## ---- eval=F, echo=T-----------------------------------------------------
# ?dbgapr
## ---- eval=F, echo=T-----------------------------------------------------
# c <- Commons()
# prjConfig(c, prjDir="/home/foo/myprj")
## ---- eval=F, echo=T-----------------------------------------------------
# prjConfig(c, prjDir="/home/foo/myprj") # all platforms
# prjConfig(c, prjDir="~/myprj") # all platforms
# prjConfig(c, prjDir="C:/Users/foo/myprj") # Windows
# prjConfig(c, prjDir="C:\\Users\\foo\\myprj") # Windows
## ---- eval=F, echo=T-----------------------------------------------------
# dir("~/myprj")
## ---- eval=F, echo=T-----------------------------------------------------
# c <- Commons()
# getPrjDir(c, showErr=TRUE)
## ---- eval=F, echo=T-----------------------------------------------------
# c <- Commons()
## ---- eval=F, echo=T-----------------------------------------------------
# c <- Commons()
# prepareData(c, userDataDir='/home/foo/my_data')
## ---- eval=F, echo=T-----------------------------------------------------
# c <- Commons()
# prepareData(c, userDataDir='/home/foo/my_data', phsAcc='phs000001.v3.p1')
## ---- eval=F, echo=T-----------------------------------------------------
# c <- Commons()
# searchCopyPhenoFiles(c, userDataDir='~/my_data')
# # or to only copy the files of a specific study
# searchCopyPhenoFiles(c, userDataDir='~/my_data', phsAcc="phs000001.v3.p1")
## ---- eval=F, echo=T-----------------------------------------------------
# c <- Commons()
# searchCopyPhenoFiles(c, userDataDir='~/my_data', copyOrMove = 'move')
## ---- eval=F, echo=T, tidy=TRUE, tidy.opts=list(width.cutoff=60)---------
# dir("~/myprj/gapwork/data/phs000001/phs000001.v3/original")
## ---- eval=F, echo=T, tidy=TRUE, tidy.opts=list(width.cutoff=60)---------
# dir("~/myprj/gapwork/data")
## ---- eval=F, echo=T-----------------------------------------------------
# c <- Commons()
# ftpDownload(c)
# # or to limit the download to a specific study
# ftpDownload(c, phsAcc="phs000001.v3.p1")
## ---- eval=F, echo=T, tidy=TRUE, tidy.opts=list(width.cutoff=60)---------
# dir("~/.dbgapr/supplemental_data")
## ---- eval=F, echo=T, tidy=TRUE, tidy.opts=list(width.cutoff=60)---------
# dir("~/myprj/gapwork/data/phs000001/phs000001.v3/supplemental_data")
## ---- eval=F, echo=T-----------------------------------------------------
# c <- Commons()
# recordPrjFileInfo(c)
# # or to process only specific study
# recordPrjFileInfo(c, phsAcc="phs000001.v3.p1")
## ---- eval=F, echo=T-----------------------------------------------------
# file.show("~/.dbgapr/pht_file_info_indiv.json")
## ---- eval=F, echo=T-----------------------------------------------------
# c <- Commons()
# mergeDatasetConsent(c)
# # or to only merged the files of a specific study
# mergeDatasetConsent(c, phsAcc='phs000001.v3.p1')
## ---- eval=F, echo=T-----------------------------------------------------
# dir("~/myprj/gapwork/data/phs000001/phs000001.v3/original")
## ---- eval=F, echo=T-----------------------------------------------------
# dir("~/myprj/gapwork/data/phs000001/phs000001.v3/combined")
## ---- eval=F, echo=T-----------------------------------------------------
# dir("~/myprj/gapwork/data/phs000001/phs000001.v3/combined/log")
#
## ---- eval=F, echo=T-----------------------------------------------------
# c <- Commons()
# df <- accInfo(c, acc='phs000001.v3.p1') # study
## ---- eval=F, echo=T-----------------------------------------------------
# c <- Commons()
# df <- accInfo(c, acc='pht000370.v2') # dataset
## ---- eval=F, echo=T-----------------------------------------------------
# c <- Commons()
# df <- accInfo(c, acc='phv00000084.v2') # variable of integer type
## ---- eval=F, echo=T-----------------------------------------------------
# c <- Commons()
# df <- accInfo(c, acc='phv00000031.v2') # varible of enum_integer type
## ---- eval=F, echo=T-----------------------------------------------------
# c <- Commons()
# df <- getAllStudyInfo(c)
# # or
# # display result as a table
# df <- getAllStudyInfo(c, showAs='table')
# # or
# # display result in json with notepad
# df <- getAllStudyInfo(c, showAs='json', editor='notepad')
## ---- eval=F, echo=T-----------------------------------------------------
# c <- Commons()
# df <- getAllDatasetInfo(c)
# # or
# # display result as a table
# df <- getAllDatasetInfo(c, showAs='table')
# # or
# # display result in json format with notepad
# df <- getAllDatasetInfo(c, showAs='json', editor='notepad')
# # or
# # display result in a text format
# df <- getAllDatasetInfo(c, showAs='text')
## ---- eval=F, echo=T-----------------------------------------------------
# s <- Study(phsAcc='phs000001.v3.p1')
# # all study variables
# df <- getStudyVariableInfo(s)
# # or
# # display result as a table
# df <- getStudyVariableInfo(s, showAs='table') ·
# # or
# # all dataset variables
# df <- getStudyVariableInfo(s, phtAcc='pht000370.v2.p1')
# # or
# # all dataset variables of numerical type
# df <- getStudyVariableInfo(s, phtAcc='pht000370.v2.p1', dataType = 'num')
# # or
# # a list of variables ·
# accList = c('phv00054119.v1.p1.c2', 'phv00054118.v1.p1')
# df <- getStudyVariableInfo(s, phvAccList=accList)
## ---- eval=F, echo=T-----------------------------------------------------
# s <- Study(phsAcc='phs000001.v3.p1')
#
# ##### Search for matches in variable descriptions #####
# # define search terms
# t1 = c('Diabetes Treatment', 'Smoking Status')
# t2 = c('Year 10')
# t3 = c('6 Months')
# # term match with 'Diabetes Treatment' OR 'Smoking Status'
# df <- getPhvAccListByTerms(s, terms_1=t1)
# # or
# # display matching variable in a table
# df <- getPhvAccListByTerms(s, terms_1=t1, showTable=T)
# # or
# # term match with ('Diabetes Treatment' OR 'Smoking Status') AND 'Year 10'
# df <- getPhvAccListByTerms(s, terms_1=t1, terms_2=t2, showTable=T)
# # or
# # term match with ('Diabetes Treatment' OR 'Smoking Status') AND 'Year 10' AND '6 Months'
# df <- getPhvAccListByTerms(s, terms_1=t1, terms_2=t2, terms_3=t3, showTable=T)
#
# ##### Search for matches in variable names #####
# t4 = 'SMK'
# t5 = 'AGE'
# # term match with 'SMK'
# df <- getPhvAccListByTerms(s, terms_1=t4, searchIn='name', showTable=T)
# # or
# # term match with 'SMK' AND 'AGE'
# df <- getPhvAccListByTerms(s, terms_1=t4, terms_2=t5, searchIn='name', showTable=T)
## ---- eval=F, echo=T-----------------------------------------------------
# s <- Study(phsAcc = 'phs000001.v3.p1')
# # get data of variables in a dataset
# df <- getStudyVariableData(s, phtAcc='pht000370.v2.p1')
# # or
# # get data of a list of variables
# # acc_list = c('phv00054119.v1.p1.c2', 'phv00053733.v2'))
# df <- getStudyVariableData(s, phvAccList=acc_list)
## ---- eval=F, echo=T-----------------------------------------------------
# s <- Study(phsAcc = 'phs000001.v3.p1')
# # variable data of a set of specified subjects in a dataset
# subj_ids = c(219, 220, 221)
# df <- getDatasetDataByPhtAcc(s, phtAcc='pht000371.v2', subjIdsOrFile=subj_ids)
# # or
# # variable data of a set of specified subjects in a dataset
# # The subject id file is a plain text file with one dbGaP_Subject_ID per line.
# subj_file = "~/my_data/subj_ids.txt"
# df <- getDatasetDataByPhtAcc(s, phtAcc='pht000371.v2', subjIdsOrFile=subj_file)
## ---- eval=F, echo=T-----------------------------------------------------
# s <- Study(phsAcc = 'phs000001.v3.p1')
# df <- getStudyVariableData(s, phtAcc='pht000370.v2.p1')
# # return column names
# colnames(df)
## ---- eval=F, echo=T-----------------------------------------------------
# s <- Study(phsAcc = 'phs000001.v3.p1')
# df <- getStudyVariableData(s, phtAcc='pht000370.v2.p1')
# # return column values
# head(subset(df, select=c('Submitted_Subject_ID', 'ID2')))
## ---- eval=F, echo=T-----------------------------------------------------
# s <- Study(phsAcc='phs000001.v3.p1')
# df <- getStudyVariableData(s, phtAcc='pht000370.v2.p1', colNameWithAcc=TRUE)
# # return column names
# colnames(df)
## ---- eval=F, echo=T-----------------------------------------------------
# s <- Study(phsAcc='phs000001.v3.p1')
# df <- variableSummary(s, phvAcc='phv00054119.v1.p1.c2') # numerical
## ---- eval=F, echo=T-----------------------------------------------------
# s <- Study(phsAcc='phs000001.v3.p1')
# df <- variableSummary(s, phvAcc='phv00000035.v2') # categorical
## ---- eval=F, echo=T-----------------------------------------------------
# s <- Study(phsAcc='phs000001.v3.p1')
# df <- variableBoxplot(s, numPhvAcc='phv00000027.v2', catPhvAcc='phv00000032.v2')
## ---- out.width = "600px", echo=FALSE------------------------------------
knitr::include_graphics("figure/boxplot_phv00000027.v2_AGEPHOT_phv00000032.v2_MARITAL.png")
## ---- eval=F, echo=T-----------------------------------------------------
# s <- Study(phsAcc='phs000001.v3.p1')
# num_1 = 'phv00000027.v2'
# num_2 = 'phv00053747.v2'
# cat_1 = 'phv00053757.v2'
# df <- variableScatterplot(s, numPhvAcc_1=num_1, numPhvAcc_2=num_2, catPhvAcc=cat_1)
## ---- out.width = "600px", out.height = "500px", echo=FALSE--------------
knitr::include_graphics("figure/scatterplot_phv00000027.v2_AGEPHOT_phv00053747.v2_LNUCSCORE_phv00053757.v2_RNUC.png")
## ---- eval=F, echo=T-----------------------------------------------------
# s <- Study(phsAcc='phs000001.v3.p1')
# # with density plot
# df <- variableHistogram(s, phvAcc='phv00053747.v2')
# # or
# # without Density plot·
# df <- variableHistogram(s, phvAcc='phv00053747.v2', withDensity=F)
## ---- out.width = "600px", echo=FALSE------------------------------------
knitr::include_graphics("figure/histogram_phv00053747.v2_LNUCSCORE.png")
## ---- eval=F, echo=T-----------------------------------------------------
# s <- Study(phsAcc='phs000001.v3.p1')
# # with density plot
# df <- variableHistogram(s, phvAcc='phv00053733.v2')
## ---- out.width = "600px", echo=FALSE------------------------------------
knitr::include_graphics("figure/barchart_phv00053733.v2_ADVSTAT.png")
## ---- eval=F, echo=T-----------------------------------------------------
# s <- Study(phsAcc='phs000001.v3.p1')
# df <- variablePiechart(s, catPhvAcc='phv00053764.v2')
## ---- out.width = "600px", echo=FALSE------------------------------------
knitr::include_graphics("figure/boxplot_phv00053764.v2_LPSC.png")
## ---- eval=F, echo=T-----------------------------------------------------
# s <- Study(phsAcc='phs000001.v3.p1')
# acc_list = c('phv00054139.v1', 'phv00053796.v2', 'phv00000089.v2')
# df <- variableVenndiagram(s, phvAccList=acc_list)
## ---- out.width = "600px", echo=FALSE------------------------------------
knitr::include_graphics("figure/VennDiagram_AGECT_phv00054139.v1_DT_PROA_phv00053796.v2_SYST07_phv00000089.v2.png")
## ---- eval=F, echo=T-----------------------------------------------------
# s <- Study(phsAcc='phs000001.v3.p1')
#
# phvAcc = 'phv00000031.v2'
# cat_acc = 'phv00000035.v2'
# # or
# num_acc_list = c('phv00000007.v2', 'phv00053794.v2', 'phv00053786.v2', 'phv00000106.v2')
# df <- variableCorrelHeatmap(s, catPhvAcc=catPhvAcc, numPhvAccList=numPhvAcc_list cc_list))
## ---- out.width = "600px", echo=FALSE------------------------------------
knitr::include_graphics("figure/correlmatrix_SCHOOL_phv00000035.v2_RCORBASE_phv00000007.v2_DT_LYC_phv00053794.v2_DT_VITE_phv00053786.v2_DIAS12_phv00000106.v2.png")
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