inst/doc/general_overview.R

## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(echo = TRUE)

## ----eval=FALSE---------------------------------------------------------------
#  if (!requireNamespace("BiocManager", quietly=TRUE))
#      install.packages("BiocManager")
#  BiocManager::install( "psygenet2r" )

## ----load_library, messages=FALSE---------------------------------------------
library( psygenet2r )

## ----dataGenet1, echo=FALSE---------------------------------------------------
t1 <- psygenetGene( gene = 4852, 
                    database = "ALL")

## ----dataGenet2---------------------------------------------------------------
t1
class( t1 )

## ----search_gene_1------------------------------------------------------------
t1 <- psygenetGene( gene = 4852, 
                    database = "ALL")
t1

## ----search_gene_2------------------------------------------------------------
t2 <- psygenetGene( gene = "NPY", 
                    database = "ALL" )
t2

## ----searcg_gene_class--------------------------------------------------------
class( t1 )
class( t2 )

## ----plot_disease, fig.width=8, fig.height=8----------------------------------
plot( t1, type = "GDA network" )

## ----plot_psychiatric, fig.width=8, fig.height=8------------------------------
plot( t1, type = "GDCA network" )

## ----search_multiple_genes----------------------------------------------------
genesOfInterest <- c( "COMT", "CLOCK", "DRD3", "GNB3", "HTR1A",
    "MAOA", "HTR2A","HTR2C", "HTR6", "SLC6A4", "ACE",  "BDNF", 
    "DRD4", "HTR1B", "HTR2B", "HTR2C", "MTHFR", "SLC6A3", "TPH1", 
    "SLC6A2", "GABRA3"
)

## ----search_multiple_search---------------------------------------------------
m1 <- psygenetGene(
    gene     = genesOfInterest, 
    database = "ALL",
    verbose  = TRUE
)

## ----show_multiple------------------------------------------------------------
m1

## ----plot_psychiatric1a,  fig.height=8, fig.width=8---------------------------
plot( m1 )

## ----plot_psychiatric1b, warning=FALSE,  fig.height=8, fig.width=8------------
plot( m1, type = "GDCA network" )

## ----heatmap_disease_m,  fig.height=8, fig.width=8----------------------------
plot( m1, type="GDA heatmap" )

## ----plot_psychiatric_heamap, warning = FALSE,  fig.height=8, fig.width=8-----
plot( m1, type = "GDCA heatmap" )

## ----panther_gene,  fig.height=8, fig.width=8---------------------------------
genesOfInterest <- unique( genesOfInterest )
pantherGraphic( genesOfInterest, "ALL" )

## ----plot_diseaseBarplot,  fig.height=8, fig.width=8--------------------------
geneAttrPlot( m1, type = "disease category" )

## ----plot_diseaseBarplotGene,  fig.height=8, fig.width=8----------------------
geneAttrPlot( m1, type = "gene" )

## ----plot_pie, fig.width=8, fig.height=8--------------------------------------
geneAttrPlot( m1, type = "pie" )

## ----barplotIP, fig.width=8, fig.height=8-------------------------------------
geneAttrPlot( m1, type = "evidence index" )

## ----enrichment---------------------------------------------------------------
tbl <- enrichedPD( genesOfInterest, database = "ALL")
tbl

## ----topAnat, eval=FALSE------------------------------------------------------
#  tpAnat <- topAnatEnrichment( genesOfInterest, cutOff = 1 )

## ----load_topAnat, echo=FALSE-------------------------------------------------
load( system.file( "extdata", "topAnat.RData", package="psygenet2r" ) )

## ----show_topAnat-------------------------------------------------------------
head( tpAnat )

## ----gda_sentenceGene---------------------------------------------------------
genesOfInterest
sss <- psygenetGeneSentences( geneList = genesOfInterest,
                             database = "ALL")
sss

geneSentences <- extractSentences( object = sss,
                                   disorder = "alcohol abuse")
head(geneSentences)
dim( geneSentences )

## ----getUMLS------------------------------------------------------------------
getUMLs( "depressive", database = "ALL" )

## ----search_diseaseId_1-------------------------------------------------------
d1 <- psygenetDisease( disease  = "umls:C1839839", 
                       database = "ALL", 
                       evidenceIndex    = c('>', 0.5 ) )
d1

## ----search_diseaseName_1-----------------------------------------------------
d2 <- psygenetDisease( disease = "major affective disorder 2", 
                       database = "ALL",
                       evidenceIndex    = c('>', 0.5 ) )
d2

## ----search_gene_class--------------------------------------------------------
class( d1 )
class( d2 )

## ----plot_visualizing_single_disease_search, fig.width=8, fig.height=8--------
plot ( d1, 
       geneColor    = "turquoise2", 
       diseaseColor = "black")

## ----diseaseList--------------------------------------------------------------
diseasesOfInterest <- c( "chronic schizophrenia","alcohol use disorder" )

## ----search_diseases_1--------------------------------------------------------
tt <- psygenetDisease( disease  = diseasesOfInterest,
                       database = "ALL" )
tt

## ----search_diseases_2--------------------------------------------------------
dm <- psygenetDisease( disease  = c( "umls:C0221765", "umls:C0001956" ), 
                       database = "ALL" )
dm

## ----search_diseases_3--------------------------------------------------------
tm <- psygenetDisease( disease  = c( "chronic schizophrenia","umls:C0001956" ), 
                       database = "ALL" )
tm

## ----search_gene_class_2------------------------------------------------------
class( tt )
class( dm )
class( tm )

## ----plot_disease_tm----------------------------------------------------------
plot( tm )

## ----heatmap_disease_tm, warning = FALSE,  fig.wide = TRUE--------------------
plot( tm, type = "GDCA heatmap" )

## ----barplot_visualizing_single_disease_search, fig.width=8, fig.height=8-----
plot( d1, 
      name = "major affective disorder 2", 
      type = "publications" )

## ----barplot_visualizing_single_gene_search, fig.width=8, fig.height=8--------
plot( t1, 
      name     = "NPY", 
      type     = "publications",
      barColor = "blue")

## ----jaccardObjectEx1, echo=FALSE, warning=FALSE, message=FALSE---------------
genes_interest <- c("SLC6A4", "DRD2", "HTR1B", "PLP1", "TH", "DRD3")
ji1 <- jaccardEstimation(genes_interest, database = "ALL")

## ----jaccardObjectEx2---------------------------------------------------------
ji1
class( ji1 )

## ----ji_1, warnings=FALSE-----------------------------------------------------
genes_interest <- c("SLC6A4", "DRD2", "HTR1B", "PLP1", "TH", "DRD3")
ji1 <- jaccardEstimation(genes_interest, database = "ALL")

## ----ji_2, warnings=FALSE-----------------------------------------------------
disease_interest <- 
  c("delirium", "bipolar i disorder", "severe depression", "cocaine dependence")
ji2 <- jaccardEstimation(genes_interest, disease_interest, database = "ALL")

## ----ji_3, warnings=FALSE-----------------------------------------------------
ji3 <- jaccardEstimation(disease_interest, database = "ALL")

## ----ji1_extract--------------------------------------------------------------
head(extract(ji1))
tail(extract(ji1))

## ----ji1_plot, fig.width=8, fig.height=8--------------------------------------
plot(ji1, cutOff = 0.1)

## ----ji2_plot, fig.width=8, fig.height=8--------------------------------------
plot(ji2)

## ----ji3_plot, fig.width=8, fig.height=8--------------------------------------
plot(ji3)

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psygenet2r documentation built on Jan. 31, 2021, 2 a.m.