Package: decoupleR 2.13.0

Pau Badia-i-Mompel

decoupleR: decoupleR: Ensemble of computational methods to infer biological activities from omics data

Many methods allow us to extract biological activities from omics data using information from prior knowledge resources, reducing the dimensionality for increased statistical power and better interpretability. Here, we present decoupleR, a Bioconductor package containing different statistical methods to extract these signatures within a unified framework. decoupleR allows the user to flexibly test any method with any resource. It incorporates methods that take into account the sign and weight of network interactions. decoupleR can be used with any omic, as long as its features can be linked to a biological process based on prior knowledge. For example, in transcriptomics gene sets regulated by a transcription factor, or in phospho-proteomics phosphosites that are targeted by a kinase.

Authors:Pau Badia-i-Mompel [aut, cre], Jesús Vélez-Santiago [aut], Jana Braunger [aut], Celina Geiss [aut], Daniel Dimitrov [aut], Sophia Müller-Dott [aut], Petr Taus [aut], Aurélien Dugourd [aut], Christian H. Holland [aut], Ricardo O. Ramirez Flores [aut], Julio Saez-Rodriguez [aut]

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decoupleR.pdf |decoupleR.html
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NEWS

# Install 'decoupleR' in R:
install.packages('decoupleR', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/saezlab/decoupler/issues

On BioConductor:decoupleR-2.13.0(bioc 3.21)decoupleR-2.12.0(bioc 3.20)

differentialexpressionfunctionalgenomicsgeneexpressiongeneregulationnetworksoftwarestatisticalmethodtranscription

11.19 score 193 stars 3 packages 266 scripts 1.7k downloads 43 exports 34 dependencies

Last updated 21 days agofrom:1d86763f58. Checks:OK: 1 ERROR: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 14 2024
R-4.5-winERRORNov 14 2024
R-4.5-linuxERRORNov 14 2024
R-4.4-winERRORNov 14 2024
R-4.4-macERRORNov 14 2024
R-4.3-winERRORNov 14 2024
R-4.3-macERRORNov 14 2024

Exports::=.data.fit_preprocessing%>%abortas_labelas_namecheck_corrconvert_f_defaultsdecoupleenquoenquosexecexprextract_setsfilt_minsizeget_collectriget_dorotheaget_ksn_omnipathget_progenyget_resourceget_toy_dataintersect_regulonspivot_wider_profilequo_is_missingquo_is_nullrename_netrun_aucellrun_consensusrun_fgsearun_gsvarun_mdtrun_mlmrun_orarun_udtrun_ulmrun_viperrun_wmeanrun_wsumshow_methodsshow_resourcessymsyms

Dependencies:backportsBHBiocParallelbroomclicodetoolscpp11dplyrfansiformatRfutile.loggerfutile.optionsgenericsgluelambda.rlatticelifecyclemagrittrMatrixparallellypillarpkgconfigpurrrR6rlangsnowstringistringrtibbletidyrtidyselectutf8vctrswithr

Introduction

Rendered fromdecoupleR.Rmdusingknitr::rmarkdownon Nov 14 2024.

Last update: 2022-04-01
Started: 2020-12-14

Pathway activity inference from scRNA-seq

Rendered frompw_sc.Rmdusingknitr::rmarkdownon Nov 14 2024.

Last update: 2023-11-21
Started: 2022-03-30

Pathway activity inference in bulk RNA-seq

Rendered frompw_bk.Rmdusingknitr::rmarkdownon Nov 14 2024.

Last update: 2023-11-21
Started: 2022-04-01

Transcription factor activity inference from scRNA-seq

Rendered fromtf_sc.Rmdusingknitr::rmarkdownon Nov 14 2024.

Last update: 2023-11-21
Started: 2022-03-30

Transcription factor activity inference in bulk RNA-seq

Rendered fromtf_bk.Rmdusingknitr::rmarkdownon Nov 14 2024.

Last update: 2023-11-21
Started: 2022-04-01

Readme and manuals

Help Manual

Help pageTopics
Pre-processing for methods that fit networks..fit_preprocessing
Check correlation (colinearity)check_corr
Rename columns and add defaults values if column not presentconvert_f_defaults
Evaluate multiple statistics with same input datadecouple
Extract setsextract_sets
Filter sources with minsize targetsfilt_minsize
CollecTRI gene regulatory network. Wrapper to access CollecTRI gene regulatory network. CollecTRI is a comprehensive resource containing a curated collection of transcription factors (TFs) and their target genes. It is an expansion of DoRothEA. Each interaction is weighted by its mode of regulation (either positive or negative).get_collectri
DoRothEA gene regulatory network.get_dorothea
OmniPath kinase-substrate networkget_ksn_omnipath
Pathway RespOnsive GENes for activity inference (PROGENy).get_progeny
Wrapper to access resources inside Omnipath. This wrapper allows to easily query different prior knowledge resources. To check available resources run 'decoupleR::show_resources()'. For more information visit the official website for Omnipath.get_resource
Generate a toy 'mat' and 'network'.get_toy_data
Intersect network target features with input matrix.intersect_regulons
Rename networkrename_net
AUCellrun_aucell
Consensus score between methodsrun_consensus
Fast Gene Set Enrichment Analysis (FGSEA)run_fgsea
Gene Set Variation Analysis (GSVA)run_gsva
Multivariate Decision Trees (MDT)run_mdt
Multivariate Linear Model (MLM)run_mlm
Over Representation Analysis (ORA)run_ora
Univariate Decision Tree (UDT)run_udt
Univariate Linear Model (ULM)run_ulm
Virtual Inference of Protein-activity by Enriched Regulon analysis (VIPER)run_viper
Weighted Mean (WMEAN)run_wmean
Weighted Sum (WSUM)run_wsum
Show methodsshow_methods
Shows available resources in Omnipath. For more information visit the official website for Omnipath.show_resources