Analysis of microbiome data on R for the project :
"The Gut Microbial Composition is Species-specific and Individual-specific in two Species of Estrildid Finches, the Bengalese Finch and the Zebra Finch"
Authors:
Öncü Maraci, Anna Antonatou-Papaioannou Sebastian Jünneman, Omar Castillo-Gutiérrez, Tobias Busche, Jörn Kalinowski, Barbara A. Caspers
In this project, we aim to investigate the impact of host-specific factors on gut microbial communities of in two estrildid finch species, the Bengalese finch and the zebra finch. We housed the breeding-pairs under strictly controlled environmental and dietary conditions and collected faecal samples at five different time points, over a range of 120 days covering different stages of the reproductive cycle. We investigated the differences and similarities between species, sexes, breeding pairs and sampling times in alpha and beta diversity.
sessionInfo() R version 4.0.2 (2020-06-22) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows >= 8 x64 (build 9200)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C LC_TIME=English_United States.1252
system code page: 65001
attached base packages: [1] stats4 grid parallel stats graphics grDevices utils datasets methods base
other attached packages:
[1] rfm_0.2.2 DESeq2_1.28.1 SummarizedExperiment_1.18.1 DelayedArray_0.14.1
[5] matrixStats_0.56.0 GenomicRanges_1.40.0 GenomeInfoDb_1.24.2 IRanges_2.22.2
[9] S4Vectors_0.26.1 microbiome_1.10.0 biomformat_1.16.0 phyloseq_1.32.0
[13] reshape2_1.4.4 scales_1.1.1 dplyr_1.0.2 ggpubr_0.4.0
[17] ggplot2_3.3.2 rstatix_0.6.0 dunn.test_1.3.5 picante_1.8.2
[21] nlme_3.1-148 vegan_2.5-6 lattice_0.20-41 permute_0.9-5
[25] ape_5.4-1 metagenomeSeq_1.30.0 RColorBrewer_1.1-2 glmnet_4.0-2
[29] Matrix_1.2-18 limma_3.44.3 Biobase_2.48.0 BiocGenerics_0.34.0
loaded via a namespace (and not attached):
[1] Rtsne_0.15 colorspace_1.4-1 ggsignif_0.6.0 ellipsis_0.3.1 rio_0.5.16
[6] rprojroot_1.3-2 XVector_0.28.0 fs_1.5.0 rstudioapi_0.11 remotes_2.2.0
[11] bit64_4.0.5 AnnotationDbi_1.50.3 fansi_0.4.1 codetools_0.2-16 splines_4.0.2
[16] geneplotter_1.66.0 pkgload_1.1.0 ade4_1.7-15 jsonlite_1.6.1 broom_0.7.0
[21] annotate_1.66.0 cluster_2.1.0 compiler_4.0.2 backports_1.1.9 assertthat_0.2.1
[26] cli_2.0.2 prettyunits_1.1.1 tools_4.0.2 igraph_1.2.5 gtable_0.3.0
[31] glue_1.4.2 GenomeInfoDbData_1.2.3 Rcpp_1.0.5 carData_3.0-4 cellranger_1.1.0
[36] vctrs_0.3.2 Biostrings_2.56.0 multtest_2.44.0 gdata_2.18.0 iterators_1.0.12
[41] stringr_1.4.0 ps_1.3.4 testthat_2.3.2 openxlsx_4.1.5 lifecycle_0.2.0
[46] devtools_2.3.1 gtools_3.8.2 XML_3.99-0.3 zlibbioc_1.34.0 MASS_7.3-51.6
[51] hms_0.5.3 rhdf5_2.32.0 yaml_2.2.1 curl_4.3 memoise_1.1.0
[56] stringi_1.5.3 RSQLite_2.2.0 genefilter_1.70.0 desc_1.2.0 foreach_1.5.0
[61] caTools_1.18.0 pkgbuild_1.1.0 zip_2.0.4 BiocParallel_1.22.0 shape_1.4.4
[66] rlang_0.4.7 pkgconfig_2.0.3 bitops_1.0-6 Wrench_1.6.0 purrr_0.3.4
[71] Rhdf5lib_1.10.0 processx_3.4.4 cowplot_1.1.0 bit_4.0.4 tidyselect_1.1.0
[76] plyr_1.8.6 magrittr_1.5 R6_2.4.1 gplots_3.0.4 generics_0.0.2
[81] DBI_1.1.0 withr_2.2.0 pillar_1.4.6 haven_2.3.1 foreign_0.8-80
[86] mgcv_1.8-31 survival_3.1-12 abind_1.4-5 RCurl_1.98-1.2 tibble_3.0.1
[91] crayon_1.3.4 car_3.0-9 KernSmooth_2.23-17 usethis_1.6.1 locfit_1.5-9.4
[96] readxl_1.3.1 data.table_1.13.0 callr_3.4.4 blob_1.2.1 forcats_0.5.0
[101] digest_0.6.25 xtable_1.8-4 tidyr_1.1.0 munsell_0.5.0 sessioninfo_1.1.1