ps_get returns phyloseq
info_get returns psExtraInfo object
dist_get returns distance matrix (or NULL)
ord_get returns ordination object (or NULL)
perm_get returns adonis2() permanova model (or NULL)
bdisp_get returns results of betadisper() (or NULL)
otu_get returns phyloseq otu_table matrix with taxa as columns
tt_get returns phyloseq tax_table
tax_models_get returns list generated by tax_model or NULL
tax_stats_get returns dataframe generated by tax_models2stats or NULL
taxatree_models_get returns list generated by taxatree_models or NULL
taxatree_stats_get returns dataframe generated by taxatree_models2stats or NULL
samdat_tbl returns phyloseq sample_data as a tibble
with sample_names as new first column called .sample_name
ps_get(psExtra, ps_extra, counts = FALSE, warn = TRUE)
dist_get(psExtra, ps_extra)
ord_get(psExtra, ps_extra)
info_get(psExtra, ps_extra)
perm_get(psExtra, ps_extra)
bdisp_get(psExtra, ps_extra)
tax_models_get(psExtra)
tax_stats_get(psExtra)
taxatree_models_get(psExtra)
taxatree_stats_get(psExtra)
otu_get(data, taxa = NA, samples = NA, counts = FALSE, warn = TRUE)
tt_get(data)
samdat_tbl(data, sample_names_col = ".sample_name")psExtra S4 class object
deprecated! don't use this
should ps_get or otu_get attempt to return counts? if present in object
if counts = TRUE, should a warning be emitted if counts are not available? set warn = "error" to stop if counts are not available
phyloseq or psExtra
subset of taxa to return, NA for all (default)
subset of samples to return, NA for all (default)
name of column where sample_names are put. if NA, return data.frame with rownames (sample_names)
element(s) from psExtra object (or NULL)
data("dietswap", package = "microbiome")
psx <- tax_transform(dietswap, "compositional", rank = "Genus")
psx
#> psExtra object - a phyloseq object with extra slots:
#>
#> phyloseq-class experiment-level object
#> otu_table() OTU Table: [ 130 taxa and 222 samples ]
#> sample_data() Sample Data: [ 222 samples by 8 sample variables ]
#> tax_table() Taxonomy Table: [ 130 taxa by 3 taxonomic ranks ]
#>
#> otu_get(counts = TRUE) [ 130 taxa and 222 samples ]
#>
#> psExtra info:
#> tax_agg = "Genus" tax_trans = "compositional"
ps_get(psx)
#> phyloseq-class experiment-level object
#> otu_table() OTU Table: [ 130 taxa and 222 samples ]
#> sample_data() Sample Data: [ 222 samples by 8 sample variables ]
#> tax_table() Taxonomy Table: [ 130 taxa by 3 taxonomic ranks ]
ps_get(psx, counts = TRUE)
#> phyloseq-class experiment-level object
#> otu_table() OTU Table: [ 130 taxa and 222 samples ]
#> sample_data() Sample Data: [ 222 samples by 8 sample variables ]
#> tax_table() Taxonomy Table: [ 130 taxa by 3 taxonomic ranks ]
info_get(psx)
#> psExtra info:
#> tax_agg = "Genus" tax_trans = "compositional"
dist_get(psx) # this psExtra has no dist_calc result
#> NULL
ord_get(psx) # this psExtra has no ord_calc result
#> NULL
perm_get(psx) # this psExtra has no dist_permanova result
#> NULL
bdisp_get(psx) # this psExtra has no dist_bdisp result
#> NULL
# these can be returned from phyloseq objects too
otu_get(psx, taxa = 6:9, samples = c("Sample-9", "Sample-1", "Sample-6"))
#> OTU Table: [4 taxa and 3 samples]
#> taxa are columns
#> Allistipes et rel. Anaerobiospirillum Anaerofustis
#> Sample-9 0.0016615239 0 0
#> Sample-1 0.0397210072 0 0
#> Sample-6 0.0008609339 0 0
#> Anaerostipes caccae et rel.
#> Sample-9 0.002729646
#> Sample-1 0.028845017
#> Sample-6 0.001468652
otu_get(psx, taxa = 6:9, samples = c(9, 1, 6), counts = TRUE)
#> OTU Table: [4 taxa and 3 samples]
#> taxa are columns
#> Allistipes et rel. Anaerobiospirillum Anaerofustis
#> Sample-9 14 0 0
#> Sample-1 336 0 0
#> Sample-6 17 0 0
#> Anaerostipes caccae et rel.
#> Sample-9 23
#> Sample-1 244
#> Sample-6 29
tt_get(psx) %>% head()
#> Taxonomy Table: [6 taxa by 3 taxonomic ranks]:
#> Phylum Family
#> Actinomycetaceae "Actinobacteria" "Actinobacteria"
#> Aerococcus "Firmicutes" "Bacilli"
#> Aeromonas "Proteobacteria" "Proteobacteria"
#> Akkermansia "Verrucomicrobia" "Verrucomicrobia"
#> Alcaligenes faecalis et rel. "Proteobacteria" "Proteobacteria"
#> Allistipes et rel. "Bacteroidetes" "Bacteroidetes"
#> Genus
#> Actinomycetaceae "Actinomycetaceae"
#> Aerococcus "Aerococcus"
#> Aeromonas "Aeromonas"
#> Akkermansia "Akkermansia"
#> Alcaligenes faecalis et rel. "Alcaligenes faecalis et rel."
#> Allistipes et rel. "Allistipes et rel."
samdat_tbl(psx)
#> # A tibble: 222 × 9
#> .sample_name subject sex nationality group sample timepoint
#> <chr> <fct> <fct> <fct> <fct> <chr> <int>
#> 1 Sample-1 byn male AAM DI Sample-1 4
#> 2 Sample-2 nms male AFR HE Sample-2 2
#> 3 Sample-3 olt male AFR HE Sample-3 2
#> 4 Sample-4 pku female AFR HE Sample-4 2
#> 5 Sample-5 qjy female AFR HE Sample-5 2
#> 6 Sample-6 riv female AFR HE Sample-6 2
#> 7 Sample-7 shj female AFR HE Sample-7 2
#> 8 Sample-8 tgx male AFR HE Sample-8 2
#> 9 Sample-9 ufm male AFR HE Sample-9 2
#> 10 Sample-10 nms male AFR HE Sample-10 3
#> # ℹ 212 more rows
#> # ℹ 2 more variables: timepoint.within.group <int>, bmi_group <fct>
samdat_tbl(psx, sample_names_col = "SAMPLENAME")
#> # A tibble: 222 × 9
#> SAMPLENAME subject sex nationality group sample timepoint
#> <chr> <fct> <fct> <fct> <fct> <chr> <int>
#> 1 Sample-1 byn male AAM DI Sample-1 4
#> 2 Sample-2 nms male AFR HE Sample-2 2
#> 3 Sample-3 olt male AFR HE Sample-3 2
#> 4 Sample-4 pku female AFR HE Sample-4 2
#> 5 Sample-5 qjy female AFR HE Sample-5 2
#> 6 Sample-6 riv female AFR HE Sample-6 2
#> 7 Sample-7 shj female AFR HE Sample-7 2
#> 8 Sample-8 tgx male AFR HE Sample-8 2
#> 9 Sample-9 ufm male AFR HE Sample-9 2
#> 10 Sample-10 nms male AFR HE Sample-10 3
#> # ℹ 212 more rows
#> # ℹ 2 more variables: timepoint.within.group <int>, bmi_group <fct>