Closed sdgamboa closed 2 years ago
Some samples are annotated with an age that doesn't correspond to their age_category. For example, one sample is labeled as "newborn" and has an age of 19.
Reprex:
suppressMessages({ library(curatedMetagenomicData) library(dplyr) library(ggplot2) }) data <- sampleMetadata %>% filter(!is.na(age), !is.na(age_category)) %>% as_tibble() unique(data$age_category) #> [1] "newborn" "child" "adult" "schoolage" "senior" data$age_category <- factor( data$age_category, levels = c("newborn", "child", "schoolage", "adult", "senior") ) ggplot(data, aes(age_category, age)) + geom_point(position = "jitter", size = 1)
## samples labeled as "newborn" with age above 1 data[data$age_category == "newborn" & data$age > 1,] %>% select(study_name, sample_id, subject_id, age_category, age) #> # A tibble: 1 × 5 #> study_name sample_id subject_id age_category age #> <chr> <chr> <chr> <fct> <int> #> 1 ChuDM_2017 NCS-049-Stool-maternal3_microbiome NCS049_mo newborn 19 ## samples labeled as "child" with age above 11 data[data$age_category == "child" & data$age > 11, ] %>% select(study_name, sample_id, subject_id, age_category, age) #> # A tibble: 1 × 5 #> study_name sample_id subject_id age_category age #> <chr> <chr> <chr> <fct> <int> #> 1 PehrssonE_2016 SID03C_000 SID03C child 19 ## samples labeled as "adult" with age above 65 data[data$age_category == "adult" & data$age >= 66, ] %>% select(study_name, sample_id, subject_id, age_category, age) #> # A tibble: 19 × 5 #> study_name sample_id subject_id age_category age #> <chr> <chr> <chr> <fct> <int> #> 1 HanniganGD_2017 MG100206 HanniganGD_2017_A27 adult 68 #> 2 HanniganGD_2017 MG100205 HanniganGD_2017_A26 adult 80 #> 3 HanniganGD_2017 MG100203 HanniganGD_2017_A24 adult 67 #> 4 HanniganGD_2017 MG100201 HanniganGD_2017_A22 adult 68 #> 5 HanniganGD_2017 MG100193 HanniganGD_2017_A14 adult 72 #> 6 HanniganGD_2017 MG100191 HanniganGD_2017_A12 adult 82 #> 7 HanniganGD_2017 MG100188 HanniganGD_2017_A09 adult 73 #> 8 HanniganGD_2017 MG100187 HanniganGD_2017_A07 adult 71 #> 9 HanniganGD_2017 MG100181 HanniganGD_2017_A01 adult 76 #> 10 HanniganGD_2017 MG100171 HanniganGD_2017_H20 adult 75 #> 11 HanniganGD_2017 MG100158 HanniganGD_2017_H06 adult 75 #> 12 HanniganGD_2017 MG100154 HanniganGD_2017_H02 adult 69 #> 13 HanniganGD_2017 MG100150 HanniganGD_2017_C28 adult 73 #> 14 HanniganGD_2017 MG100142 HanniganGD_2017_C19 adult 71 #> 15 HanniganGD_2017 MG100133 HanniganGD_2017_C10 adult 69 #> 16 HanniganGD_2017 MG100130 HanniganGD_2017_C06 adult 69 #> 17 HanniganGD_2017 MG100128 HanniganGD_2017_C04 adult 88 #> 18 HanniganGD_2017 MG100127 HanniganGD_2017_C03 adult 69 #> 19 HanniganGD_2017 MG100125 HanniganGD_2017_C01 adult 70 ## samples labeled as "senior" with age < 66 data[data$age_category == "senior" & data$age < 66, ] %>% select(study_name, sample_id, subject_id, age_category, age) #> # A tibble: 1 × 5 #> study_name sample_id subject_id age_category age #> <chr> <chr> <chr> <fct> <int> #> 1 LifeLinesDeep_2016 EGAR00001420886_900200… sub_90020000014… senior 19 sessionInfo() #> R version 4.1.1 (2021-08-10) #> Platform: x86_64-pc-linux-gnu (64-bit) #> Running under: Ubuntu 20.04.3 LTS #> #> Matrix products: default #> BLAS: /home/usuario/Apps/R-4.1.1/lib/libRblas.so #> LAPACK: /home/usuario/Apps/R-4.1.1/lib/libRlapack.so #> #> locale: #> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C #> [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 #> [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 #> [7] LC_PAPER=en_US.UTF-8 LC_NAME=C #> [9] LC_ADDRESS=C LC_TELEPHONE=C #> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C #> #> attached base packages: #> [1] stats4 stats graphics grDevices utils datasets methods #> [8] base #> #> other attached packages: #> [1] ggplot2_3.3.5 dplyr_1.0.7 #> [3] curatedMetagenomicData_3.3.3 TreeSummarizedExperiment_2.2.0 #> [5] Biostrings_2.62.0 XVector_0.34.0 #> [7] SingleCellExperiment_1.16.0 SummarizedExperiment_1.24.0 #> [9] Biobase_2.54.0 GenomicRanges_1.46.1 #> [11] GenomeInfoDb_1.30.0 IRanges_2.28.0 #> [13] S4Vectors_0.32.3 BiocGenerics_0.40.0 #> [15] MatrixGenerics_1.6.0 matrixStats_0.61.0 #> #> loaded via a namespace (and not attached): #> [1] backports_1.4.1 AnnotationHub_3.2.0 #> [3] BiocFileCache_2.2.0 plyr_1.8.6 #> [5] lazyeval_0.2.2 splines_4.1.1 #> [7] BiocParallel_1.28.3 scater_1.22.0 #> [9] digest_0.6.29 yulab.utils_0.0.4 #> [11] htmltools_0.5.2 viridis_0.6.2 #> [13] fansi_1.0.0 magrittr_2.0.1 #> [15] memoise_2.0.1 ScaledMatrix_1.2.0 #> [17] cluster_2.1.2 DECIPHER_2.22.0 #> [19] R.utils_2.11.0 colorspace_2.0-2 #> [21] blob_1.2.2 rappdirs_0.3.3 #> [23] ggrepel_0.9.1 xfun_0.29 #> [25] crayon_1.4.2 RCurl_1.98-1.5 #> [27] jsonlite_1.7.2 ape_5.6-1 #> [29] glue_1.6.0 gtable_0.3.0 #> [31] zlibbioc_1.40.0 DelayedArray_0.20.0 #> [33] R.cache_0.15.0 BiocSingular_1.10.0 #> [35] scales_1.1.1 DBI_1.1.2 #> [37] Rcpp_1.0.8 viridisLite_0.4.0 #> [39] xtable_1.8-4 decontam_1.14.0 #> [41] tidytree_0.3.7 bit_4.0.4 #> [43] rsvd_1.0.5 httr_1.4.2 #> [45] ellipsis_0.3.2 pkgconfig_2.0.3 #> [47] R.methodsS3_1.8.1 farver_2.1.0 #> [49] scuttle_1.4.0 dbplyr_2.1.1 #> [51] utf8_1.2.2 tidyselect_1.1.1 #> [53] labeling_0.4.2 rlang_0.4.12 #> [55] reshape2_1.4.4 later_1.3.0 #> [57] AnnotationDbi_1.56.2 munsell_0.5.0 #> [59] BiocVersion_3.14.0 tools_4.1.1 #> [61] cachem_1.0.6 cli_3.1.0 #> [63] DirichletMultinomial_1.36.0 generics_0.1.1 #> [65] RSQLite_2.2.9 ExperimentHub_2.2.0 #> [67] mia_1.2.3 evaluate_0.14 #> [69] stringr_1.4.0 fastmap_1.1.0 #> [71] yaml_2.2.1 knitr_1.37 #> [73] bit64_4.0.5 fs_1.5.2 #> [75] purrr_0.3.4 KEGGREST_1.34.0 #> [77] nlme_3.1-153 sparseMatrixStats_1.6.0 #> [79] mime_0.12 R.oo_1.24.0 #> [81] rstudioapi_0.13 compiler_4.1.1 #> [83] beeswarm_0.4.0 filelock_1.0.2 #> [85] curl_4.3.2 png_0.1-7 #> [87] interactiveDisplayBase_1.32.0 reprex_2.0.1 #> [89] treeio_1.18.1 tibble_3.1.6 #> [91] stringi_1.7.6 highr_0.9 #> [93] lattice_0.20-45 Matrix_1.4-0 #> [95] styler_1.6.2 vegan_2.5-7 #> [97] permute_0.9-5 vctrs_0.3.8 #> [99] pillar_1.6.4 lifecycle_1.0.1 #> [101] BiocManager_1.30.16 BiocNeighbors_1.12.0 #> [103] bitops_1.0-7 irlba_2.3.5 #> [105] httpuv_1.6.5 R6_2.5.1 #> [107] promises_1.2.0.1 gridExtra_2.3 #> [109] vipor_0.4.5 MASS_7.3-54 #> [111] assertthat_0.2.1 withr_2.4.3 #> [113] GenomeInfoDbData_1.2.7 mgcv_1.8-38 #> [115] parallel_4.1.1 MultiAssayExperiment_1.20.0 #> [117] grid_4.1.1 beachmat_2.10.0 #> [119] tidyr_1.1.4 rmarkdown_2.11 #> [121] DelayedMatrixStats_1.16.0 shiny_1.7.1 #> [123] ggbeeswarm_0.6.0
Created on 2022-01-14 by the reprex package (v2.0.1)
Pinging @paolinomanghi - would be great to fix this before the Bioconductor 3.15 release.
Some samples are annotated with an age that doesn't correspond to their age_category. For example, one sample is labeled as "newborn" and has an age of 19.
Reprex:
Created on 2022-01-14 by the reprex package (v2.0.1)