Manually set order of samples by specifying samples names in desired order.
ps_reorder(ps, sample_order)phyloseq
names or current numerical indices of samples in desired order
phyloseq
Ordering of samples in a phyloseq is controlled from the otu_table slot!
ps_arrange for arranging samples by sample_data variables (or otu_table)
ps_seriate for arranging samples by microbiome similarity
ps_filter for keeping only some samples, based on sample_data
library(phyloseq)
data("dietswap", package = "microbiome")
dietswap %>%
sample_data() %>%
head(8)
#> subject sex nationality group sample timepoint
#> Sample-1 byn male AAM DI Sample-1 4
#> Sample-2 nms male AFR HE Sample-2 2
#> Sample-3 olt male AFR HE Sample-3 2
#> Sample-4 pku female AFR HE Sample-4 2
#> Sample-5 qjy female AFR HE Sample-5 2
#> Sample-6 riv female AFR HE Sample-6 2
#> Sample-7 shj female AFR HE Sample-7 2
#> Sample-8 tgx male AFR HE Sample-8 2
#> timepoint.within.group bmi_group
#> Sample-1 1 obese
#> Sample-2 1 lean
#> Sample-3 1 overweight
#> Sample-4 1 obese
#> Sample-5 1 overweight
#> Sample-6 1 obese
#> Sample-7 1 obese
#> Sample-8 1 overweight
new_order <- rev(sample_names(dietswap))
dietswap %>%
ps_reorder(new_order) %>%
sample_data() %>%
head(8)
#> subject sex nationality group sample timepoint
#> Sample-222 ufm male AFR ED Sample-222 6
#> Sample-221 tgx male AFR ED Sample-221 6
#> Sample-220 shj female AFR ED Sample-220 6
#> Sample-219 riv female AFR ED Sample-219 6
#> Sample-218 qjy female AFR ED Sample-218 6
#> Sample-217 pku female AFR ED Sample-217 6
#> Sample-216 olt male AFR ED Sample-216 6
#> Sample-215 nms male AFR ED Sample-215 6
#> timepoint.within.group bmi_group
#> Sample-222 2 lean
#> Sample-221 2 overweight
#> Sample-220 2 obese
#> Sample-219 2 obese
#> Sample-218 2 overweight
#> Sample-217 2 obese
#> Sample-216 2 overweight
#> Sample-215 2 lean
# random ordering with numbers
set.seed(1000)
random_order <- sample(1:nsamples(dietswap))
dietswap %>%
ps_reorder(random_order) %>%
sample_data() %>%
head(8)
#> subject sex nationality group sample timepoint
#> Sample-68 cxj female AAM ED Sample-68 1
#> Sample-43 gty male AAM ED Sample-43 6
#> Sample-214 ufm male AFR ED Sample-214 1
#> Sample-51 dwc male AFR ED Sample-51 1
#> Sample-88 fud female AFR DI Sample-88 5
#> Sample-29 qjy female AFR DI Sample-29 5
#> Sample-99 fud female AFR HE Sample-99 3
#> Sample-61 azl female AFR ED Sample-61 1
#> timepoint.within.group bmi_group
#> Sample-68 1 overweight
#> Sample-43 2 overweight
#> Sample-214 1 lean
#> Sample-51 1 lean
#> Sample-88 2 obese
#> Sample-29 2 overweight
#> Sample-99 2 obese
#> Sample-61 1 obese