CRAN Package Check Results for Package getspres

Last updated on 2020-03-31 19:49:43 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.1.0 9.87 34.40 44.27 OK
r-devel-linux-x86_64-debian-gcc 0.1.0 6.90 26.90 33.80 OK
r-devel-linux-x86_64-fedora-clang 0.1.1 46.72 OK
r-devel-linux-x86_64-fedora-gcc 0.1.0 44.32 OK
r-devel-windows-ix86+x86_64 0.1.0 11.00 50.00 61.00 OK
r-devel-windows-ix86+x86_64-gcc8 0.1.0 9.00 49.00 58.00 OK
r-patched-linux-x86_64 0.1.0 9.06 33.65 42.71 OK
r-patched-solaris-x86 0.1.0 80.20 OK
r-release-linux-x86_64 0.1.0 7.12 30.84 37.96 OK
r-release-windows-ix86+x86_64 0.1.0 12.00 63.00 75.00 OK
r-release-osx-x86_64 0.1.0 OK
r-oldrel-windows-ix86+x86_64 0.1.1 5.00 66.00 71.00 ERROR
r-oldrel-osx-x86_64 0.1.0 OK

Additional issues

donttest

Check Details

Version: 0.1.1
Check: examples
Result: ERROR
    Running examples in 'getspres-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: plotspres
    > ### Title: 'plotspres' generates forest plots showing _SPRE_ statistics.
    > ### Aliases: plotspres plotspre forestspre spreforest plotspres.default
    >
    > ### ** Examples
    >
    > library(getspres)
    >
    >
    > # Generate a forest plot showing SPRE statistics for variants in heartgenes214.
    > # heartgenes214 is a case-control GWAS meta-analysis of coronary artery disease.
    > # To learn more about the heartgenes214 dataset ?heartgenes214
    >
    > # Calculating SPRE statistics for 3 variants in heartgenes214
    >
    > heartgenes3 <- subset(heartgenes214,
    + variants %in% c("rs10139550", "rs10168194", "rs11191416"))
    >
    > getspres_results <- getspres(beta_in = heartgenes3$beta_flipped,
    + se_in = heartgenes3$gcse,
    + study_names_in = heartgenes3$studies,
    + variant_names_in = heartgenes3$variants)
    >
    > # Explore results generated by the getspres function
    > str(getspres_results)
    List of 4
     $ number_variants: int 3
     $ number_studies : int 48
     $ spre_dataset :'data.frame': 143 obs. of 17 variables:
     ..$ beta : num [1:143] -0.2056 0.1058 0.0841 0.18 0.3271 ...
     ..$ se : num [1:143] 0.144 0.0778 0.0752 0.1286 0.1105 ...
     ..$ variant_names: Factor w/ 3 levels "rs10139550","rs10168194",..: 1 1 1 1 1 1 1 1 1 1 ...
     ..$ study_names : Factor w/ 48 levels "01","02","03",..: 1 2 3 4 5 6 7 8 9 10 ...
     ..$ study : Factor w/ 48 levels "1","2","3","4",..: 1 2 3 4 5 6 7 8 9 10 ...
     ..$ snp : Factor w/ 3 levels "1","2","3": 1 1 1 1 1 1 1 1 1 1 ...
     ..$ tau2 : num [1:143] 0.00211 0.00211 0.00211 0.00211 0.00211 ...
     ..$ I2 : num [1:143] 34.9 34.9 34.9 34.9 34.9 ...
     ..$ Q : num [1:143] 72.2 72.2 72.2 72.2 72.2 ...
     ..$ xb : num [1:143] 0.0631 0.0631 0.0631 0.0631 0.0631 ...
     ..$ xbse : num [1:143] 0.0121 0.0121 0.0121 0.0121 0.0121 ...
     ..$ xbu : num [1:143] 0.0383 0.0741 0.0688 0.0763 0.102 ...
     ..$ stdxbu : num [1:143] 0.0451 0.0406 0.0402 0.0446 0.0437 ...
     ..$ hat : num [1:143] 0.00626 0.01752 0.01842 0.00768 0.00999 ...
     ..$ rawresid : num [1:143] -0.2687 0.0427 0.021 0.1169 0.264 ...
     ..$ uncondse : num [1:143] 0.1507 0.0896 0.0873 0.136 0.1191 ...
     ..$ spre : num [1:143] -1.784 0.477 0.241 0.86 2.217 ...
     $ call : language getspres.default(beta_in = heartgenes3$beta_flipped, se_in = heartgenes3$gcse, study_names_in = heartgenes3$| __truncated__
     - attr(*, "class")= chr "getspres"
    >
    > # Retrieve number of studies and variants
    > getspres_results$number_variants
    [1] 3
    > getspres_results$number_studies
    [1] 48
    >
    > # Retrieve SPRE dataset
    > df_spres <- getspres_results$spre_dataset
    > head(df_spres)
     beta se variant_names study_names study
    rs10139550.rs10139550.01 -0.205650 0.14399623 rs10139550 01 1
    rs10139550.rs10139550.02 0.105799 0.07784344 rs10139550 02 2
    rs10139550.rs10139550.03 0.084100 0.07523906 rs10139550 03 3
    rs10139550.rs10139550.04 0.180000 0.12857537 rs10139550 04 4
    rs10139550.rs10139550.05 0.327100 0.11052377 rs10139550 05 5
    rs10139550.rs10139550.06 0.152000 0.06835058 rs10139550 06 6
     snp tau2 I2 Q xb xbse
    rs10139550.rs10139550.01 1 0.002109174 34.87837 72.17264 0.06309822 0.012147
    rs10139550.rs10139550.02 1 0.002109174 34.87837 72.17264 0.06309822 0.012147
    rs10139550.rs10139550.03 1 0.002109174 34.87837 72.17264 0.06309822 0.012147
    rs10139550.rs10139550.04 1 0.002109174 34.87837 72.17264 0.06309822 0.012147
    rs10139550.rs10139550.05 1 0.002109174 34.87837 72.17264 0.06309822 0.012147
    rs10139550.rs10139550.06 1 0.002109174 34.87837 72.17264 0.06309822 0.012147
     xbu stdxbu hat rawresid
    rs10139550.rs10139550.01 0.03828494 0.04512203 0.006264557 -0.26874822
    rs10139550.rs10139550.02 0.07412354 0.04056819 0.017518916 0.04270078
    rs10139550.rs10139550.03 0.06879911 0.04018658 0.018417818 0.02100178
    rs10139550.rs10139550.04 0.07632546 0.04457099 0.007677144 0.11690178
    rs10139550.rs10139550.05 0.10197000 0.04365680 0.009990319 0.26400178
    rs10139550.rs10139550.06 0.09075049 0.03902777 0.021104352 0.08890178
     uncondse spre
    rs10139550.rs10139550.01 0.15065370 -1.7838806
    rs10139550.rs10139550.02 0.08956130 0.4767771
    rs10139550.rs10139550.03 0.08730716 0.2405504
    rs10139550.rs10139550.04 0.13598989 0.8596358
    rs10139550.rs10139550.05 0.11906775 2.2172400
    rs10139550.rs10139550.06 0.08144585 1.0915446
    >
    > # Extract SPREs from SPRE dataset
    > head(spres <- df_spres[, "spre"])
    [1] -1.7838806 0.4767771 0.2405504 0.8596358 2.2172400 1.0915446
    >
    >
    > # Generating forest plots showing SPREs for variants in heartgenes3
    >
    > # Forest plot with default settings
    > # Tip: To store plots set save_plot = TRUE (useful when generating multiple plots)
    > plotspres_res <- plotspres(beta_in = df_spres$beta,
    + se_in = df_spres$se,
    + study_names_in = as.character(df_spres$study_names),
    + variant_names_in = as.character(df_spres$variant_names),
    + spres_in = df_spres$spre,
    + save_plot = FALSE)
    Error in update_tibble_attrs(x, ...) :
     object 'tibble_update_attrs' not found
    Calls: plotspres ... recycle_columns -> new_tibble -> update_tibble_attrs
    Execution halted
Flavor: r-oldrel-windows-ix86+x86_64