software-review icon indicating copy to clipboard operation
software-review copied to clipboard

Published 20 hours ago • verified publisher icon ropensci

gigs: Assess Fetal, Newborn, and Child Growth with International Standards

Open simpar1471 opened this issue 1 year ago • 41 comments

Submitting Author Name: Simon Parker Submitting Author Github Handle: @simpar1471 Repository: https://github.com/lshtm-gigs/gigs/ Version submitted: 0.4.1 Submission type: Stats Badge grade: silver Editor: @rkillick Reviewers: @chitrams, @brovic

Due date for @chitrams: 2024-09-20

Due date for @brovic: 2024-09-24 Archive: TBD Version accepted: TBD Language: en

  • Paste the full DESCRIPTION file inside a code block below:
Type: Package
Package: gigs
Title: Assess Fetal, Newborn, and Child Growth with International Standards
Version: 0.4.1
Authors@R: c(
    person(given = "Simon", family = "Parker",
           email = "[email protected]",
           role = c("aut", "cre"), comment = c(ORCID = "0009-0003-8214-4496")),
    person(given = "Linda", family = "Vesel", role = c("dtc"),
           comment = c(ORCID = "0000-0003-3753-4172")),
    person(given = "Eric", family = "Ohuma", role = c("dtc"),
           comment = c(ORCID = "0000-0002-3116-2593")),
    person(given = "Bill & Melinda Gates Foundation", role = c("fnd", "cph"))
    )
Description: Convert between anthropometric measures and z-scores/centiles in
    multiple growth standards, and classify fetal, newborn, and child growth
    accordingly. With a simple interface to growth standards from the World
    Health Organisation and International Fetal and Newborn Growth Consortium
    for the 21st Century, gigs makes growth assessment easy and reproducible for
    clinicians, researchers and policy-makers.
License: GPL (>= 3)
URL: https://github.com/lshtm-gigs/gigs/,
    https://lshtm-gigs.github.io/gigs/
BugReports: https://github.com/lshtm-gigs/gigs/issues
Depends: 
    R (>= 4.1.0)
Imports:
    stats,
    gamlss.dist,
    checkmate,
    vctrs
Suggests:
    knitr,
    rmarkdown,
    testthat (>= 3.0.0),
    units,
    withr
VignetteBuilder: knitr
Config/testthat/edition: 3
Config/testthat/parallel: true
Config/testthat/start-first: who_gs, ig_nbs, ig_fet, ig_png
Encoding: UTF-8
Language: en-GB
LazyData: true
RoxygenNote: 7.3.0
Roxygen: list(markdown = TRUE, roclets = c ("namespace", "rd", "srr::srr_stats_roclet"))

Scope

  • Please indicate which of our statistical package categories this package falls under. (Please check one appropriate box below):

    Statistical Packages

    • [ ] Bayesian and Monte Carlo Routines
    • [ ] Dimensionality Reduction, Clustering, and Unsupervised Learning
    • [ ] Machine Learning
    • [ ] Regression and Supervised Learning
    • [X] Exploratory Data Analysis (EDA) and Summary Statistics
    • [ ] Spatial Analyses
    • [ ] Time Series Analyses

Pre-submission Inquiry

  • [X] A pre-submission inquiry has been approved in issue#616

General Information

  • Who is the target audience and what are scientific applications of this package?

The target audience for this package is researchers, clinicians, and policy-makers interested in nutrition and fetal/newborn/child health. The package itself is used to convert measurements, for example a baby's weight at a given age, into summary statistics such as z-scores (i.e. number of standard deviations away from mean) and percentiles (i.e. number of percentage points above/below the median, expressed as a decimal). It can also be used to classify these z-scores and percentiles into specific categories for specific facets of growth. Scientific applications of this package would therefore include using our functions to generate statistical measures of growth in individuals or populations across time or pre/post a healthcare intervention. These could then be used in further downstream analyses.

Several R packages which implement child growth charts already exist, but they differ in the range of growth charts offered, their flexibility in conversion, and in what data they make available to users.

  1. anthro converts measurements into z-scores in the WHO Child Growth Standards, but lacks any INTERGROWTH-21st standards and outputs tabular data. We provide an interface which takes vectors in and gives vectors out, so is more flexible (e.g. with dplyr pipelines). This package is available on CRAN.
  2. childsds can convert measurements to z-scores or percentiles, but cannot convert z-scores/percentiles to expected measurements. Additionally, childsds does not contain the newborn/postnatal INTERGROWTH-21st growth standards, which we implement. Though childsds does include more growth references, growth references are not within the scope of the GIGS project. We can discuss the reasons for this if necessary. This package is available on CRAN.
  3. growthstandards contains functions for converting between values and z-scores/percentiles, as in gigs. It includes the INTERGROWTH-21st fetal standards, but not the newborn or postnatal standards we implement. This package makes coefficients available to end-users, but not reference growth curves. This package is not available on CRAN. It was last updated in January 2024.
  4. intergrowth provides more fetal growth standards than gigs, but cannot convert between z-scores/percentiles in the lacks the INTERGROWTH-21st newborn or postnatal growth standards, which we have implemented in gigs. This package also does not make coefficients for the growth standards available to end-users, though it it does provide growth curve data to end-users. This package is not available on CRAN, and was last updated in January 2023.
  5. gigs provides a simple interface for working with the growth standards it implements, which can be easily included in dplyr-like data wrangling pipelines. It implements all available WHO 2006/2007 and INTERGROWTH-21st growth standards, and makes published growth curves and model coefficients are available wherever possible. In our own testing, we found that it also warns end users about bad input data more comprehensively.

The Other packages section of the repository README also contains links to each of these packages, and a table describing features present in gigs compared to other growth standards packages.

We have a benchmarking vignette which shows the scaling of these packages when analysing datasets containing 1 to 100,000 cases. In summary: anthro scales the worst (29 ms to 2.24 seconds). The other packages are then clustered together: growthstandards is the fastest for 100,000 cases (4.62 ms to 125 ms); childsds is next (2.40 ms to 126 ms); then gigs (1.32 ms to 128 ms).

Not applicable.

Badging

Silver

  • Demonstrating excellence in compliance with multiple standards from at least two broad sub-categories. I feel this package has a comprehensive test suite and good error/warning behaviours in response to undesired input.

Technical checks

Confirm each of the following by checking the box.

This package:

Publication options

  • [X] Do you intend for this package to go on CRAN?
  • [ ] Do you intend for this package to go on Bioconductor?

Code of conduct

  • [X] I agree to abide by rOpenSci's Code of Conduct during the review process and in maintaining my package should it be accepted.

simpar1471 avatar Feb 07 '24 13:02 simpar1471

Thanks for submitting to rOpenSci, our editors and @ropensci-review-bot will reply soon. Type @ropensci-review-bot help for help.

ropensci-review-bot avatar Feb 07 '24 13:02 ropensci-review-bot

:rocket:

Editor check started

:wave:

ropensci-review-bot avatar Feb 07 '24 13:02 ropensci-review-bot

Checks for gigs (v0.4.1)

git hash: a9d9654a

  • :heavy_check_mark: Package name is available
  • :heavy_check_mark: has a 'codemeta.json' file.
  • :heavy_check_mark: has a 'contributing' file.
  • :heavy_check_mark: uses 'roxygen2'.
  • :heavy_check_mark: 'DESCRIPTION' has a URL field.
  • :heavy_check_mark: 'DESCRIPTION' has a BugReports field.
  • :heavy_check_mark: Package has at least one HTML vignette
  • :heavy_check_mark: All functions have examples.
  • :heavy_check_mark: Package has continuous integration checks.
  • :heavy_check_mark: Package coverage is 100%.
  • :heavy_check_mark: R CMD check found no errors.
  • :heavy_check_mark: R CMD check found no warnings.

Package License: GPL (>= 3)

1. rOpenSci Statistical Standards (srr package)

This package is in the following category:

  • Exploratory Data Analysis

:heavy_check_mark: All applicable standards [v0.2.0] have been documented in this package (632 complied with; 0 N/A standards)

Click to see the report of author-reported standards compliance of the package with links to associated lines of code, which can be re-generated locally by running the srr_report() function from within a local clone of the repository.

2. Package Dependencies

Details of Package Dependency Usage (click to open)

The table below tallies all function calls to all packages ('ncalls'), both internal (r-base + recommended, along with the package itself), and external (imported and suggested packages). 'NA' values indicate packages to which no identified calls to R functions could be found. Note that these results are generated by an automated code-tagging system which may not be entirely accurate.

type package ncalls
internal gigs 401
internal base 271
imports stats 36
imports checkmate 13
imports gamlss.dist 1
imports vctrs 1
suggests knitr NA
suggests rmarkdown NA
suggests testthat NA
suggests units NA
suggests withr NA
linking_to NA NA

Click below for tallies of functions used in each package. Locations of each call within this package may be generated locally by running 's <- pkgstats::pkgstats(<path/to/repo>)', and examining the 'external_calls' table.

gigs

validate_ig_fet (22), validate_ig_nbs (17), fn_on_subset (13), validate_who_gs (11), who_gs_lms2value (9), validate_ig_png (6), gigs_xaz_lgls (5), validate_yzp (5), ig_fet_doppler_gms (3), ig_fet_efw_lms (3), ig_fet_gwg_mu_sigma (3), ig_fet_mu_sigma (3), ig_nbs_bodycomp_mu_sigma (3), ig_nbs_msnt (3), ig_nbs_wlr_mu_sigma (3), ig_png_equations (3), ig_vpns_equations (3), mu_sigma_z2y (3), validate_parameter_lengths (3), who_gs_lms (3), classify_sfga (2), gigs_laz (2), gigs_option_get (2), gigs_waz (2), gigs_wlz (2), ig_nbs_hcfga_value2zscore (2), ig_nbs_lfga_value2zscore (2), ig_nbs_wfga_value2centile (2), ig_nbs_wfga_value2zscore (2), ig_png_hcfa_value2zscore (2), ig_png_lfa_value2zscore (2), ig_png_wfa_value2zscore (2), ig_png_wfl_value2zscore (2), inrange (2), validate_hcaz_params (2), validate_laz_params (2), validate_waz_params (2), validate_wlz_params (2), who_gs_hcfa_value2zscore (2), who_gs_lhfa_value2zscore (2), who_gs_wfa_value2zscore (2), classify_stunting (1), classify_svn (1), classify_wasting (1), classify_wfa (1), drop_null_elements (1), exponent (1), gigs_hcaz (1), gigs_option_set (1), handle_invalid_chr_options (1), handle_missing_data (1), handle_oob_centiles (1), handle_oob_xvar (1), handle_undefined_data (1), handle_var (1), hcfa_mu (1), hcfa_sigma (1), hcfga_mu (1), ig_fet_acfga_centile2value (1), ig_fet_acfga_value2centile (1), ig_fet_acfga_value2zscore (1), ig_fet_acfga_zscore2value (1), ig_fet_avfga_centile2value (1), ig_fet_avfga_value2centile (1), ig_fet_avfga_value2zscore (1), ig_fet_avfga_zscore2value (1), ig_fet_bpdfga_centile2value (1), ig_fet_bpdfga_value2centile (1), ig_fet_bpdfga_value2zscore (1), ig_fet_bpdfga_zscore2value (1), ig_fet_centile2value (1), ig_fet_cmfga_centile2value (1), ig_fet_cmfga_value2centile (1), ig_fet_cmfga_value2zscore (1), ig_fet_cmfga_zscore2value (1), ig_fet_crlfga_centile2value (1), ig_fet_crlfga_value2centile (1), ig_fet_crlfga_value2zscore (1), ig_fet_crlfga_zscore2value (1), ig_fet_doppler_y2z (1), ig_fet_doppler_z2y (1), ig_fet_efw_y2z (1), ig_fet_efw_z2y (1), ig_fet_efwfga_centile2value (1), ig_fet_efwfga_value2centile (1), ig_fet_efwfga_value2zscore (1), ig_fet_efwfga_zscore2value (1), ig_fet_estimate_fetal_weight (1), ig_fet_estimate_ga (1), ig_fet_estimate_ga_crl (1), ig_fet_estimate_ga_hc (1), ig_fet_estimate_ga_hcfl (1), ig_fet_flfga_centile2value (1), ig_fet_flfga_value2centile (1), ig_fet_flfga_value2zscore (1), ig_fet_flfga_zscore2value (1), ig_fet_gafcrl_centile2value (1), ig_fet_gafcrl_value2centile (1), ig_fet_gafcrl_value2zscore (1), ig_fet_gafcrl_zscore2value (1), ig_fet_gaftcd_centile2value (1), ig_fet_gaftcd_value2centile (1), ig_fet_gaftcd_value2zscore (1), ig_fet_gaftcd_zscore2value (1), ig_fet_gwg_y2z (1), ig_fet_gwg_z2y (1), ig_fet_gwgfga_centile2value (1), ig_fet_gwgfga_value2centile (1), ig_fet_gwgfga_value2zscore (1), ig_fet_gwgfga_zscore2value (1), ig_fet_hcfga_centile2value (1), ig_fet_hcfga_value2centile (1), ig_fet_hcfga_value2zscore (1), ig_fet_hcfga_zscore2value (1), ig_fet_mu_sigma_y2z (1), ig_fet_mu_sigma_z2y (1), ig_fet_ofdfga_centile2value (1), ig_fet_ofdfga_value2centile (1), ig_fet_ofdfga_value2zscore (1), ig_fet_ofdfga_zscore2value (1), ig_fet_pifga_centile2value (1), ig_fet_pifga_value2centile (1), ig_fet_pifga_value2zscore (1), ig_fet_pifga_zscore2value (1), ig_fet_poffga_centile2value (1), ig_fet_poffga_value2centile (1), ig_fet_poffga_value2zscore (1), ig_fet_poffga_zscore2value (1), ig_fet_pvfga_centile2value (1), ig_fet_pvfga_value2centile (1), ig_fet_pvfga_value2zscore (1), ig_fet_pvfga_zscore2value (1), ig_fet_rifga_centile2value (1), ig_fet_rifga_value2centile (1), ig_fet_rifga_value2zscore (1), ig_fet_rifga_zscore2value (1), ig_fet_sdrfga_centile2value (1), ig_fet_sdrfga_value2centile (1), ig_fet_sdrfga_value2zscore (1), ig_fet_sdrfga_zscore2value (1), ig_fet_sffga_centile2value (1), ig_fet_sffga_value2centile (1), ig_fet_sffga_value2zscore (1), ig_fet_sffga_zscore2value (1), ig_fet_sfhfga_centile2value (1), ig_fet_sfhfga_value2centile (1), ig_fet_sfhfga_value2zscore (1), ig_fet_sfhfga_zscore2value (1), ig_fet_tcdfga_centile2value (1), ig_fet_tcdfga_value2centile (1), ig_fet_tcdfga_value2zscore (1), ig_fet_tcdfga_zscore2value (1), ig_fet_v2z_internal (1), ig_fet_value2centile (1), ig_fet_value2zscore (1), ig_fet_z2v_internal (1), ig_fet_zscore2value (1), ig_nbs_bfpfga_centile2value (1), ig_nbs_bfpfga_value2centile (1), ig_nbs_bfpfga_value2zscore (1), ig_nbs_bfpfga_zscore2value (1), ig_nbs_bodycomp_p2v (1), ig_nbs_bodycomp_v2p (1), ig_nbs_c2v_internal (1), ig_nbs_centile2value (1), ig_nbs_ffmfga_centile2value (1), ig_nbs_ffmfga_value2centile (1), ig_nbs_ffmfga_value2zscore (1), ig_nbs_ffmfga_zscore2value (1), ig_nbs_fmfga_centile2value (1), ig_nbs_fmfga_value2centile (1), ig_nbs_fmfga_value2zscore (1), ig_nbs_fmfga_zscore2value (1), ig_nbs_hcfga_centile2value (1), ig_nbs_hcfga_value2centile (1), ig_nbs_hcfga_zscore2value (1), ig_nbs_lfga_centile2value (1), ig_nbs_lfga_value2centile (1), ig_nbs_lfga_zscore2value (1), ig_nbs_msnt_p2v (1), ig_nbs_msnt_v2p (1), ig_nbs_v2c_internal (1), ig_nbs_value2centile (1), ig_nbs_value2zscore (1), ig_nbs_wfga_centile2value (1), ig_nbs_wfga_zscore2value (1), ig_nbs_wlrfga_centile2value (1), ig_nbs_wlrfga_p2v (1), ig_nbs_wlrfga_v2p (1), ig_nbs_wlrfga_value2centile (1), ig_nbs_wlrfga_value2zscore (1), ig_nbs_wlrfga_zscore2value (1), ig_nbs_zscore2value (1), ig_png_centile2value (1), ig_png_hcfa_centile2value (1), ig_png_hcfa_value2centile (1), ig_png_hcfa_zscore2value (1), ig_png_lfa_centile2value (1), ig_png_lfa_value2centile (1), ig_png_lfa_zscore2value (1), ig_png_v2z_internal (1), ig_png_value2centile (1), ig_png_value2zscore (1), ig_png_wfa_centile2value (1), ig_png_wfa_value2centile (1), ig_png_wfa_zscore2value (1), ig_png_wfl_centile2value (1), ig_png_wfl_value2centile (1), ig_png_wfl_zscore2value (1), ig_png_z2v_internal (1), ig_png_zscore2value (1), ig_vpns_value2zscore (1), ig_vpns_zscore2value (1), lfa_log_mu (1), lfa_sigma (1), lfga_mu (1), msg_invalid_sex_acronym (1), msg_missing_data (1), msg_oob_centiles (1), msg_oob_xvar (1), msg_undefined_data (1), mu_sigma_y2z (1), remove_attributes (1), retrieve_coefficients (1), validate_acronym (1), validate_chr (1), validate_ig_fet_estimation_param (1), validate_ig_fet_weight_estimation_param (1), validate_numeric (1), validate_sex (1), validate_xvar (1), wfa_log_mu (1), wfa_sigma (1), wfga_logmu (1), wfl_mu (1), wfl_sigma (1), who_gs_acfa_centile2value (1), who_gs_acfa_value2centile (1), who_gs_acfa_value2zscore (1), who_gs_acfa_zscore2value (1), who_gs_bfa_centile2value (1), who_gs_bfa_value2centile (1), who_gs_bfa_value2zscore (1), who_gs_bfa_zscore2value (1), who_gs_centile2value (1), who_gs_hcfa_centile2value (1), who_gs_hcfa_value2centile (1), who_gs_hcfa_zscore2value (1), who_gs_lhfa_centile2value (1), who_gs_lhfa_value2centile (1), who_gs_lhfa_zscore2value (1), who_gs_lms_v2z (1), who_gs_lms_v2z_constrained (1), who_gs_lms_v2z_over_three (1), who_gs_lms_v2z_under_minus_three (1), who_gs_lms_z2v (1), who_gs_lms_z2v_over_three (1), who_gs_lms_z2v_under_minus_three (1), who_gs_ssfa_centile2value (1), who_gs_ssfa_value2centile (1), who_gs_ssfa_value2zscore (1), who_gs_ssfa_zscore2value (1), who_gs_tsfa_centile2value (1), who_gs_tsfa_value2centile (1), who_gs_tsfa_value2zscore (1), who_gs_tsfa_zscore2value (1), who_gs_v2z_internal (1), who_gs_value2centile (1), who_gs_value2zscore (1), who_gs_wfa_centile2value (1), who_gs_wfa_value2centile (1), who_gs_wfa_zscore2value (1), who_gs_wfh_centile2value (1), who_gs_wfh_value2centile (1), who_gs_wfh_value2zscore (1), who_gs_wfl_value2zscore (1)

base

list (63), length (32), is.null (18), c (15), rep (12), log (9), is.na (8), names (8), for (7), ifelse (6), gamma (5), lengths (5), sqrt (5), data.frame (4), logical (4), matrix (4), paste0 (4), unique (4), abs (3), character (3), get (3), if (3), lapply (3), ncol (3), nrow (3), numeric (3), vapply (3), as.data.frame (2), levels (2), options (2), parent.frame (2), rep_len (2), sum (2), with (2), deparse (1), emptyenv (1), exp (1), inherits (1), max (1), mode (1), new.env (1), paste (1), q (1), range (1), rep.int (1), replace (1), seq_along (1), sign (1), substitute (1), unlist (1), vector (1)

stats

sigma (28), complete.cases (4), var (2), approx (1), qnorm (1)

checkmate

qassert (8), assert_numeric (2), assert_subset (2), assert_character (1)

gamlss.dist

pST3C (1)

vctrs

vec_recycle_common (1)

3. Statistical Properties

This package features some noteworthy statistical properties which may need to be clarified by a handling editor prior to progressing.

Details of statistical properties (click to open)

The package has:

  • code in R (100% in 15 files) and
  • 1 authors
  • 3 vignettes
  • 7 internal data files
  • 4 imported packages
  • 185 exported functions (median 6 lines of code)
  • 376 non-exported functions in R (median 8 lines of code)

Statistical properties of package structure as distributional percentiles in relation to all current CRAN packages The following terminology is used:

  • loc = "Lines of Code"
  • fn = "function"
  • exp/not_exp = exported / not exported

All parameters are explained as tooltips in the locally-rendered HTML version of this report generated by the checks_to_markdown() function

The final measure (fn_call_network_size) is the total number of calls between functions (in R), or more abstract relationships between code objects in other languages. Values are flagged as "noteworthy" when they lie in the upper or lower 5th percentile.

measure value percentile noteworthy
files_R 15 73.0
files_vignettes 3 92.4
files_tests 10 90.7
loc_R 2689 89.0
loc_vignettes 877 89.0
loc_tests 4157 97.6 TRUE
num_vignettes 3 94.2
data_size_total 1093128 95.5 TRUE
data_size_median 11317 79.8
n_fns_r 561 98.0 TRUE
n_fns_r_exported 185 98.3 TRUE
n_fns_r_not_exported 376 97.5 TRUE
n_fns_per_file_r 21 95.9 TRUE
num_params_per_fn 3 33.6
loc_per_fn_r 6 12.1
loc_per_fn_r_exp 6 10.5
loc_per_fn_r_not_exp 8 22.6
rel_whitespace_R 13 82.6
rel_whitespace_vignettes 13 67.8
rel_whitespace_tests 12 94.8
doclines_per_fn_exp 163 97.4 TRUE
doclines_per_fn_not_exp 0 0.0 TRUE
fn_call_network_size 408 94.2

3a. Network visualisation

Click to see the interactive network visualisation of calls between objects in package

4. goodpractice and other checks

Details of goodpractice checks (click to open)

3a. Continuous Integration Badges

R-CMD-check.yaml pkgcheck test-coverage.yaml

GitHub Workflow Results

id name conclusion sha run_number date
7815041175 pages build and deployment success ea59a9 20 2024-02-07
7815003364 pkgcheck success a9d965 5 2024-02-07
7815003368 pkgdown success a9d965 45 2024-02-07
7814822521 R-CMD-check success a9d965 51 2024-02-07
7814822525 test-coverage success a9d965 51 2024-02-07
7815003373 Update CITATION.cff success a9d965 2 2024-02-07

3b. goodpractice results

R CMD check with rcmdcheck

rcmdcheck found no errors, warnings, or notes

Test coverage with covr

Package coverage: 100

Cyclocomplexity with cyclocomp

No functions have cyclocomplexity >= 15

Static code analyses with lintr

lintr found the following 69 potential issues:

message number of times
Avoid library() and require() calls in packages 2
Lines should not be more than 80 characters. 67
Package Versions

package version
pkgstats 0.1.3.9
pkgcheck 0.1.2.14
srr 0.0.1.194

Editor-in-Chief Instructions:

This package is in top shape and may be passed on to a handling editor

ropensci-review-bot avatar Feb 07 '24 13:02 ropensci-review-bot

@ropensci-review-bot check srr

ldecicco-USGS avatar Feb 22 '24 20:02 ldecicco-USGS

'srr' standards compliance:

  • Complied with: 53 / 102 = 52% (eda: 8 / 34; general: 45 / 68)
  • Not complied with: 49 / 102 = 48% (eda: 26 / 34; general: 23 / 68)

:heavy_check_mark: This package complies with > 50% of all standads and may be submitted.

ropensci-review-bot avatar Feb 22 '24 20:02 ropensci-review-bot

@ropensci-review-bot assign @rkillick as editor

rkillick avatar Feb 23 '24 18:02 rkillick

Assigned! @rkillick is now the editor

ropensci-review-bot avatar Feb 23 '24 18:02 ropensci-review-bot

Hi @rkillick, have you had any chance to look at this? Not meaning to be pushy if you're rained in with other things at the moment!

simpar1471 avatar Mar 19 '24 16:03 simpar1471