addDivergence from OMA vignette

[shwetha141]

under the community typing section, I saw that you had a code snippet that I could not replicate.

tse <- addDivergence( tse, assay.type = "counts", reference = "median", FUN = vegan::vegdist)

I was not able to find addDivergence function. Any thoughts?

[Daenarys8]

Hi, did you load mia package? library(mia)

[Daenarys8]

Is it okay now?

[shwetha141]

Hi , I apologize for not giving the details. I ran the tutorial or examples from OMA book. Most of the functions were unrecognized ( i had installed mia last year) I forced install from github (regular install -says there are no changes in the code). After the forced install of mia, the examples from the tutorial run ok but when I run against my data , I get errors (addRDA). I looked at the repo and i didn't see these functions so I was puzzled.

[Daenarys8]

Hi, no worries. Can you run sessioninfo::package_info() and tell me the version of mia you have?

[antagomir]

mia is still in development and the latest changes occur in the official BIoconductor release with a delay of some months, the remotes::install_github("microbiome/mia") will install the latest development version (which is in sync with OMA).

[shwetha141]

Hi, no worries. Can you run sessioninfo::package_info() and tell me the version of mia you have?

sessionInfo() R version 4.3.2 (2023-10-31) Platform: aarch64-apple-darwin20 (64-bit) Running under: macOS Sonoma 14.5

Matrix products: default BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0

locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: America/Chicago tzcode source: internal

attached base packages: [1] parallel grid stats4 stats graphics grDevices utils datasets [9] methods base

other attached packages: [1] GWalkR_0.1.4 miaViz_1.13.9
[3] ggraph_2.2.1 scater_1.30.1
[5] scuttle_1.12.0 mia_1.13.36
[7] MultiAssayExperiment_1.28.0 TreeSummarizedExperiment_2.10.0 [9] Biostrings_2.70.3 XVector_0.42.0
[11] SingleCellExperiment_1.24.0 vcdExtra_0.8-5
[13] gnm_1.1-5 vcd_1.4-12
[15] jmv_2.5.6 charter_0.0.1.9000
[17] shiny_1.9.1 showtext_0.9-7
[19] showtextdb_3.0 sysfonts_0.8.9
[21] echarts4r_0.4.5 highcharter_0.9.4
[23] patchwork_1.2.0 ggthemes_5.1.0
[25] scico_1.5.0 rcartocolor_2.1.1
[27] ggtext_0.1.2 ggridges_0.5.6
[29] ggrepel_0.9.5 cowplot_1.1.3
[31] corrr_0.4.4 prismatic_1.1.2
[33] flextable_0.9.6 scales_1.3.0
[35] janitor_2.2.0 gtsummary_2.0.0
[37] skimr_2.1.5 here_1.0.1
[39] rio_1.2.1 readxl_1.4.3
[41] data.table_1.15.4 RColorBrewer_1.1-3
[43] heatmaply_1.5.0 Hmisc_5.1-3
[45] DT_0.33 knitr_1.48
[47] tsne_0.1-3.1 GGally_2.2.1
[49] reshape2_1.4.4 robustHD_0.8.1
[51] robustbase_0.99-3 perry_0.3.1
[53] corrplot_0.92 gplots_3.1.3.1
[55] rstatix_0.7.2 ComplexHeatmap_2.18.0
[57] DESeq2_1.42.1 SummarizedExperiment_1.32.0
[59] Biobase_2.64.0 MatrixGenerics_1.14.0
[61] matrixStats_1.3.0 GenomicRanges_1.54.1
[63] GenomeInfoDb_1.38.8 IRanges_2.36.0
[65] S4Vectors_0.40.2 BiocGenerics_0.48.1
[67] ANCOMBC_2.4.0 phyloseq_1.48.0
[69] glue_1.7.0 viridis_0.6.5
[71] viridisLite_0.4.2 plotly_4.10.4
[73] ggpubr_0.6.0 gridExtra_2.3
[75] hrbrthemes_0.8.7 rbiom_2.0.0.9137
[77] BiocManager_1.30.23 vegan_2.6-6.1
[79] lattice_0.22-6 permute_0.9-7
[81] lubridate_1.9.3 forcats_1.0.0
[83] stringr_1.5.1 dplyr_1.1.4
[85] purrr_1.0.2 readr_2.1.5
[87] tidyr_1.3.1 tibble_3.2.1
[89] ggplot2_3.5.1 tidyverse_2.0.0

loaded via a namespace (and not attached): [1] igraph_2.0.3 ca_0.71.1 Formula_1.2-5
[4] zlibbioc_1.48.2 tidyselect_1.2.1 bit_4.0.5
[7] doParallel_1.0.17 clue_0.3-65 rjson_0.2.21
[10] blob_1.2.4 rngtools_1.5.2 S4Arrays_1.2.1
[13] png_0.1-8 ggplotify_0.1.2 cli_3.6.3
[16] registry_0.5-1 CVXR_1.0-14 askpass_1.2.0
[19] multtest_2.58.0 openssl_2.2.0 textshaping_0.4.0
[22] bluster_1.12.0 officer_0.6.6 BiocNeighbors_1.20.2
[25] dendextend_1.17.1 curl_5.2.1 mime_0.12
[28] evaluate_0.24.0 tidytree_0.4.6 ggh4x_0.2.8
[31] stringi_1.8.4 backports_1.5.0 lmerTest_3.1-3
[34] gsl_2.1-8 Exact_3.3 httpuv_1.6.15
[37] umap_0.2.10.0 magrittr_2.0.3 splines_4.3.2
[40] doRNG_1.8.6 webshot_0.5.5 lpSolve_5.6.20
[43] rootSolve_1.8.2.4 ggbeeswarm_0.7.2 DBI_1.2.3
[46] withr_3.0.1 class_7.3-22 systemfonts_1.1.0
[49] lmtest_0.9-40 rprojroot_2.0.4 ggnewscale_0.5.0
[52] tidygraph_1.3.1 htmlwidgets_1.6.4 fs_1.6.4
[55] labeling_0.4.3 SparseArray_1.2.4 cellranger_1.1.0
[58] DEoptimR_1.1-3 extrafont_0.19 lmom_3.0
[61] reticulate_1.38.0 zoo_1.8-12 timechange_0.3.0
[64] decontam_1.22.0 foreach_1.5.2 fansi_1.0.6
[67] caTools_1.18.2 ggtree_3.10.1 rhdf5_2.46.1
[70] seriation_1.5.5 R.oo_1.26.0 RSpectra_0.16-2
[73] irlba_2.3.5.1 extrafontdb_1.0 gridGraphics_0.5-1
[76] DescTools_0.99.55 lazyeval_0.2.2 yaml_2.3.10
[79] ade4_1.7-22 survival_3.7-0 crayon_1.5.3
[82] mediation_4.5.0 tweenr_2.0.3 later_1.3.2
[85] gfonts_0.2.0 codetools_0.2-20 base64enc_0.1-3
[88] GlobalOptions_0.1.2 rlist_0.4.6.2 shape_1.4.6.1
[91] estimability_1.5.1 gdtools_0.3.7 foreign_0.8-87
[94] pkgconfig_2.0.3 xml2_1.3.6 aplot_0.2.3
[97] ape_5.8 xtable_1.8-4 car_3.1-2
[100] plyr_1.8.9 httr_1.4.7 rbibutils_2.2.16
[103] tools_4.3.2 beeswarm_0.4.0 htmlTable_2.4.3
[106] broom_1.0.6 checkmate_2.3.2 nlme_3.1-165
[109] qvcalc_1.0.3 assertthat_0.2.1 lme4_1.1-35.5
[112] digest_0.6.36 numDeriv_2016.8-1.1 relimp_1.0-5
[115] Matrix_1.6-5 farver_2.1.2 tzdb_0.4.0
[118] yulab.utils_0.1.5 DirichletMultinomial_1.44.0 rpart_4.1.23
[121] crul_1.5.0 cachem_1.1.0 polyclip_1.10-7
[124] generics_0.1.3 mvtnorm_1.2-5 biomformat_1.30.0
[127] fillpattern_1.0.2 ragg_1.3.2 ScaledMatrix_1.10.0
[130] fontBitstreamVera_0.1.1 carData_3.0-5 minqa_1.2.7
[133] jmvcore_2.4.7 utf8_1.2.4 graphlayouts_1.1.1
[136] gtools_3.9.5 httpcode_0.3.0 ggsignif_0.6.4
[139] GenomeInfoDbData_1.2.11 energy_1.7-11 R.utils_2.12.3
[142] rhdf5filters_1.14.1 RCurl_1.98-1.16 memoise_2.0.1
[145] rmarkdown_2.27 R.methodsS3_1.8.2 gld_2.6.6
[148] fontLiberation_0.1.0 rstudioapi_0.16.0 cluster_2.1.6
[151] hms_1.1.3 munsell_0.5.1 colorspace_2.1-1
[154] rlang_1.1.4 DelayedMatrixStats_1.24.0 sparseMatrixStats_1.14.0
[157] xts_0.14.0 quantmod_0.4.26 ggforce_0.4.2
[160] circlize_0.4.16 mgcv_1.9-1 xfun_0.46
[163] pacman_0.5.1 coda_0.19-4.1 e1071_1.7-14
[166] TH.data_1.1-2 iterators_1.0.14 emmeans_1.10.3
[169] abind_1.4-5 treeio_1.26.0 gmp_0.7-4
[172] Rhdf5lib_1.24.2 DECIPHER_2.30.0 repr_1.1.7
[175] bitops_1.0-8 Rdpack_2.6.1 promises_1.3.0
[178] RSQLite_2.3.7 sandwich_3.1-0 TSP_1.2-4
[181] DelayedArray_0.28.0 proxy_0.4-27 Rmpfr_0.9-5
[184] compiler_4.3.2 boot_1.3-30 beachmat_2.18.1
[187] Rcpp_1.0.13 Rttf2pt1_1.3.12 fontquiver_0.2.1
[190] BiocSingular_1.18.0 MASS_7.3-60.0.1 uuid_1.2-1
[193] BiocParallel_1.36.0 gridtext_0.1.5 R6_2.5.1
[196] fastmap_1.2.0 multcomp_1.4-26 vipor_0.4.7
[199] TTR_0.24.4 ggstats_0.6.0 rsvd_1.0.5
[202] nnet_7.3-19 gtable_0.3.5 KernSmooth_2.23-24
[205] htmltools_0.5.8.1 RcppParallel_5.1.8 bit64_4.0.5
[208] lifecycle_1.0.4 zip_2.3.1 nloptr_2.1.1
[211] vctrs_0.6.5 slam_0.1-52 snakecase_0.11.1
[214] ggfun_0.1.5 pillar_1.9.0 locfit_1.5-9.10
[217] jsonlite_1.8.8 expm_0.999-9 GetoptLong_1.0.5

[shwetha141]

mia is still in development and the latest changes occur in the official BIoconductor release with a delay of some months, the remotes::install_github("microbiome/mia") will install the latest development version (which is in sync with OMA).

I reinstalled mia ([using github](remotes::install_github("microbiome/OMA", dependencies = TRUE, upgrade = TRUE, force=TRUE)). I am able to run all the vignettes from OMA, but run into an error from the ones on Community typing (under Diversity and Similarity section). I am attaching the error . I am suspecting it could be regarding data formats

[antagomir]

Can you paste here output of typing "tse"?

[shwetha141]

[antagomir]

Thanks! Could you paste this as plain text, it will be easier to copy for testing?

[shwetha141]

Load dependencies

rm(list=ls()) library(bluster) library(kableExtra) library(mia) data("peerj13075", package = "mia") tse <- peerj13075

Filter out most taxa to ease the calculation

altExp(tse, "prevalent") <- agglomerateByPrevalence(

• tse, rank = "class", prevalence = 20/100, detection = 1/100) Error in x[[name, exact = FALSE]] : each subscript must be a single integer when subsetting an DummyArrayGrid object with [[

  Load dependencies

  rm(list=ls()) library(bluster) library(kableExtra) library(mia) data("peerj13075", package = "mia") tse <- peerj13075

Filter out most taxa to ease the calculation

altExp(tse, "prevalent") <- agglomerateByPrevalence(

• tse, rank = "class", prevalence = 20/100, detection = 1/100) Error in x[[name, exact = FALSE]] : each subscript must be a single integer when subsetting an DummyArrayGrid object with [[ tse class: TreeSummarizedExperiment dim: 674 58 metadata(0): assays(1): counts rownames(674): OTU1 OTU2 ... OTU2567 OTU2569 rowData names(6): kingdom phylum ... family genus colnames(58): ID1 ID2 ... ID57 ID58 colData names(5): Sample Geographical_location Gender Age Diet reducedDimNames(0): mainExpName: NULL altExpNames(0): rowLinks: NULL rowTree: NULL colLinks: NULL colTree: NULL

[shwetha141]

sessionInfo() R version 4.3.2 (2023-10-31) Platform: aarch64-apple-darwin20 (64-bit) Running under: macOS Sonoma 14.5

Matrix products: default BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0

locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: America/Chicago tzcode source: internal

attached base packages: [1] parallel grid stats4 stats graphics grDevices utils datasets [9] methods base

other attached packages: [1] kableExtra_1.4.0 bluster_1.12.0
[3] GWalkR_0.1.4 miaViz_1.13.9
[5] ggraph_2.2.1 scater_1.30.1
[7] scuttle_1.12.0 mia_1.13.36
[9] MultiAssayExperiment_1.28.0 TreeSummarizedExperiment_2.10.0 [11] Biostrings_2.70.3 XVector_0.42.0
[13] SingleCellExperiment_1.24.0 vcdExtra_0.8-5
[15] gnm_1.1-5 vcd_1.4-12
[17] jmv_2.5.6 charter_0.0.1.9000
[19] shiny_1.9.1 showtext_0.9-7
[21] showtextdb_3.0 sysfonts_0.8.9
[23] echarts4r_0.4.5 highcharter_0.9.4
[25] patchwork_1.2.0 ggthemes_5.1.0
[27] scico_1.5.0 rcartocolor_2.1.1
[29] ggtext_0.1.2 ggridges_0.5.6
[31] ggrepel_0.9.5 cowplot_1.1.3
[33] corrr_0.4.4 prismatic_1.1.2
[35] flextable_0.9.6 scales_1.3.0
[37] janitor_2.2.0 gtsummary_2.0.0
[39] skimr_2.1.5 here_1.0.1
[41] rio_1.2.1 readxl_1.4.3
[43] data.table_1.15.4 RColorBrewer_1.1-3
[45] heatmaply_1.5.0 Hmisc_5.1-3
[47] DT_0.33 knitr_1.48
[49] tsne_0.1-3.1 GGally_2.2.1
[51] reshape2_1.4.4 robustHD_0.8.1
[53] robustbase_0.99-3 perry_0.3.1
[55] corrplot_0.92 gplots_3.1.3.1
[57] rstatix_0.7.2 ComplexHeatmap_2.18.0
[59] DESeq2_1.42.1 SummarizedExperiment_1.32.0
[61] Biobase_2.64.0 MatrixGenerics_1.14.0
[63] matrixStats_1.3.0 GenomicRanges_1.54.1
[65] GenomeInfoDb_1.38.8 IRanges_2.36.0
[67] S4Vectors_0.40.2 BiocGenerics_0.48.1
[69] ANCOMBC_2.4.0 phyloseq_1.48.0
[71] glue_1.7.0 viridis_0.6.5
[73] viridisLite_0.4.2 plotly_4.10.4
[75] ggpubr_0.6.0 gridExtra_2.3
[77] hrbrthemes_0.8.7 rbiom_2.0.0.9137
[79] BiocManager_1.30.23 vegan_2.6-6.1
[81] lattice_0.22-6 permute_0.9-7
[83] lubridate_1.9.3 forcats_1.0.0
[85] stringr_1.5.1 dplyr_1.1.4
[87] purrr_1.0.2 readr_2.1.5
[89] tidyr_1.3.1 tibble_3.2.1
[91] ggplot2_3.5.1 tidyverse_2.0.0

loaded via a namespace (and not attached): [1] igraph_2.0.3 ca_0.71.1 Formula_1.2-5
[4] zlibbioc_1.48.2 tidyselect_1.2.1 bit_4.0.5
[7] doParallel_1.0.17 clue_0.3-65 rjson_0.2.21
[10] blob_1.2.4 rngtools_1.5.2 S4Arrays_1.2.1
[13] png_0.1-8 ggplotify_0.1.2 cli_3.6.3
[16] registry_0.5-1 CVXR_1.0-14 askpass_1.2.0
[19] multtest_2.58.0 openssl_2.2.0 textshaping_0.4.0
[22] officer_0.6.6 BiocNeighbors_1.20.2 dendextend_1.17.1
[25] curl_5.2.1 mime_0.12 evaluate_0.24.0
[28] tidytree_0.4.6 ggh4x_0.2.8 stringi_1.8.4
[31] backports_1.5.0 lmerTest_3.1-3 gsl_2.1-8
[34] Exact_3.3 httpuv_1.6.15 umap_0.2.10.0
[37] magrittr_2.0.3 splines_4.3.2 doRNG_1.8.6
[40] webshot_0.5.5 lpSolve_5.6.20 rootSolve_1.8.2.4
[43] ggbeeswarm_0.7.2 DBI_1.2.3 withr_3.0.1
[46] class_7.3-22 systemfonts_1.1.0 lmtest_0.9-40
[49] rprojroot_2.0.4 ggnewscale_0.5.0 tidygraph_1.3.1
[52] htmlwidgets_1.6.4 fs_1.6.4 labeling_0.4.3
[55] SparseArray_1.2.4 cellranger_1.1.0 DEoptimR_1.1-3
[58] extrafont_0.19 lmom_3.0 reticulate_1.38.0
[61] zoo_1.8-12 timechange_0.3.0 decontam_1.22.0
[64] foreach_1.5.2 fansi_1.0.6 caTools_1.18.2
[67] ggtree_3.10.1 rhdf5_2.46.1 seriation_1.5.5
[70] R.oo_1.26.0 RSpectra_0.16-2 irlba_2.3.5.1
[73] extrafontdb_1.0 gridGraphics_0.5-1 DescTools_0.99.55
[76] lazyeval_0.2.2 yaml_2.3.10 ade4_1.7-22
[79] survival_3.7-0 crayon_1.5.3 mediation_4.5.0
[82] tweenr_2.0.3 later_1.3.2 gfonts_0.2.0
[85] codetools_0.2-20 base64enc_0.1-3 GlobalOptions_0.1.2
[88] rlist_0.4.6.2 shape_1.4.6.1 estimability_1.5.1
[91] gdtools_0.3.7 foreign_0.8-87 pkgconfig_2.0.3
[94] xml2_1.3.6 aplot_0.2.3 ape_5.8
[97] xtable_1.8-4 car_3.1-2 plyr_1.8.9
[100] httr_1.4.7 rbibutils_2.2.16 tools_4.3.2
[103] beeswarm_0.4.0 htmlTable_2.4.3 broom_1.0.6
[106] checkmate_2.3.2 nlme_3.1-165 qvcalc_1.0.3
[109] assertthat_0.2.1 lme4_1.1-35.5 digest_0.6.36
[112] numDeriv_2016.8-1.1 relimp_1.0-5 Matrix_1.6-5
[115] farver_2.1.2 tzdb_0.4.0 yulab.utils_0.1.5
[118] DirichletMultinomial_1.44.0 rpart_4.1.23 crul_1.5.0
[121] cachem_1.1.0 polyclip_1.10-7 generics_0.1.3
[124] mvtnorm_1.2-5 biomformat_1.30.0 fillpattern_1.0.2
[127] ragg_1.3.2 ScaledMatrix_1.10.0 fontBitstreamVera_0.1.1
[130] carData_3.0-5 minqa_1.2.7 jmvcore_2.4.7
[133] utf8_1.2.4 graphlayouts_1.1.1 gtools_3.9.5
[136] httpcode_0.3.0 ggsignif_0.6.4 GenomeInfoDbData_1.2.11
[139] energy_1.7-11 R.utils_2.12.3 rhdf5filters_1.14.1
[142] RCurl_1.98-1.16 memoise_2.0.1 rmarkdown_2.27
[145] R.methodsS3_1.8.2 gld_2.6.6 svglite_2.1.3
[148] fontLiberation_0.1.0 rstudioapi_0.16.0 cluster_2.1.6
[151] hms_1.1.3 munsell_0.5.1 colorspace_2.1-1
[154] rlang_1.1.4 DelayedMatrixStats_1.24.0 sparseMatrixStats_1.14.0
[157] xts_0.14.0 quantmod_0.4.26 ggforce_0.4.2
[160] circlize_0.4.16 mgcv_1.9-1 xfun_0.46
[163] pacman_0.5.1 coda_0.19-4.1 e1071_1.7-14
[166] TH.data_1.1-2 remotes_2.5.0 iterators_1.0.14
[169] emmeans_1.10.3 abind_1.4-5 treeio_1.26.0
[172] gmp_0.7-4 Rhdf5lib_1.24.2 DECIPHER_2.30.0
[175] repr_1.1.7 bitops_1.0-8 Rdpack_2.6.1
[178] promises_1.3.0 RSQLite_2.3.7 sandwich_3.1-0
[181] TSP_1.2-4 DelayedArray_0.28.0 proxy_0.4-27
[184] Rmpfr_0.9-5 compiler_4.3.2 boot_1.3-30
[187] beachmat_2.18.1 Rcpp_1.0.13 Rttf2pt1_1.3.12
[190] fontquiver_0.2.1 BiocSingular_1.18.0 MASS_7.3-60.0.1
[193] uuid_1.2-1 BiocParallel_1.36.0 gridtext_0.1.5
[196] R6_2.5.1 fastmap_1.2.0 multcomp_1.4-26
[199] vipor_0.4.7 TTR_0.24.4 ggstats_0.6.0
[202] rsvd_1.0.5 nnet_7.3-19 gtable_0.3.5
[205] KernSmooth_2.23-24 htmltools_0.5.8.1 RcppParallel_5.1.8
[208] bit64_4.0.5 lifecycle_1.0.4 zip_2.3.1
[211] nloptr_2.1.1 vctrs_0.6.5 slam_0.1-52
[214] snakecase_0.11.1 ggfun_0.1.5 pillar_1.9.0
[217] locfit_1.5-9.10 jsonlite_1.8.8 expm_0.999-9
[220] GetoptLong_1.0.5

[antagomir]

Strange, I cannot reproduce the bug.

Is this the exact sequence that you run after launching a fresh R session:

rm(list=ls())
library(bluster)
library(kableExtra)
library(mia)
data("peerj13075", package = "mia")
tse <- peerj13075
altExp(tse, "prevalent") <- agglomerateByPrevalence(tse, rank = "class", prevalence = 20/100, detection = 1/100)

[shwetha141]

Hmm. So you are right. I used the same code on the new session and it didn't give me an error (ddn't run the previous sections). When I sent you the code, I was following the book per page. I think I do something majorly wrong in between the first section and the last section of the Diversity and similarity.. Thanks though. Can I ask you something? Why can't i see these functions on git hub? Thank you for this!

[antagomir]

Possibly there was some difference in the code that you initially used.

I cannot fully assess that because you have only shared 1) screenshot, and later 2) copypasted code that breaks in the middle (see above). It can help to use the "code" higlight (from the top panel of this text box, "< >"). Then we could directly compare the exact code. Perhaps you copied also the "+" mark in the code? That is actually not code but instead denotes line break and it should not be included in the code. Anyway, if the problem is solved now it seems good.

Not seeing the functions on Github: where did you try to search for those functions in Github? Do you need to see the function source code, function documentation page, or something else?

[shwetha141]

I reckon you are right. So rather than probe this further , I will try to run each section individually and as whole and see where I go wrong. It is quite possibly that I am doing something wrong. The reason I asked about the functions like agglomerate by rank, I think it aggregates the count matrix by the rank you specify. I was looking at the source code for functions such as agglomerateByPrevalence from the OMA in here https://github.com/microbiome/mia. Then I found it in agglomerate.R. Apologies.

[antagomir]

Ok - and documentation for each function, with examples and details are here: https://microbiome.github.io/mia/reference/index.html