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Note
titlePrerequisites

It is recommended that you familiarise yourself with R first by sitting our Introduction to R tutorial.

It also requires that you have the DataSHIELD training environment installed on your machine, see our Installation Instructions for Linux, Windows, or Mac.


Tip
titleHelp

DataSHIELD support is freely available in the DataSHIELD forum by the DataSHIELD community. Please use this as the first port of call for any problems you may be having, it is monitored closely for new threads.

DataSHIELD bespoke user support and also user training classes are offered on a fee-paying basis. Please enquire at datashield@newcastle.ac.uk for current prices. 

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Quick reminder for logging in:

#load

Start R/RStudio

Load Packages

Expand

Recall from the installation instructions, the Opal web interface is a simple check to tell if the VMs have started. Load the following urls, waiting at least 1 minute after starting the training VMs.

Start R/RStudio

Load Packages

Code Block
xmlxml
Code Block
xml
xml
#load libraries
library(DSI)
library(DSOpal)
library(dsBaseClient)

Build your login dataframe 

Code Block
languagexml
titleBuild your login dataframe
builder <- DSI::newDSLoginBuilder()
builder <- DSI::newDSLoginBuilder()
builder$append(server = "study1server1",  url = "httphttps://192opal-demo.168.56.100:8080/",
               user = "administrator", password = "datashield_test&",
               table = "CNSIM.CNSIM1obiba.org/",
user = "dsuser", password = "P@ssw0rd", driver = "OpalDriver", options='list(ssl_verifyhost=0, ssl_verifypeer=0)')
builder$append(server = "study2server2", url = "httphttps://192.168.56.101:8080/",
              opal-demo.obiba.org/",
user = "administratordsuser", password = "datashield_test&P@ssw0rd",                table driver = "CNSIM.CNSIM2OpalDriver", driver = "OpalDriver"options='list(ssl_verifyhost=0, ssl_verifypeer=0)')

logindata <- builder$build()

logindata <- builder$build()

connections <- DSI::datashield.login(logins = logindata, assign = TRUE)
DSI::datashield.assign.table(conns = connections, symbol = "D""DST", table = c("CNSIM.CNSIM1","CNSIM.CNSIM2"))
  • Command to logout:
Code Block
languagebash
DSI::datashield.logout(connections)


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Code Block
languagexml
ds.log(x='D$LABDST$LAB_HDL', datasources = connections)

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Code Block
themeRDark
  Aggregated (exists("DDST")) [=============================================================] 100% / 0s
  Aggregated (classDS("D$LABDST$LAB_HDL")) [====================================================] 100% / 1s
  Assigned expr. (log.newobj <- log(D$LABDST$LAB_HDL,2.71828182845905)) [=======================] 100% / 0s
  Aggregated (exists("log.newobj")) [====================================================] 100% / 0s

...

Code Block
languagexml
ds.log(x='D$LABDST$LAB_HDL', newobj='LAB_HDL_log', datasources = connections)

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Code Block
languagexml
ds.assign(toAssign='D$LABDST$LAB_HDL-1.562', newobj='LAB_HDL.c', datasources = connections)

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Code Block
languagexml
ds.table(rvar="D$GENDERDST$GENDER")


Code Block
themeRDark
  Aggregated (asFactorDS1("D$GENDERDST$GENDER")) [=================================================] 100% / 0s
  Aggregated (tableDS(rvar.transmit = "D$GENDERDST$GENDER", cvar.transmit = NULL, stvar.transmit = NULL, ) ...

 Data in all studies were valid 

Study 1 :  No errors reported from this study
Study 2 :  No errors reported from this study

$output.list
$output.list$TABLE_rvar.by.study_row.props
        study
D$GENDERDST$GENDER         1         2
       0 0.4079193 0.5920807
       1 0.4160839 0.5839161

$output.list$TABLE_rvar.by.study_col.props
        study
D$GENDERDST$GENDER         1         2
       0 0.5048544 0.5132772
       1 0.4951456 0.4867228

$output.list$TABLE_rvar.by.study_counts
        study
D$GENDERDST$GENDER    1    2
       0 1092 1585
       1 1071 1503

$output.list$TABLES.COMBINED_all.sources_proportions
D$GENDERDST$GENDER
   0    1 
0.51 0.49 

$output.list$TABLES.COMBINED_all.sources_counts
D$GENDERDST$GENDER
   0    1 
2677 2574 


$validity.message
[1] "Data in all studies were valid"

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Code Block
languagexml
ds.table(rvar='D$DISDST$DIS_DIAB', cvar='D$GENDERDST$GENDER', datasources = connections)

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Code Block
themeRDark
  Aggregated (asFactorDS1("D$DISDST$DIS_DIAB")) [===============================================] 100% / 0s
  Aggregated (asFactorDS1("D$GENDERDST$GENDER")) [=================================================] 100% / 0s
  Aggregated (tableDS(rvar.transmit = "D$DISDST$DIS_DIAB", cvar.transmit = "D$GENDERDST$GENDER", ) [======] 100% / 0s

 Data in all studies were valid 

Study 1 :  No errors reported from this study
Study 2 :  No errors reported from this study

$output.list
$output.list$TABLE.STUDY.1_row.props
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB     0     1
         0 0.502 0.498
         1 0.700 0.300

$output.list$TABLE.STUDY.1_col.props
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB      0      1
         0 0.9810 0.9920
         1 0.0192 0.0084

$output.list$TABLE.STUDY.2_row.props
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB     0     1
         0 0.511 0.489
         1 0.660 0.340

$output.list$TABLE.STUDY.2_col.props
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB      0      1
         0 0.9800 0.9890
         1 0.0196 0.0106

$output.list$TABLES.COMBINED_all.sources_row.props
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB     0     1
         0 0.507 0.493
         1 0.675 0.325

$output.list$TABLES.COMBINED_all.sources_col.props
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB      0       1
         0 0.9810 0.99000
         1 0.0194 0.00971

$output.list$TABLE_STUDY.1_counts
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB    0    1
         0 1071 1062
         1   21    9

$output.list$TABLE_STUDY.2_counts
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB    0    1
         0 1554 1487
         1   31   16

$output.list$TABLES.COMBINED_all.sources_counts
          D$GENDERDST$GENDER
D$DISDST$DIS_DIAB    0    1
         0 2625 2549
         1   52   25


$validity.message
[1] "Data in all studies were valid"

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Code Block
languagexml
ds.table(rvar='D$DISDST$DIS_DIAB', cvar='D$GENDERDST$GENDER', datasources = connections, report.chisq.tests = TRUE)

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Tip

Also remember you can:

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