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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
M͐ʼnŇĽŅŊĹň, ķŀŊňʼnĹŇĽłĻ, ŋĽňŊĵŀĽňĵʼnĽŃł 
Sébastien Plutniak1 Marion Maisonobe2 
1Lisst-Cers, Ehess — 2Lisst-Cieu, Labex SMS 
ǨǬ mai ǩǧǨǫ 
ResTO, Toulouse
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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
IłʼnŇŃĸŊķʼnĽŃł 
D͐ŇŃŊŀ͐ ĸĹ ŀ’ĵʼnĹŀĽĹŇ 
D͐ŇŃŊŀ͐ ĸĹ ŀ’ĵʼnĹŀĽĹŇ 
lj IłʼnŇŃĸŊķʼnĽŃł 
Déroulé de l’atelier 
Tour de table 
NJ PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R 
Les graphes, objets mathématiques et R 
Les package R concernant l’analyse de graphes 
Ressources en ligne 
Nj MĵłĽńŊŀĹŇ ĵŋĹķ IĽʼnķņľ Ĺʼn ŋńĻŋ 
nj Uł ĹŎĹŁńŀĹ ĸĹ ńŇŃľĹʼn
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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
IłʼnŇŃĸŊķʼnĽŃł 
TŃŊŇ ĸĹ ʼnĵĶŀĹ 
TŃŊŇ ĸĹ ʼnĵĶŀĹ 
Pour commencer… 
Types de données relationnelles que chacun a à traiter ? 
Quels outils déjà utilisés ? Leurs limites éventuelles ? 
En conséquence, quels besoins ? 
(Quelle connaissance préalable de R ? )
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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R 
LĹň ĻŇĵńļĹň, ŃĶľĹʼnň Łĵʼnļ͐ŁĵʼnĽŅŊĹň Ĺʼn R 
LĹň ĻŇĵńļĹň, ŃĶľĹʼnň Łĵʼnļ͐ŁĵʼnĽŅŊĹň Ĺʼn R 
Le graphe comme objet mathématique 
Une graphe est composé : 
d’un ensemble d’éléments qui sont les sommets (ou noeuds) du graphe ; 
et d’un ensemble d’éléments qui sont les arètes (ou arcs) du graphe. Les 
arètes peuvent être orientées ou non. 
Implémentation minimale dans R 
un objet data.frame contenant une liste d’arètes ; 
un objet matrix contenant une matrice carrée des (id des) noeuds en colonne, 
et la valeur des liens dans les cases (Ǩ ou ǧ pour les graphes non valués ; une 
valeur pour les graphes valués).
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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R 
LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň 
LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň 
Ǩǩǫ packages ayant le mot « network » dans leur titre ou leur description sur CRAN 
abn Data Modelling with Additive Bayesian Networks 
amen Additive and multiplicative effects modeling of networks and relational data 
AMORE A MORE flexible neural network package 
ANN Feedforward Artificial Neural Network optimized by Genetic Algorithm 
ARTIVA Infer a time-varying DBN network from time series data 
BiomarkeR Paired (pBI) and Unpaired Biomarker Identifier (uBI) including a method to infer networks 
bionetdata Biological and chemical data networks 
bioPN Simulation of deterministic and stochastic biochemical reaction networks using Petri Nets 
bipartite Visualising bipartite networks and calculating some (ecological) indices 
blkergm Fitting block ERGM given the block structure on social networks 
blockmodeling An R package for Generalized and classical blockmodeling of valued networks 
BMN The pseudo-likelihood method for pairwise binary markov networks 
bnlearn Bayesian network structure learning, parameter learning and inference 
BoolNet Generation, reconstruction, simulation and analysis of synchronous, asynchronous, and probabilistic Boolean networks 
brnn brnn (Bayesian regularization for feed-forward neural networks) 
cǪnet Infering large-scale gene networks with CǪNET 
CaDENCE Conditional Density Estimation Network Construction and Evaluation 
catnet Categorical Bayesian Network Inference 
CCMnet Simulate Congruence Class Model for Networks 
CHCN Canadian Historical Climate Network 
CIDnetworks Generative models for networks with conditionally independent dyadic structure 
condmixt Conditional Density Estimation with Neural Network Conditional Mixtures 
COSINE COndition SpecIfic sub-NEtwork 
crn Downloads and Builds datasets for Climate Reference Network 
dǪNetwork Tools for creating DǪ JavaScript network and tree graphs from R
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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R 
LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň 
LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň 
Ǩǩǫ packages ayant le mot « network » dans leur titre ou leur description sur CRAN 
ddepn Dynamic Deterministic Effects Propagation Networks : Infer signalling networks for timecourse RPPA data 
deal Learning Bayesian Networks with Mixed Variables 
degreenet Models for Skewed Count Distributions Relevant to Networks 
diagram Functions for visualising simple graphs (networks), plotting flow diagrams 
dils Data-Informed Link Strength. Combine multiple-relationship networks into a single weighted network. Impute (fill-in) missing network links 
dna Differential Network Analysis 
dnet Integrative analysis of digitised data in terms of network, ontology and evolution 
Dominance ADI (average dominance index), social network graphs with dual directions, and music notation graph 
dvn Access to The Dataverse Network APIs 
ebdbNet Empirical Bayes Estimation of Dynamic Bayesian Networks 
EDISON SoƜware for network reconstruction and changepoint detection 
egonet Tool for ego-centric measures in Social Network Analysis 
elmNN Implementation of ELM (Extreme Learning Machine ) algorithm for SLFN ( Single Hidden Layer Feedforward Neural Networks ) 
ENA Ensemble Network Aggregation 
enaR Tools for ecological network analysis (ena) in R 
epinet A collection of epidemic/network-related tools 
ergm Fit, Simulate and Diagnose Exponential-Family Models for Networks 
ergm.count Fit, Simulate and Diagnose Exponential-Family Models for Networks with Count Edges 
ergmharris Local Health Department network data set 
foodweb visualisation and analysis of food web networks 
GǨDBN A package performing Dynamic Bayesian Network inference 
GANPA Gene Association Network-based Pathway Analysis 
gemtc GeMTC network meta-analysis 
GeneNet Modeling and Inferring Gene Networks 
GeneReg Construct time delay gene regulatory network
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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R 
LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň 
LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň 
Ǩǩǫ packages ayant le mot « network » dans leur titre ou leur description sur CRAN 
geospt Spatial geostatistics ; some geostatistical and radial basis functions, prediction and cross validation ; design of optimal spatial sampling networks based on GEVcdn GEV conditional density estimation network 
GOGANPA GO-Functional-Network-based Gene-Set-Analysis 
gRain Graphical Independence Networks 
grnn General regression neural network 
igraph Network analysis and visualization 
igraphdata A collection of network data sets for the igraph package 
InteractiveIGraph interactive network analysis and visualization 
intergraph Coercion routines for network data objects in R 
interventionalDBN Interventional Inference for Dynamic Bayesian Networks 
latentnet Latent position and cluster models for statistical networks 
linkcomm Tools for Generating, Visualizing, and Analysing Link Communities in Networks 
LogitNet Infer network based on binary arrays using regularized logistic regression 
loop loop decomposition of weighted directed graphs for life cycle analysis, providing flexbile network plotting methods, and analyzing food chain properties in mlDNA Machine Learning-based Differential Network Analysis of Transcriptome Data 
monmlp Monotone multi-layer perceptron neural network 
MPINet The package can implement the network-based metabolite pathway identification of pathways 
mugnet Mixture of Gaussian Bayesian Network Model 
multiplex Analysis of Multiple Social Networks with Algebra 
ndtv Network Dynamic Temporal Visualizations 
netClass netClass : An R Package for Network-Based Biomarker Discovery 
NetCluster Clustering for networks 
NetComp Network Generation and Comparison 
NetData Network Data for McFarland’s SNA R labs 
NetIndices Estimating network indices, including trophic structure of foodwebs in R
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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R 
LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň 
LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň 
Ǩǩǫ packages ayant le mot « network » dans leur titre ou leur description sur CRAN 
netmeta Network meta-analysis with R 
NetPreProc NetPreProc : Network Pre-Processing and normalization 
nets Network Estimation for Time Series 
NetSim A Social Networks Simulation Tool in R 
netweavers NetWeAvers : Weighted Averages for Networks 
network Classes for Relational Data 
networkDynamic Dynamic Extensions for Network Objects 
networkDynamicData dynamic network datasets 
networkreporting Tools for using network reporting estimators 
networksis Simulate bipartite graphs with fixed marginals through sequential importance sampling 
networkTomography Tools for network tomography 
neuralnet Training of neural networks 
nnet Feed-forward Neural Networks and Multinomial Log-Linear Models 
nws R functions for NetWorkSpaces and Sleigh 
parmigene Parallel Mutual Information estimation for Gene Network reconstruction 
pcnetmeta Methods for patient-centered network meta-analysis 
pnn Probabilistic neural networks 
qgraph Network representations of relationships in data 
qrnn Quantile regression neural network 
qtlnet Causal Inference of QTL Networks 
QuACN QuACN : Quantitative Analysis of Complex Networks 
queueing Analysis of Queueing Networks and Models 
rbmn Handling Linear Gaussian Bayesian Networks 
RCurl General network (HTTP/FTP/...) client interface for R 
rDNA R Bindings for the Discourse Network Analyzer
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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R 
LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň 
LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň 
Ǩǩǫ packages ayant le mot « network » dans leur titre ou leur description sur CRAN 
ResistorArray electrical properties of resistor networks 
RSiena Siena - Simulation Investigation for Empirical Network Analysis 
RSNNS Neural Networks in R using the Stuttgart Neural Network Simulator (SNNS) 
sand Statistical Analysis of Network Data with R 
sbioPN sbioPN : Simulation of deterministic and stochastic spatial biochemical reaction networks using Petri Nets 
sdnet SoƜ Discretization-based Bayesian Network Inference 
SIMMS Subnetwork Integration for Multi-Modal Signatures 
simone Statistical Inference for MOdular NEtworks (SIMoNe) 
sna Tools for Social Network Analysis 
SNFtool Similarity Network Fusion 
snow Simple Network of Workstations 
snowFT Fault Tolerant Simple Network of Workstations 
SocialNetworks Generates social networks based on distance 
SSN Spatial Modeling on Stream Networks 
statnet SoƜware tools for the Statistical Analysis of Network Data 
SyNet Inference and Analysis of Sympatry Networks 
TeachNet Fits neural networks to learn about back propagation 
tergm Fit, Simulate and Diagnose Models for Network Evolution based on Exponential-Family Random Graph Models 
timeordered Time-ordered and time-aggregated network analyses 
tnet tnet : SoƜware for Analysis of Weighted, Two-mode, and Longitudinal networks 
transnet Conducts transmission modeling on a bayesian network 
VBLPCM Variational Bayes Latent Position Cluster Model for networks 
wccsom SOM networks for comparing patterns with peak shiƜs 
WGCNA Weighted Correlation Network Analysis
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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R 
LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň 
LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň 
Les packages généralistes 
Statnet/network : anciennement sna ; développé par Carter Butts (univ. de 
Californie). Particulièrement bien fourni pour la modélisation ; 
Igraph : développé par Gabor Csardi (univ. de Budapest). Davantage 
d’indicateurs et de métriques — disponible sous R, Python et C ; 
le package intergraph permet des conversions d’objets network <> igraph.
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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R 
LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň 
LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň 
Packages spécialisés 
gplot : visualisation de graphes produits avec statnet ; 
bipartite : analyse de réseaux bipartis ; 
tnet : analyse de réseaux valués ; 
egonet : extraction et analyse de réseau égocentrés ; 
ndtv : visualisation dynamique de réseaux igraph (produit des .gif).
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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R 
RĹňňŃŊŇķĹň Ĺł ŀĽĻłĹ 
RĹňňŃŊŇķĹň ĸĹ ĺŃŇŁĵʼnĽŃł Ĺł ŀĽĻłĹ 
Tutoriels (en français) 
Un présentation générale, basée sur statnet : 
Barnier J. ǩǧǨǨ, Analyse de réseaux avec R, http://alea.fr.eu.org/. 
Un tutoriel pas-à-pas plus avancé, présentant plusieurs packages : 
Beauguitte L. ǩǧǨǨ, Analyser les réseaux avec R (packages statnet, igraph et tnet), FMR.
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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R 
RĹňňŃŊŇķĹň Ĺł ŀĽĻłĹ 
RĹňňŃŊŇķĹň ĸĹ ĺŃŇŁĵʼnĽŃł Ĺł ŀĽĻłĹ 
Articles dans le R Journal 
http://journal.r-project.org/ 
Hankin ǩǧǧǭ, “Electrical properties of resistor networks”. R News, ǭ(ǩ) : Ǭǩ-ǬǪ. 
Long & Carey ǩǧǧǭ, “Graphs and networks : Tools in Bioconductor”. R News, ǭ(Ǭ) : ǩ–Ǯ. 
Schäfer, Opgen-Rhein & Strimmer ǩǧǧǭ, “Reverse engineering genetic networks using the 
GeneNet package”. R News, ǭ(Ǭ) : Ǭǧ–ǬǪ. 
Dormann, Gruber & Fründ ǩǧǧǯ, “Introducing the bipartite package : Analysing ecological 
networks”. R News, ǯ(ǩ) : ǯ–ǨǨ. 
Articles dans le J. of Statistical SoƜware 
http://www.jstatsoft.org 
Butts & Carter ǩǧǧǯ, “Social network analysis with sna”. Journal of Statistical SoƜware, ǩǫ(ǭ) : 
Ǩ–ǬǨ. 
Butts & Carter ǩǧǧǯ, “network : A Package for Managing Relational Data in R”. Journal of Statistical 
SoƜware, ǩǫ(ǩ) : Ǩ–Ǫǭ. 
Bender-deMoll, Morris & Moody ǩǧǧǯ, ”Prototype Packages for Managing and Animating 
Longitudinal Network Data : dynamicnetwork and rSoNIA”. Journal of Statistical SoƜware, ǩǫ(Ǯ).
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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R 
RĹňňŃŊŇķĹň Ĺł ŀĽĻłĹ 
RĹňňŃŊŇķĹň ĸĹ ĺŃŇŁĵʼnĽŃł Ĺł ŀĽĻłĹ 
Sites internet 
Le site de statnet/sna : 
http://statnet.csde.washington.edu/ 
Le site de igraph : 
http://igraph.sourceforge.net/ 
Le groupe « Flux, matrices, réseaux » (FMR) : 
http://groupefmr.hypotheses.org/ 
Le site de Tore Opsahl, développeur de tnet : 
http://toreopsahl.com/ 
Le site de Julien Barnier, développeur de rgrs/questionr : 
http://alea.fr.eu.org/ 
Le site de l’International Network for Social Network Analysis (Sunbelt Social 
Networks Conference) : http://www.insna.org/
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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
MĵłĽńŊŀĹŇ ĵŋĹķ IĽʼnķņľ Ĺʼn ŋńĻŋ 
MĵłĽńŊŀĹŇ ĵŋĹķ IĽʼnķņľ Ĺʼn ŋńĻŋ 
Maintenant, quelques manipulations.
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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
Uł ĹŎĹŁńŀĹ ĸĹ ńŇŃľĹʼn 
Uł ĹŎĹŁńŀĹ ĸĹ ńŇŃľĹʼn 
Une étude de réception d’un ensemble d’articles scientifiques…
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L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R 
Uł ĹŎĹŁńŀĹ ĸĹ ńŇŃľĹʼn 
Questions, discussions… ? 
marion.maisonobe@univ-tlse2.fr 
sebastien.plutniak@ehess.fr

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Plutniak maisonobe resto atelier2-network

  • 1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R M͐ʼnŇĽŅŊĹň, ķŀŊňʼnĹŇĽłĻ, ŋĽňŊĵŀĽňĵʼnĽŃł Sébastien Plutniak1 Marion Maisonobe2 1Lisst-Cers, Ehess — 2Lisst-Cieu, Labex SMS ǨǬ mai ǩǧǨǫ ResTO, Toulouse
  • 2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R IłʼnŇŃĸŊķʼnĽŃł D͐ŇŃŊŀ͐ ĸĹ ŀ’ĵʼnĹŀĽĹŇ D͐ŇŃŊŀ͐ ĸĹ ŀ’ĵʼnĹŀĽĹŇ lj IłʼnŇŃĸŊķʼnĽŃł Déroulé de l’atelier Tour de table NJ PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R Les graphes, objets mathématiques et R Les package R concernant l’analyse de graphes Ressources en ligne Nj MĵłĽńŊŀĹŇ ĵŋĹķ IĽʼnķņľ Ĺʼn ŋńĻŋ nj Uł ĹŎĹŁńŀĹ ĸĹ ńŇŃľĹʼn
  • 3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R IłʼnŇŃĸŊķʼnĽŃł TŃŊŇ ĸĹ ʼnĵĶŀĹ TŃŊŇ ĸĹ ʼnĵĶŀĹ Pour commencer… Types de données relationnelles que chacun a à traiter ? Quels outils déjà utilisés ? Leurs limites éventuelles ? En conséquence, quels besoins ? (Quelle connaissance préalable de R ? )
  • 4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R LĹň ĻŇĵńļĹň, ŃĶľĹʼnň Łĵʼnļ͐ŁĵʼnĽŅŊĹň Ĺʼn R LĹň ĻŇĵńļĹň, ŃĶľĹʼnň Łĵʼnļ͐ŁĵʼnĽŅŊĹň Ĺʼn R Le graphe comme objet mathématique Une graphe est composé : d’un ensemble d’éléments qui sont les sommets (ou noeuds) du graphe ; et d’un ensemble d’éléments qui sont les arètes (ou arcs) du graphe. Les arètes peuvent être orientées ou non. Implémentation minimale dans R un objet data.frame contenant une liste d’arètes ; un objet matrix contenant une matrice carrée des (id des) noeuds en colonne, et la valeur des liens dans les cases (Ǩ ou ǧ pour les graphes non valués ; une valeur pour les graphes valués).
  • 5. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň Ǩǩǫ packages ayant le mot « network » dans leur titre ou leur description sur CRAN abn Data Modelling with Additive Bayesian Networks amen Additive and multiplicative effects modeling of networks and relational data AMORE A MORE flexible neural network package ANN Feedforward Artificial Neural Network optimized by Genetic Algorithm ARTIVA Infer a time-varying DBN network from time series data BiomarkeR Paired (pBI) and Unpaired Biomarker Identifier (uBI) including a method to infer networks bionetdata Biological and chemical data networks bioPN Simulation of deterministic and stochastic biochemical reaction networks using Petri Nets bipartite Visualising bipartite networks and calculating some (ecological) indices blkergm Fitting block ERGM given the block structure on social networks blockmodeling An R package for Generalized and classical blockmodeling of valued networks BMN The pseudo-likelihood method for pairwise binary markov networks bnlearn Bayesian network structure learning, parameter learning and inference BoolNet Generation, reconstruction, simulation and analysis of synchronous, asynchronous, and probabilistic Boolean networks brnn brnn (Bayesian regularization for feed-forward neural networks) cǪnet Infering large-scale gene networks with CǪNET CaDENCE Conditional Density Estimation Network Construction and Evaluation catnet Categorical Bayesian Network Inference CCMnet Simulate Congruence Class Model for Networks CHCN Canadian Historical Climate Network CIDnetworks Generative models for networks with conditionally independent dyadic structure condmixt Conditional Density Estimation with Neural Network Conditional Mixtures COSINE COndition SpecIfic sub-NEtwork crn Downloads and Builds datasets for Climate Reference Network dǪNetwork Tools for creating DǪ JavaScript network and tree graphs from R
  • 6. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň Ǩǩǫ packages ayant le mot « network » dans leur titre ou leur description sur CRAN ddepn Dynamic Deterministic Effects Propagation Networks : Infer signalling networks for timecourse RPPA data deal Learning Bayesian Networks with Mixed Variables degreenet Models for Skewed Count Distributions Relevant to Networks diagram Functions for visualising simple graphs (networks), plotting flow diagrams dils Data-Informed Link Strength. Combine multiple-relationship networks into a single weighted network. Impute (fill-in) missing network links dna Differential Network Analysis dnet Integrative analysis of digitised data in terms of network, ontology and evolution Dominance ADI (average dominance index), social network graphs with dual directions, and music notation graph dvn Access to The Dataverse Network APIs ebdbNet Empirical Bayes Estimation of Dynamic Bayesian Networks EDISON SoƜware for network reconstruction and changepoint detection egonet Tool for ego-centric measures in Social Network Analysis elmNN Implementation of ELM (Extreme Learning Machine ) algorithm for SLFN ( Single Hidden Layer Feedforward Neural Networks ) ENA Ensemble Network Aggregation enaR Tools for ecological network analysis (ena) in R epinet A collection of epidemic/network-related tools ergm Fit, Simulate and Diagnose Exponential-Family Models for Networks ergm.count Fit, Simulate and Diagnose Exponential-Family Models for Networks with Count Edges ergmharris Local Health Department network data set foodweb visualisation and analysis of food web networks GǨDBN A package performing Dynamic Bayesian Network inference GANPA Gene Association Network-based Pathway Analysis gemtc GeMTC network meta-analysis GeneNet Modeling and Inferring Gene Networks GeneReg Construct time delay gene regulatory network
  • 7. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň Ǩǩǫ packages ayant le mot « network » dans leur titre ou leur description sur CRAN geospt Spatial geostatistics ; some geostatistical and radial basis functions, prediction and cross validation ; design of optimal spatial sampling networks based on GEVcdn GEV conditional density estimation network GOGANPA GO-Functional-Network-based Gene-Set-Analysis gRain Graphical Independence Networks grnn General regression neural network igraph Network analysis and visualization igraphdata A collection of network data sets for the igraph package InteractiveIGraph interactive network analysis and visualization intergraph Coercion routines for network data objects in R interventionalDBN Interventional Inference for Dynamic Bayesian Networks latentnet Latent position and cluster models for statistical networks linkcomm Tools for Generating, Visualizing, and Analysing Link Communities in Networks LogitNet Infer network based on binary arrays using regularized logistic regression loop loop decomposition of weighted directed graphs for life cycle analysis, providing flexbile network plotting methods, and analyzing food chain properties in mlDNA Machine Learning-based Differential Network Analysis of Transcriptome Data monmlp Monotone multi-layer perceptron neural network MPINet The package can implement the network-based metabolite pathway identification of pathways mugnet Mixture of Gaussian Bayesian Network Model multiplex Analysis of Multiple Social Networks with Algebra ndtv Network Dynamic Temporal Visualizations netClass netClass : An R Package for Network-Based Biomarker Discovery NetCluster Clustering for networks NetComp Network Generation and Comparison NetData Network Data for McFarland’s SNA R labs NetIndices Estimating network indices, including trophic structure of foodwebs in R
  • 8. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň Ǩǩǫ packages ayant le mot « network » dans leur titre ou leur description sur CRAN netmeta Network meta-analysis with R NetPreProc NetPreProc : Network Pre-Processing and normalization nets Network Estimation for Time Series NetSim A Social Networks Simulation Tool in R netweavers NetWeAvers : Weighted Averages for Networks network Classes for Relational Data networkDynamic Dynamic Extensions for Network Objects networkDynamicData dynamic network datasets networkreporting Tools for using network reporting estimators networksis Simulate bipartite graphs with fixed marginals through sequential importance sampling networkTomography Tools for network tomography neuralnet Training of neural networks nnet Feed-forward Neural Networks and Multinomial Log-Linear Models nws R functions for NetWorkSpaces and Sleigh parmigene Parallel Mutual Information estimation for Gene Network reconstruction pcnetmeta Methods for patient-centered network meta-analysis pnn Probabilistic neural networks qgraph Network representations of relationships in data qrnn Quantile regression neural network qtlnet Causal Inference of QTL Networks QuACN QuACN : Quantitative Analysis of Complex Networks queueing Analysis of Queueing Networks and Models rbmn Handling Linear Gaussian Bayesian Networks RCurl General network (HTTP/FTP/...) client interface for R rDNA R Bindings for the Discourse Network Analyzer
  • 9. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň Ǩǩǫ packages ayant le mot « network » dans leur titre ou leur description sur CRAN ResistorArray electrical properties of resistor networks RSiena Siena - Simulation Investigation for Empirical Network Analysis RSNNS Neural Networks in R using the Stuttgart Neural Network Simulator (SNNS) sand Statistical Analysis of Network Data with R sbioPN sbioPN : Simulation of deterministic and stochastic spatial biochemical reaction networks using Petri Nets sdnet SoƜ Discretization-based Bayesian Network Inference SIMMS Subnetwork Integration for Multi-Modal Signatures simone Statistical Inference for MOdular NEtworks (SIMoNe) sna Tools for Social Network Analysis SNFtool Similarity Network Fusion snow Simple Network of Workstations snowFT Fault Tolerant Simple Network of Workstations SocialNetworks Generates social networks based on distance SSN Spatial Modeling on Stream Networks statnet SoƜware tools for the Statistical Analysis of Network Data SyNet Inference and Analysis of Sympatry Networks TeachNet Fits neural networks to learn about back propagation tergm Fit, Simulate and Diagnose Models for Network Evolution based on Exponential-Family Random Graph Models timeordered Time-ordered and time-aggregated network analyses tnet tnet : SoƜware for Analysis of Weighted, Two-mode, and Longitudinal networks transnet Conducts transmission modeling on a bayesian network VBLPCM Variational Bayes Latent Position Cluster Model for networks wccsom SOM networks for comparing patterns with peak shiƜs WGCNA Weighted Correlation Network Analysis
  • 10. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň Les packages généralistes Statnet/network : anciennement sna ; développé par Carter Butts (univ. de Californie). Particulièrement bien fourni pour la modélisation ; Igraph : développé par Gabor Csardi (univ. de Budapest). Davantage d’indicateurs et de métriques — disponible sous R, Python et C ; le package intergraph permet des conversions d’objets network <> igraph.
  • 11. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň LĹň ńĵķĿĵĻĹ R ķŃłķĹŇłĵłʼn ŀ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň Packages spécialisés gplot : visualisation de graphes produits avec statnet ; bipartite : analyse de réseaux bipartis ; tnet : analyse de réseaux valués ; egonet : extraction et analyse de réseau égocentrés ; ndtv : visualisation dynamique de réseaux igraph (produit des .gif).
  • 12. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R RĹňňŃŊŇķĹň Ĺł ŀĽĻłĹ RĹňňŃŊŇķĹň ĸĹ ĺŃŇŁĵʼnĽŃł Ĺł ŀĽĻłĹ Tutoriels (en français) Un présentation générale, basée sur statnet : Barnier J. ǩǧǨǨ, Analyse de réseaux avec R, http://alea.fr.eu.org/. Un tutoriel pas-à-pas plus avancé, présentant plusieurs packages : Beauguitte L. ǩǧǨǨ, Analyser les réseaux avec R (packages statnet, igraph et tnet), FMR.
  • 13. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R RĹňňŃŊŇķĹň Ĺł ŀĽĻłĹ RĹňňŃŊŇķĹň ĸĹ ĺŃŇŁĵʼnĽŃł Ĺł ŀĽĻłĹ Articles dans le R Journal http://journal.r-project.org/ Hankin ǩǧǧǭ, “Electrical properties of resistor networks”. R News, ǭ(ǩ) : Ǭǩ-ǬǪ. Long & Carey ǩǧǧǭ, “Graphs and networks : Tools in Bioconductor”. R News, ǭ(Ǭ) : ǩ–Ǯ. Schäfer, Opgen-Rhein & Strimmer ǩǧǧǭ, “Reverse engineering genetic networks using the GeneNet package”. R News, ǭ(Ǭ) : Ǭǧ–ǬǪ. Dormann, Gruber & Fründ ǩǧǧǯ, “Introducing the bipartite package : Analysing ecological networks”. R News, ǯ(ǩ) : ǯ–ǨǨ. Articles dans le J. of Statistical SoƜware http://www.jstatsoft.org Butts & Carter ǩǧǧǯ, “Social network analysis with sna”. Journal of Statistical SoƜware, ǩǫ(ǭ) : Ǩ–ǬǨ. Butts & Carter ǩǧǧǯ, “network : A Package for Managing Relational Data in R”. Journal of Statistical SoƜware, ǩǫ(ǩ) : Ǩ–Ǫǭ. Bender-deMoll, Morris & Moody ǩǧǧǯ, ”Prototype Packages for Managing and Animating Longitudinal Network Data : dynamicnetwork and rSoNIA”. Journal of Statistical SoƜware, ǩǫ(Ǯ).
  • 14. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R PĵłŃŇĵŁĵ ĸĹň ńŃňňĽĶĽŀĽʼn͐ň ĸ’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹ ňŃŊň R RĹňňŃŊŇķĹň Ĺł ŀĽĻłĹ RĹňňŃŊŇķĹň ĸĹ ĺŃŇŁĵʼnĽŃł Ĺł ŀĽĻłĹ Sites internet Le site de statnet/sna : http://statnet.csde.washington.edu/ Le site de igraph : http://igraph.sourceforge.net/ Le groupe « Flux, matrices, réseaux » (FMR) : http://groupefmr.hypotheses.org/ Le site de Tore Opsahl, développeur de tnet : http://toreopsahl.com/ Le site de Julien Barnier, développeur de rgrs/questionr : http://alea.fr.eu.org/ Le site de l’International Network for Social Network Analysis (Sunbelt Social Networks Conference) : http://www.insna.org/
  • 15. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R MĵłĽńŊŀĹŇ ĵŋĹķ IĽʼnķņľ Ĺʼn ŋńĻŋ MĵłĽńŊŀĹŇ ĵŋĹķ IĽʼnķņľ Ĺʼn ŋńĻŋ Maintenant, quelques manipulations.
  • 16. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R Uł ĹŎĹŁńŀĹ ĸĹ ńŇŃľĹʼn Uł ĹŎĹŁńŀĹ ĸĹ ńŇŃľĹʼn Une étude de réception d’un ensemble d’articles scientifiques…
  • 17. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L’ĵłĵŀŏňĹ ĸĹ ĻŇĵńļĹň ĵŋĹķ R Uł ĹŎĹŁńŀĹ ĸĹ ńŇŃľĹʼn Questions, discussions… ? marion.maisonobe@univ-tlse2.fr sebastien.plutniak@ehess.fr