library(MiscMetabar)
library(formattable)
data(data_fungi)
data(data_fungi_sp_known)Export phyloseq object
You can export a phyloseq object to csv (and txt for phylogenetic
tree) files in a folder. It is possible to export each table into one
file or to merge all slot (except phytree) in one file (args
one_file = TRUE). Finally, if rdata is set to
TRUE, a rdata file containing the phyloseq object is also
writed.
write_pq(data_fungi, path = "fungi_phyloseq")
write_pq(data_fungi, path = "fungi_phyloseq", one_file = TRUE)
write_pq(data_fungi, path = "fungi_phyloseq", rdata = TRUE)Finally, you can use the function save_pq() to write the
phyloseq object in all 3 versions (one table for each slot, a file
merging each slot and an Rdata file).
save_pq(data_fungi)Import
To import a Rdata file, just use load() base function.
In order to import phyloseq object from a folder create using
write_pq() or save_pq(), please use the
function read_pq().
d <- read_pq(path = "fungi_phyloseq")Tracking sequences, clusters and samples
In bioinformatic pipeline, we often need to track the number of
samples, sequences and clusters across step in the pipeline. MiscMetabar
propose two utilities to achieve this goal : track_wkflow()
and a version to compute value per samples :
track_wkflow_samples(). The function
track_wkflow() can deal with (i) fastq and fastg.gz files,
dada-class object, derep-class object, matrix of samples x clusters
(e.g. otu_table) and phyloseq-class object.
track_wkflow(list(data_fungi, data_fungi_sp_known))
#> nb_sequences nb_clusters nb_samples
#> 1 1839124 1420 185
#> 2 1106581 651 185Session information
sessionInfo()
#> R version 4.3.3 (2024-02-29)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Debian GNU/Linux 11 (bullseye)
#>
#> Matrix products: default
#> BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
#> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.13.so; LAPACK version 3.9.0
#>
#> locale:
#> [1] LC_CTYPE=fr_FR.UTF-8 LC_NUMERIC=C
#> [3] LC_TIME=fr_FR.UTF-8 LC_COLLATE=fr_FR.UTF-8
#> [5] LC_MONETARY=fr_FR.UTF-8 LC_MESSAGES=fr_FR.UTF-8
#> [7] LC_PAPER=fr_FR.UTF-8 LC_NAME=C
#> [9] LC_ADDRESS=C LC_TELEPHONE=C
#> [11] LC_MEASUREMENT=fr_FR.UTF-8 LC_IDENTIFICATION=C
#>
#> time zone: Europe/Paris
#> tzcode source: system (glibc)
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] formattable_0.2.1 MiscMetabar_0.9.1 purrr_1.0.2 dplyr_1.1.4
#> [5] dada2_1.30.0 Rcpp_1.0.12 ggplot2_3.5.0 phyloseq_1.46.0
#>
#> loaded via a namespace (and not attached):
#> [1] bitops_1.0-7 pbapply_1.7-2
#> [3] deldir_2.0-4 permute_0.9-7
#> [5] rlang_1.1.3 magrittr_2.0.3
#> [7] ade4_1.7-22 matrixStats_1.3.0
#> [9] compiler_4.3.3 mgcv_1.9-1
#> [11] png_0.1-8 systemfonts_1.0.6
#> [13] vctrs_0.6.5 reshape2_1.4.4
#> [15] stringr_1.5.1 pkgconfig_2.0.3
#> [17] crayon_1.5.2 fastmap_1.1.1
#> [19] XVector_0.42.0 utf8_1.2.4
#> [21] Rsamtools_2.18.0 rmarkdown_2.26
#> [23] ragg_1.3.0 xfun_0.43
#> [25] zlibbioc_1.48.2 cachem_1.0.8
#> [27] GenomeInfoDb_1.38.8 jsonlite_1.8.8
#> [29] biomformat_1.30.0 rhdf5filters_1.14.1
#> [31] DelayedArray_0.28.0 Rhdf5lib_1.24.2
#> [33] BiocParallel_1.36.0 jpeg_0.1-10
#> [35] parallel_4.3.3 cluster_2.1.6
#> [37] R6_2.5.1 bslib_0.7.0
#> [39] stringi_1.8.3 RColorBrewer_1.1-3
#> [41] GenomicRanges_1.54.1 jquerylib_0.1.4
#> [43] SummarizedExperiment_1.32.0 iterators_1.0.14
#> [45] knitr_1.46 IRanges_2.36.0
#> [47] Matrix_1.6-5 splines_4.3.3
#> [49] igraph_2.0.3 tidyselect_1.2.1
#> [51] rstudioapi_0.16.0 abind_1.4-5
#> [53] yaml_2.3.8 vegan_2.6-4
#> [55] codetools_0.2-19 hwriter_1.3.2.1
#> [57] lattice_0.22-6 tibble_3.2.1
#> [59] plyr_1.8.9 Biobase_2.62.0
#> [61] withr_3.0.0 ShortRead_1.60.0
#> [63] evaluate_0.23 desc_1.4.3
#> [65] survival_3.5-8 RcppParallel_5.1.7
#> [67] Biostrings_2.70.3 pillar_1.9.0
#> [69] MatrixGenerics_1.14.0 foreach_1.5.2
#> [71] stats4_4.3.3 generics_0.1.3
#> [73] RCurl_1.98-1.14 S4Vectors_0.40.2
#> [75] munsell_0.5.1 scales_1.3.0
#> [77] glue_1.7.0 tools_4.3.3
#> [79] interp_1.1-6 data.table_1.15.4
#> [81] GenomicAlignments_1.38.2 fs_1.6.3
#> [83] rhdf5_2.46.1 grid_4.3.3
#> [85] ape_5.8 latticeExtra_0.6-30
#> [87] colorspace_2.1-0 nlme_3.1-164
#> [89] GenomeInfoDbData_1.2.11 cli_3.6.2
#> [91] textshaping_0.3.7 fansi_1.0.6
#> [93] S4Arrays_1.2.1 gtable_0.3.4
#> [95] sass_0.4.9 digest_0.6.35
#> [97] BiocGenerics_0.48.1 SparseArray_1.2.4
#> [99] htmlwidgets_1.6.4 memoise_2.0.1
#> [101] htmltools_0.5.8.1 pkgdown_2.0.7
#> [103] multtest_2.58.0 lifecycle_1.0.4
#> [105] MASS_7.3-60.0.1