The objective of this R Markdown code is to reproduce the building of the 5 dietary patterns (DP5) obtained via Dirichlet Multinomial Mixture (DMM) models in Cotillard at al., A posteriori dietary patterns better explain variations of the gut microbiome than individual markers in the American Gut Project, accepted in AJCN. (https://doi.org/10.1093/ajcn/nqab332) It also includes code for associations with 16S gut microbiome using DESeq2.
Load all directories keeping the same organization and just run the .Rmd file after installing the require packages.
Thank you to Mathilde Saccareau and Julien Tap (https://github.com/tapj) for their contributions.
The code is under GNU GPL-3
R version 4.0.3 (2020-10-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19041)
attached base packages:
[1] parallel stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] DESeq2_1.28.1 SummarizedExperiment_1.18.2 DelayedArray_0.14.1 Biobase_2.48.0 GenomicRanges_1.40.0
[6] GenomeInfoDb_1.24.2 phyloseq_1.32.0 vegan_2.5-6 lattice_0.20-41 permute_0.9-5
[11] reshape2_1.4.4 gtools_3.8.2 multcompView_0.1-8 compareGroups_4.4.5 DT_0.16
[16] matrixStats_0.57.0 effsize_0.8.1 dplyr_1.0.2 scales_1.1.1 DirichletMultinomial_1.30.0
[21] IRanges_2.22.2 S4Vectors_0.26.1 BiocGenerics_0.34.0 fpc_2.2-8 glue_1.4.2
[26] ggplot2_3.3.2
loaded via a namespace (and not attached):
[1] uuid_0.1-4 backports_1.2.0 systemfonts_0.3.2 plyr_1.8.6 igraph_1.2.6 splines_4.0.3
[7] crosstalk_1.1.0.1 BiocParallel_1.22.0 digest_0.6.27 foreach_1.5.1 htmltools_0.5.0 viridis_0.5.1
[13] fansi_0.4.1 memoise_1.1.0 magrittr_2.0.1 Rsolnp_1.16 cluster_2.1.0 Biostrings_2.56.0
[19] annotate_1.66.0 officer_0.3.15 prettyunits_1.1.1 colorspace_2.0-0 blob_1.2.1 rvest_0.3.6
[25] xfun_0.19 crayon_1.3.4 RCurl_1.98-1.2 jsonlite_1.7.1 genefilter_1.70.0 survival_3.2-7
[31] iterators_1.0.13 ape_5.4-1 kableExtra_1.3.1 gtable_0.3.0 zlibbioc_1.34.0 XVector_0.28.0
[37] webshot_0.5.2 kernlab_0.9-29 Rhdf5lib_1.10.0 prabclus_2.3-2 DEoptimR_1.0-8 DBI_1.1.0
[43] Rcpp_1.0.5 viridisLite_0.3.0 xtable_1.8-4 progress_1.2.2 bit_4.0.4 mclust_5.4.6
[49] truncnorm_1.0-8 htmlwidgets_1.5.2 httr_1.4.2 RColorBrewer_1.1-2 modeltools_0.2-23 ellipsis_0.3.1
[55] mice_3.11.0 farver_2.0.3 pkgconfig_2.0.3 XML_3.99-0.5 flexmix_2.3-17 nnet_7.3-14
[61] locfit_1.5-9.4 labeling_0.4.2 tidyselect_1.1.0 rlang_0.4.8 AnnotationDbi_1.50.1 munsell_0.5.0
[67] tools_4.0.3 cli_2.1.0 generics_0.1.0 RSQLite_2.2.1 ade4_1.7-16 broom_0.7.2
[73] evaluate_0.14 biomformat_1.16.0 stringr_1.4.0 yaml_2.2.1 knitr_1.30 bit64_4.0.5
[79] zip_2.1.1 robustbase_0.93-6 purrr_0.3.4 dendextend_1.14.0 nlme_3.1-150 xml2_1.3.2
[85] compiler_4.0.3 rstudioapi_0.13 geneplotter_1.66.0 tibble_3.0.4 stringi_1.5.3 HardyWeinberg_1.6.8
[91] gdtools_0.2.2 Matrix_1.2-18 multtest_2.44.0 vctrs_0.3.5 pillar_1.4.7 lifecycle_0.2.0
[97] data.table_1.13.2 bitops_1.0-6 flextable_0.5.11 R6_2.5.0 gridExtra_2.3 writexl_1.3.1
[103] codetools_0.2-18 assertthat_0.2.1 MASS_7.3-53 chron_2.3-56 rhdf5_2.32.0 withr_2.3.0
[109] GenomeInfoDbData_1.2.3 diptest_0.75-7 mgcv_1.8-33 hms_0.5.3 grid_4.0.3 tidyr_1.1.2
[115] class_7.3-17 rmarkdown_2.5 base64enc_0.1-3