Package: dbGaPCheckup 1.2.0

dbGaPCheckup: dbGaP Checkup

Contains functions that check for formatting of the Subject Phenotype data set and data dictionary as specified by the National Center for Biotechnology Information (NCBI) Database of Genotypes and Phenotypes (dbGaP) <https://www.ncbi.nlm.nih.gov/gap/docs/submissionguide/>.

Authors:Lacey W. Heinsberg [aut, cre], Daniel E. Weeks [aut], University of Pittsburgh [cph]

dbGaPCheckup_1.2.0.tar.gz
dbGaPCheckup_1.2.0.zip(r-4.7-any)dbGaPCheckup_1.2.0.zip(r-4.6-any)dbGaPCheckup_1.2.0.zip(r-4.5-any)
dbGaPCheckup_1.2.0.tgz(r-4.6-any)dbGaPCheckup_1.2.0.tgz(r-4.5-any)
dbGaPCheckup_1.2.0.tar.gz(r-4.7-any)dbGaPCheckup_1.2.0.tar.gz(r-4.6-any)
dbGaPCheckup_1.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
dbGaPCheckup/json (API)

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

Bug tracker:https://github.com/lwheinsberg/dbgapcheckup/issues

Pkgdown/docs site:https://lwheinsberg.github.io

Datasets:

On CRAN:

Conda:

4.96 score 4 stars 23 scripts 525 downloads 46 exports 98 dependencies

Last updated from:984c24fef8. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK159
source / vignettesOK212
linux-releaseOK157
macos-releaseOK209
macos-oldrelOK195
windows-develOK135
windows-releaseOK107
windows-oldrelOK113
wasm-releaseOK114

Exports:add_missing_fieldsascii_checkascii_cleanercheck_reportcomplete_checkcreate_awareness_reportcreate_reportdat_functiondat_function_selecteddecimal_checkdescription_checkdictionary_searchdimension_checkdup_valuesduplicated_id_checkeval_functionfield_checkid_checkid_first_dataid_first_dictint_checkinteger_checklabel_dataminmax_checkmisc_format_checkmissing_value_checkmissingness_summarymm_precheckmv_precheckNA_checkNA_precheckname_checkname_correctname_precheckpkg_field_checkreorder_datareorder_dictionaryrow_checkshort_field_checkshort_prechecksuper_short_prechecktype_checkvalue_meaning_tablevalue_missing_tablevalues_checkvalues_precheck

Dependencies:base64encbitbit64bslibcachemcellrangerclassclassIntclicliprcommonmarkcpp11crayondigestdplyre1071evaluatefarverfastmapfontawesomeforcatsformatRfsgenericsggplot2gluegridExtragtablehavenhighrhmshtmltoolshttpuvisobandjquerylibjsonliteKernSmoothknitrlabelinglabelledlaterlifecyclemagrittrmemoisemimeminiUInaniarnormotelpanderpillarpkgconfigplyrprettyunitsprogresspromisesproxypurrrquestionrR.cacheR.methodsS3R.ooR.utilsR6rappdirsRColorBrewerRcppreadrreadxlrematchrlangrmarkdownrprojrootrstudioapiS7sassscalesshinysourcetoolsstringistringrstylertibbletidyrtidyselecttinytextzdbUpSetRutf8vctrsviridisviridisLitevisdatvroomwithrxfunxtableyaml

dbGaPCheckup Quick Start
Copyright information | Installation | Quick start | Usage | Example usage | Load the dbGaPCheckup R package | Read in your Subject Phenotype data into DS.data. | Read in your Subject Phenotype data dictionary into DD.dict. | Run the function check_report. | If needed, run the function add_missing_fields and repeat check_report | Reporting | Labelled data | Contact information | Acknowledgments

Last update: 2025-05-01
Started: 2022-10-31

dbGaPCheckup Vignette
Copyright information | Overview | Installation | Data format, file types, and file names | Files | Subject Phenotype Data Set (DS) | Subject Phenotype Data Dictionary (DD) | Execution with example runs and interpretation | Check, utility, and awareness functions | Example 1 | Example 2 | Example 3 | Example 4 | Example 5 | Example 6 | Reporting functions | Label data function | Appendix: Reporting functions | Appendix A: Awareness Report | Missingness Summary | Values Missing Tables | Check A: If the user defines a missing value code that is not present in the data (In Set M and Not in Set D). | Check B: If a VALUES entry defines an encoded code value, but that value is not present in the data (In Set V and Not in Set D). | Check C: If the user defines a missing value code that is not defined in a VALUES entry (In Set M and Not in Set V). | Check D: If a user-defined missing value code is present in the data for a given variable, but that variable does not have a corresponding VALUES entry (M in Set D and Not in Set V). | Check E: If a VALUES entry is NOT defined as a missing value code AND is NOT identified in the data. ((Set V values that are NOT in Set M) that are NOT in Set D). | Appendix B: Data Report | Summary and plots | Contact information | Acknowledgments

Last update: 2025-05-01
Started: 2022-10-31

Readme and manuals

Help Manual

Help pageTopics
Add Missing Fieldsadd_missing_fields
ASCII Character Checkascii_check
ASCII Cleanerascii_cleaner
Check Reportcheck_report
Complete Checkcomplete_check
Create Awareness Reportcreate_awareness_report
Create Reportcreate_report
Data Utility Functiondat_function
Data Selected Utility Functiondat_function_selected
DD.dict.ADD.dict.A
DD.dict.BDD.dict.B
DD.dict.CDD.dict.C
DD.dict.DDD.dict.D
DD.dict.EDD.dict.E
DD.dict.FDD.dict.F
DD.dict.GDD.dict.G
DD.dict.HDD.dict.H
DD.dict.IDD.dict.I
DD.dict.JDD.dict.J
DD.dict.KDD.dict.K
DD.dict.LDD.dict.L
DD.dict.MDD.dict.M
DD.dict.NDD.dict.N
DD.dict.QDD.dict.Q
DD.dict.RDD.dict.R
DD.dict.SDD.dict.S
DD.dict.TDD.dict.T
Decimal Checkdecimal_check
Description Checkdescription_check
Data Dictionary Searchdictionary_search
Dimension Checkdimension_check
DS.data.ADS.data.A
DS.data.BDS.data.B
DS.data.CDS.data.C
DS.data.DDS.data.D
DS.data.EDS.data.E
DS.data.FDS.data.F
DS.data.GDS.data.G
DS.data.HDS.data.H
DS.data.IDS.data.I
DS.data.JDS.data.J
DS.data.KDS.data.K
DS.data.LDS.data.L
DS.data.MDS.data.M
DS.data.NDS.data.N
DS.data.ODS.data.O
DS.data.PDS.data.P
DS.data.QDS.data.Q
DS.data.RDS.data.R
DS.data.SDS.data.S
DS.data.TDS.data.T
Duplicate Values Functiondup_values
Duplicated ID Checkduplicated_id_check
Evaluation Utility Functioneval_function
ExampleAExampleA
ExampleBExampleB
ExampleCExampleC
ExampleDExampleD
ExampleEExampleE
ExampleFExampleF
ExampleGExampleG
ExampleHExampleH
ExampleIExampleI
ExampleJExampleJ
ExampleKExampleK
ExampleLExampleL
ExampleMExampleM
ExampleNExampleN
ExampleOExampleO
ExamplePExampleP
ExampleQExampleQ
ExampleRExampleR
ExampleSExampleS
ExampleTExampleT
Field Checkfield_check
ID Checkid_check
Relocate SUBJECT_ID to First Column of Data Setid_first_data
Relocate SUBJECT_ID to First Column of Data Dictionaryid_first_dict
Integer Check Base Functionint_check
Integer Checkinteger_check
Label the datalabel_data
Minimum and Maximum Values Checkminmax_check
Miscellaneous Format Checkmisc_format_check
Missing Value Checkmissing_value_check
Missingness Summarymissingness_summary
Min Max Required Pre-checksmm_precheck
Missing Values Required Pre-checksmv_precheck
Missing Value (NA) CheckNA_check
Min Max Required Pre-checksNA_precheck
Name Checkname_check
Name Correction Utility Functionname_correct
Name Pre-checksname_precheck
Package Required Field Checkpkg_field_check
Reorder Data Set Utility Functionreorder_data
Reorder Data Dictionary Utility Functionreorder_dictionary
Row Checkrow_check
Truncated Field Checkshort_field_check
Truncated Pre-checkshort_precheck
Very Truncated Pre-checksuper_short_precheck
Type Checktype_check
Value-Meaning Tablevalue_meaning_table
Values Missing Table Awareness Functionvalue_missing_table
Values Checkvalues_check
Values Pre-Checkvalues_precheck