrich) ; plot(mDrugEnrich) ...
mFC
Fold change matrix of differential gene expresion from RNAseq data of Multiple myeloma
Description
There are 6 contrasts : 1- glucocorticoid sensitive vs glucocorticoid resistant ("Resistant.vs.Sensitive").2- Treated with Withaferin-A vs untreated ("WithaferinA.vs.Untreated"). 3- untreated glucocorticoid resistant cells vs untreated glucocorticoid sensitive cells ("UTR.vs.UTS"). 4- Treated with Withaferin-A glucocorticoid resistant cells vs Treated with Withaferin-A glucocorticoid sensitive cells ("WAR.vs.WAS"). 5- Treated Resistant vs Untreated Resistant ("WAR.vs.UTR"). 6- Treated sensitive vs Untreated sensitive ("WAS.vs.UTS")
Format
A data frame with 5332 observations on the following 6 variables. Resistant.vs.Sensitive, "WithaferinA.vs.Untreated, UTR.vs.UTS, WAR.vs.WAS , WAR.vs.UTR, WAS.vs.UTS.
Usage
data("mFC")
Details
The RNAseq data from (Logie et al 2021) study. They compared the therapeutic efficacy of the phytochemical kinase inhibitor withaferin A with the clinically approved BTK inhibitor ibrutinib to target hyperactivated tyrosine kinase signaling in glucocorticoid-resistant multiple myeloma cells. theur results demonstrate that withaferin-A induced cell death of glucocorticoid-resistant MM1R cells involves covalent cysteine targeting of multiple Hinge-6 domain type tyrosine kinases of the kinase cysteinome classification, including BTK.
References
Logie E, Chirumamilla CS, Perez-Novo C, Shaw P et al. Covalent Cysteine Targeting of Bruton's Tyrosine Kinase (BTK) Family by Withaferin-A Reduces Survival of Glucocorticoid-Resistant Multiple Myeloma MM1 Cell. Cancers (Basel) 2021 Mar 31;13(7). PMID: 33807411
Examples
data(mFC)
## maybe str(mFC) ; plot(mFC) ...
plotDrugConnectivity
Plot Drug Connectivity
Description
Plot Drug Connectivity
Usage
plotDrugConnectivity(dsea)
Arguments
| Argument | Description |
|----------|----------------------------------------------------------------|
| dsea | is a drug set Enrichment object is the output of getActiveDSEA |
Value
a plot of drug connectivity
Examples
# from the data-sets provided as examples within the package load the .rda files
# DrugsAnnot, mDrugEnrich, mFC
dsea <- getActiveDSEA(mDrugEnrich, DrugsAnnot, mFC, contr = colnames(mFC)[1])
plotDrugConnectivity(dsea)
plotMOA
Plot mechanism of action
Description
Plot mechanism of action
Usage
plotMOA(dsea, ntop = 16)
Arguments
+---------------+------------------------------------------------------------------------------+
| Argument | Description |
+===============+==============================================================================+
| dsea | is dsea object which is the output of the function getActiveDSEA() |
+---------------+------------------------------------------------------------------------------+
| ntop | the number of the top enteries (genes or drug), ntop = 16 as a default value |
+---------------+------------------------------------------------------------------------------+
Value
plot of mechanism of action
Examples
# from the data-sets provided as examples within the package load the .rda files
# DrugsAnnot, mDrugEnrich, mFC
dsea <- getActiveDSEA(mDrugEnrich, DrugsAnnot, mFC, contr = colnames(mFC)[1])
plotMOA(dsea)
bigomics/SPACEconnect documentation built on March 19, 2022, 3:39 a.m.
R Package Documentation
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output: pdf_document: toc: yes number_sections: yes html_document: default
\title{SPACEconnect Reference Manual} \author{Ivo Kwee and Layal Abo Khayal \thanks{funded by the BigOmics}}
\maketitle
Januar 03, 2022
DESCRIPTION
Package: SPACEconnect
Title: Stratified Perturbation Analysis by Correlation Enrichment of
connectivity
Version: 0.0.0.9000
Authors@R: c(
person("IVO", "KWEE", , "kwee@bigomics.ch", role = "aut", comment = c(ORCID = "0000-0002-2751-4218")),
pperson("Layal", "Abo Khayal", , "Layal.abo.khayal@gmail.com", role = "cre")
)
Description: 'SPACEconnect' calculate and visualise the correlations
between expermental gene expresion profiles and the signatures from
databases that have focused on detailing gene expression profiles
based on the exposure of different cell lines to various perturbagen,
such as varying concentration of various compounds, or identifying
signatures that correlate with drug responses, or even the alteration
in gene expression profile caused by silencing or activating a gene or
a set of genes.
License: GPL (>= 3)
URL: https://public.bigomics.ch/app/omicsplayground_contrib
Imports:
corrplot,
fgsea,
gplots,
graphics,
Matrix,
qlcMatrix,
stats,
utils,
uwot,
WGCNA
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
LazyDataCompression: bzip2
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.2
computePeturbEnrichment
Compute drug Enrichment, drugs activity or drugs sensitivity based on database and annotation provided as input parameter
Description
Compute drug Enrichment, drugs activity or drugs sensitivity based on database and annotation provided as input parameter
Usage
computePeturbEnrichment(
mFC,
mDrugEnrich,
DrugsAnnot,
methods = c("GSEA", "cor"),
nmin = 15,
nprune = 0,
contrast = NULL
)
Arguments
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Argument | Description |
+===============+============================================================================================================================================================================================================+
| mFC | = A matrix of differential gene expression fold-change of own experiment, the rows name of the matrix must be the genes names |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| mDrugEnrich | = a large matrix represents the gene expression fold change in the presence of different perturbations, either various drugs concentrations or other genetic engineering techniques as gene-knock-in etc.. |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| DrugsAnnot | =is matrix represents the drugs annotation that contains the targets, mechanism of action , clinical phase, disease area, and indication |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| methods | the computation methods of Enrichment, either using GSEA algorithm or the rank correlation. |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| nmin | the minimum number of drugs |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| nprune | takes only the (nprune) top matching drugs for each comparison to reduce the size of the matrix. default is 0 to take the full matrix |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| contrast | is a character string represent the two compared conditions(contrast) as it is provided from the fold-change matrix |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
Value
drugs a list of drugs enrichment stats and annotations
Examples
# from the data-sets provided as examples within the package load the .rda files
# DrugsAnnot, mDrugEnrich, mFC
drugs <- computePeturbEnrichment(
mFC = mFC, mDrugEnrich = mDrugEnrich, DrugsAnnot = DrugsAnnot,
methods = "GSEA", nprune = 250, contrast = NULL
)
DrugsAnnot
Annotation of a set of drugs
Description
This data set is a matrix represents the drugs annotation that contains drugs' names, targets, mechanism of action , clinical phase, disease area, and indication.
Format
A data frame with 6125 observations on the following 6 variables. "pert_iname","clinical_phase", "moa", "target", "disease_area" and indication
Usage
data("DrugsAnnot")
Details
L1000 repurposing drugs . For research use only. Do not use the Repurposing Hub to make clinical treatment decisions. BROAD DOES NOT GUARANTEE OR WARRANT THE ACCURACY OF THE DATA WITHIN THE REPURPOSING HUB.
References
Corsello SM, et al. Nature Medicine. 2017 Apr 7;23(4):405-408. doi: 10.1038/nm.4306
Examples
data(DrugsAnnot)
## maybe str(DrugsAnnot) ; plot(DrugsAnnot) ...
dseaPlotActmap
Plot drug Activity Map
Description
Plot drug Activity Map
Usage
dseaPlotActmap(dsea, drugs, method = "GSEA", contr, nterms = 50, nfc = 20)
Arguments
+------------+---------------------------------------------------------------------------------------------------------------------+
| Argument | Description |
+============+=====================================================================================================================+
| dsea | drugs set enrichment analysis object as output of getActiveDSEA |
+------------+---------------------------------------------------------------------------------------------------------------------+
| drugs | a list of drugs enrichment stats and annotations the output of computePeturbEnrichment() |
+------------+---------------------------------------------------------------------------------------------------------------------+
| method | the computation methods of Enrichment, either using GSEA algorithm or the rank correlation. |
+------------+---------------------------------------------------------------------------------------------------------------------+
| contr | is a character string represent the two compared conditions(contrast) as it is provided from the fold-change matrix |
+------------+---------------------------------------------------------------------------------------------------------------------+
| nterms | integer |
+------------+---------------------------------------------------------------------------------------------------------------------+
| nfc | integer |
+------------+---------------------------------------------------------------------------------------------------------------------+
Value
plot of drug activity map
Examples
# from the data-sets provided as examples within the package load the .rda files
#DrugsAnnot, mDrugEnrich, mFC
dsea = getActiveDSEA(mDrugEnrich, DrugsAnnot, mFC, contr = colnames(mFC)[1])
drugs= computePeturbEnrichment(mFC = mFC, mDrugEnrich = mDrugEnrich, DrugsAnnot = DrugsAnnot,
methods = "GSEA", nprune = 250, contrast = NULL)
dseaPlotActmap (dsea, drugs, method = "GSEA", contr=colnames(mFC)[1], nterms = 50, nfc=20)
getActiveDSEA
Create the drug set enrichment object that is used in the visualization
Description
Create the drug set enrichment object that is used in the visualization
Usage
getActiveDSEA(mDrugEnrich, DrugsAnnot, mFC, contr = NULL)
Arguments
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Argument | Description |
+===============+========================================================================================================================================================================+
| mDrugEnrich | a large matrix represents the gene expression fold change in the presence of different perturbations, either various drugs concentrations or other genetic engineering |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| DrugsAnnot | is matrix represents the drugs annotation that contains the targets, mechanism of action , clinical phase, disease area, and indication |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| mFC | A matrix of differential gene expression fold-change of own experiment, the rows name of the matrix must be the genes names |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| contr | is a character string represent the two compared conditions(contrast) as it is provided from the fold-change matrix |
+---------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
Value
drug set enrichment object
Examples
# from the data-sets provided as examples within the package load the .rda files
# DrugsAnnot, mDrugEnrich, mFC
dsea <- getActiveDSEA(mDrugEnrich, DrugsAnnot, mFC, contr = colnames(mFC)[1])
getMOA
Get the mechanism of action object
Description
Get the mechanism of action object
Usage
getMOA(dsea)
Arguments
+---------------+------------------------------------------------------------------------------+
| Argument | Description |
+===============+==============================================================================+
| dsea | is a drug set enrichment object as an output of the function getActiveDSEA() |
+---------------+------------------------------------------------------------------------------+
Value
MoA Mechanism of Action object
Examples
# from the data-sets provided as examples within the package load the .rda files
# DrugsAnnot, mDrugEnrich, mFC
dsea <- getActiveDSEA(mDrugEnrich, DrugsAnnot, mFC, contr = colnames(mFC)[1])
Moa <- getMOA(dsea)
mDrugEnrich
The drugs activity on 1001 genes
Description
a large matrix represents the gene expression fold change of 1001 genes in the presence of 20220 different drugs concentrations and working time.
Format
The format is: num [1:1001, 1:20220] -12.7 0.82 -1.48 -1.89 4.02 ... - attr(*, "dimnames")=List of 2 ..\$ : chr [1:1001] "PSME1" "CISD1" "SPDEF" "ATF1" ... ..\$ : chr [1:20220] "crizotinib_HEPG2_10um_24h" "avicin-d_JURKAT_10um_24h" "BRD-K35716340_WSUDLCL2_10um_6h" "trequinsin_HCC515_0.4um_24h" ...
Usage
data("mDrugEnrich")
Details
The LINCS L1000 project has collected gene expression profiles for thousands of perturbagens at a variety of time points, doses, and cell lines. A full list of the chemical and genetic perturbations used can be found on the CLUE website along with their descriptions.
References
Duan Q et al. LINCS Canvas Browser: interactive web app to query, browse and interrogate LINCS L1000 gene expression signatures. Nucleic Acids Res. 2014 Jul;42 (Web Server issue):W449-60.
Examples
data(mDrugEnrich)
## maybe str(mDrugEnrich) ; plot(mDrugEnrich) ...
mFC
Fold change matrix of differential gene expresion from RNAseq data of Multiple myeloma
Description
There are 6 contrasts : 1- glucocorticoid sensitive vs glucocorticoid resistant ("Resistant.vs.Sensitive").2- Treated with Withaferin-A vs untreated ("WithaferinA.vs.Untreated"). 3- untreated glucocorticoid resistant cells vs untreated glucocorticoid sensitive cells ("UTR.vs.UTS"). 4- Treated with Withaferin-A glucocorticoid resistant cells vs Treated with Withaferin-A glucocorticoid sensitive cells ("WAR.vs.WAS"). 5- Treated Resistant vs Untreated Resistant ("WAR.vs.UTR"). 6- Treated sensitive vs Untreated sensitive ("WAS.vs.UTS")
Format
A data frame with 5332 observations on the following 6 variables. Resistant.vs.Sensitive, "WithaferinA.vs.Untreated, UTR.vs.UTS, WAR.vs.WAS , WAR.vs.UTR, WAS.vs.UTS.
Usage
data("mFC")
Details
The RNAseq data from (Logie et al 2021) study. They compared the therapeutic efficacy of the phytochemical kinase inhibitor withaferin A with the clinically approved BTK inhibitor ibrutinib to target hyperactivated tyrosine kinase signaling in glucocorticoid-resistant multiple myeloma cells. theur results demonstrate that withaferin-A induced cell death of glucocorticoid-resistant MM1R cells involves covalent cysteine targeting of multiple Hinge-6 domain type tyrosine kinases of the kinase cysteinome classification, including BTK.
References
Logie E, Chirumamilla CS, Perez-Novo C, Shaw P et al. Covalent Cysteine Targeting of Bruton's Tyrosine Kinase (BTK) Family by Withaferin-A Reduces Survival of Glucocorticoid-Resistant Multiple Myeloma MM1 Cell. Cancers (Basel) 2021 Mar 31;13(7). PMID: 33807411
Examples
data(mFC)
## maybe str(mFC) ; plot(mFC) ...
plotDrugConnectivity
Plot Drug Connectivity
Description
Plot Drug Connectivity
Usage
plotDrugConnectivity(dsea)
Arguments
| Argument | Description |
|----------|----------------------------------------------------------------|
| dsea | is a drug set Enrichment object is the output of getActiveDSEA |
Value
a plot of drug connectivity
Examples
# from the data-sets provided as examples within the package load the .rda files
# DrugsAnnot, mDrugEnrich, mFC
dsea <- getActiveDSEA(mDrugEnrich, DrugsAnnot, mFC, contr = colnames(mFC)[1])
plotDrugConnectivity(dsea)
plotMOA
Plot mechanism of action
Description
Plot mechanism of action
Usage
plotMOA(dsea, ntop = 16)
Arguments
+---------------+------------------------------------------------------------------------------+
| Argument | Description |
+===============+==============================================================================+
| dsea | is dsea object which is the output of the function getActiveDSEA() |
+---------------+------------------------------------------------------------------------------+
| ntop | the number of the top enteries (genes or drug), ntop = 16 as a default value |
+---------------+------------------------------------------------------------------------------+
Value
plot of mechanism of action
Examples
# from the data-sets provided as examples within the package load the .rda files
# DrugsAnnot, mDrugEnrich, mFC
dsea <- getActiveDSEA(mDrugEnrich, DrugsAnnot, mFC, contr = colnames(mFC)[1])
plotMOA(dsea)
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