-## R version 4.3.1 (2023-06-16)
-## Platform: x86_64-apple-darwin20 (64-bit)
-## Running under: macOS Ventura 13.4.1
+## R version 4.3.2 (2023-10-31)
+## Platform: x86_64-pc-linux-gnu (64-bit)
+## Running under: Ubuntu 23.10
##
## Matrix products: default
-## BLAS: /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRblas.0.dylib
-## LAPACK: /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0
+## BLAS: /home/leo/bin/R-4.3.2/lib/libRblas.so
+## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.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
+## [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
##
## time zone: Europe/Helsinki
-## tzcode source: internal
+## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
-## [1] miaSim_1.7.8 TreeSummarizedExperiment_2.9.0
-## [3] Biostrings_2.69.2 XVector_0.41.1
-## [5] SingleCellExperiment_1.23.0 SummarizedExperiment_1.31.1
-## [7] Biobase_2.61.0 GenomicRanges_1.53.1
-## [9] GenomeInfoDb_1.37.2 IRanges_2.35.2
-## [11] S4Vectors_0.39.1 BiocGenerics_0.47.0
-## [13] MatrixGenerics_1.13.1 matrixStats_1.0.0
-## [15] BiocStyle_2.29.1
+## [1] miaSim_1.9.1 TreeSummarizedExperiment_2.10.0
+## [3] Biostrings_2.70.1 XVector_0.42.0
+## [5] SingleCellExperiment_1.24.0 SummarizedExperiment_1.32.0
+## [7] Biobase_2.62.0 GenomicRanges_1.54.1
+## [9] GenomeInfoDb_1.38.5 IRanges_2.36.0
+## [11] S4Vectors_0.40.2 BiocGenerics_0.48.1
+## [13] MatrixGenerics_1.14.0 matrixStats_1.2.0
+## [15] BiocStyle_2.30.0
##
## loaded via a namespace (and not attached):
-## [1] xfun_0.39 bslib_0.5.0 poweRlaw_0.70.6
-## [4] lattice_0.21-8 yulab.utils_0.0.6 vctrs_0.6.3
-## [7] tools_4.3.1 bitops_1.0-7 generics_0.1.3
-## [10] parallel_4.3.1 tibble_3.2.1 fansi_1.0.4
-## [13] pkgconfig_2.0.3 Matrix_1.6-0 desc_1.4.2
-## [16] lifecycle_1.0.3 GenomeInfoDbData_1.2.10 compiler_4.3.1
-## [19] stringr_1.5.0 treeio_1.25.2 textshaping_0.3.6
-## [22] codetools_0.2-19 htmltools_0.5.5 sass_0.4.7
-## [25] lazyeval_0.2.2 RCurl_1.98-1.12 yaml_2.3.7
-## [28] pracma_2.4.2 tidyr_1.3.0 pkgdown_2.0.7.9000
-## [31] pillar_1.9.0 crayon_1.5.2 jquerylib_0.1.4
-## [34] BiocParallel_1.35.3 DelayedArray_0.27.10 cachem_1.0.8
-## [37] abind_1.4-5 nlme_3.1-162 tidyselect_1.2.0
-## [40] digest_0.6.33 stringi_1.7.12 dplyr_1.1.2
-## [43] purrr_1.0.1 bookdown_0.34 rprojroot_2.0.3
-## [46] fastmap_1.1.1 grid_4.3.1 cli_3.6.1
-## [49] SparseArray_1.1.11 magrittr_2.0.3 S4Arrays_1.1.5
-## [52] utf8_1.2.3 ape_5.7-1 rmarkdown_2.23
-## [55] deSolve_1.36 ragg_1.2.5 memoise_2.0.1
-## [58] evaluate_0.21 knitr_1.43 rlang_1.1.1
-## [61] Rcpp_1.0.11 tidytree_0.4.4 glue_1.6.2
-## [64] BiocManager_1.30.21.1 rstudioapi_0.15.0 jsonlite_1.8.7
-## [67] R6_2.5.1 systemfonts_1.0.4 fs_1.6.3
-## [70] zlibbioc_1.47.0
+## [1] xfun_0.41 bslib_0.6.1 poweRlaw_0.70.6
+## [4] lattice_0.22-5 yulab.utils_0.1.2 vctrs_0.6.5
+## [7] tools_4.3.2 bitops_1.0-7 generics_0.1.3
+## [10] parallel_4.3.2 tibble_3.2.1 fansi_1.0.6
+## [13] pkgconfig_2.0.3 Matrix_1.6-4 desc_1.4.3
+## [16] lifecycle_1.0.4 GenomeInfoDbData_1.2.11 compiler_4.3.2
+## [19] treeio_1.26.0 textshaping_0.3.7 codetools_0.2-19
+## [22] htmltools_0.5.7 sass_0.4.8 lazyeval_0.2.2
+## [25] RCurl_1.98-1.13 yaml_2.3.8 pracma_2.4.4
+## [28] tidyr_1.3.0 pkgdown_2.0.7 pillar_1.9.0
+## [31] crayon_1.5.2 jquerylib_0.1.4 BiocParallel_1.36.0
+## [34] DelayedArray_0.28.0 cachem_1.0.8 abind_1.4-5
+## [37] nlme_3.1-164 tidyselect_1.2.0 digest_0.6.33
+## [40] dplyr_1.1.4 purrr_1.0.2 bookdown_0.37
+## [43] fastmap_1.1.1 grid_4.3.2 cli_3.6.2
+## [46] SparseArray_1.2.3 magrittr_2.0.3 S4Arrays_1.2.0
+## [49] utf8_1.2.4 ape_5.7-1 rmarkdown_2.25.2
+## [52] deSolve_1.40 ragg_1.2.7 memoise_2.0.1
+## [55] evaluate_0.23 knitr_1.45 rlang_1.1.2
+## [58] Rcpp_1.0.11 tidytree_0.4.6 glue_1.6.2
+## [61] BiocManager_1.30.22 jsonlite_1.8.8 R6_2.5.1
+## [64] systemfonts_1.0.5 fs_1.6.3 zlibbioc_1.48.0
### Citing the package
@@ -74,12 +80,10 @@ Gao _et al._ (2023). Methods in Ecology and Evolution. DOI:
For citation details, see R command `citation("miaSim")`.
-# Code of conduct
-
-Please note that the project is released with a [Bioconductor Code of
-Conduct](https://bioconductor.github.io/bioc_coc_multilingual/).
-By contributing to this project, you agree to abide by its terms.
-
+**Code of conduct** Please note that the project is released with a
+[Bioconductor Code of
+Conduct](https://bioconductor.github.io/bioc_coc_multilingual/). By
+contributing to this project, you agree to abide by its terms.
[github-watch-badge]: https://img.shields.io/github/watchers/microbiome/miaSim.svg?style=social
diff --git a/README.md b/README.md
index 083e6a9..9faf7ca 100644
--- a/README.md
+++ b/README.md
@@ -6,7 +6,6 @@
[](https://gitter.im/microbiome/miaverse)
[![Watch on GitHub][github-watch-badge]][github-watch]
[![Star on GitHub][github-star-badge]][github-star]
-
[](https://github.com/microbiome/miaSim/actions)
@@ -15,18 +14,10 @@
## miaSim
-This miaSim R/Bioconductor package can be used to simulate
-(longitudinal) data for the benchmarking and analysis of quantitative
-models of microbial communities.
-
-For installation and use, see the [Getting
-started](https://microbiome.github.io/miaSim/articles/miaSim.html)
-page.
-
-The package is based on the `(Tree)SummarizedExperiment` data
-container that supports microbiome data analysis. The package
-[homepage](https://microbiome.github.io/miaSim/) provides further
-tutorials and references for the [implemented
+This R/Bioconductor package provides tools to simulate (longitudinal)
+time series data from popular models in microbial ecology. The
+[homepage](https://microbiome.github.io/miaSim/) provides tutorials
+and references for the [implemented
models](https://microbiome.github.io/miaSim/reference/index.html):
* Self-organised instability (SOI)
@@ -36,7 +27,14 @@ models](https://microbiome.github.io/miaSim/reference/index.html):
* Stochastic logistic model
* Consumer-resource model
+These methods can be used for _in silico_ studies of microbial
+community dynamics or multi-omic or host-microbiome interactions. The
+miaSim package supports the Bioconductor [multi-assay data science
+framework](https://microbiome.github.io/OMA) for multi-omic data
+integration and time series analysis, and utilizes the
+`(Tree)SummarizedExperiment` data container.
+[Getting started](https://microbiome.github.io/miaSim/articles/miaSim.html).
### miaSimShiny
@@ -64,6 +62,13 @@ flow kind of approach. Development version should be done against the
We are grateful to all
[contributors](https://github.com/microbiome/miaSim/graphs/contributors).
+This research has received funding from
+
+ * the Horizon 2020 Programme of the European Union within the [FindingPheno project](https://www.findingpheno.eu/) under grant agreement No 952914.
+ * Research Council of Finland (grant 330887)
+
+
+