Compute the number of sequence to obtain a given proportion of ASV in accumulation curves

Note that as most bioinformatic pipeline discard singleton, accumulation curves from metabarcoding cannot be interpreted in the same way as with conventional biodiversity sampling techniques.

Usage

accu_samp_threshold(res_accuplot, threshold = 0.95)

Arguments

res_accuplot

the result of the function accu_plot()

threshold

the proportion of ASV to obtain in each samples

Value

a value for each sample of the number of sequences needed to obtain threshold proportion of the ASV

See also

accu_plot()

Author

Adrien Taudière

Examples

# \donttest{
data("GlobalPatterns", package = "phyloseq")
GP <- subset_taxa(GlobalPatterns, GlobalPatterns@tax_table[, 1] == "Archaea")
#> Found more than one class "phylo" in cache; using the first, from namespace 'phyloseq'
#> Also defined by ‘RNeXML’
#> Found more than one class "phylo" in cache; using the first, from namespace 'phyloseq'
#> Also defined by ‘RNeXML’
#> Found more than one class "phylo" in cache; using the first, from namespace 'phyloseq'
#> Also defined by ‘RNeXML’
#> Found more than one class "phylo" in cache; using the first, from namespace 'phyloseq'
#> Also defined by ‘RNeXML’
GP <- rarefy_pq(subset_samples_pq(GP, sample_sums(GP) > 3000), replace = TRUE)
#> Found more than one class "phylo" in cache; using the first, from namespace 'phyloseq'
#> Also defined by ‘RNeXML’
#> Found more than one class "phylo" in cache; using the first, from namespace 'phyloseq'
#> Also defined by ‘RNeXML’
#> Found more than one class "phylo" in cache; using the first, from namespace 'phyloseq'
#> Also defined by ‘RNeXML’
#> Found more than one class "phylo" in cache; using the first, from namespace 'phyloseq'
#> Also defined by ‘RNeXML’
#> Found more than one class "phylo" in cache; using the first, from namespace 'phyloseq'
#> Also defined by ‘RNeXML’
p <- accu_plot(GP, "SampleType", add_nb_seq = TRUE, by.fact = TRUE, step = 10)

val_threshold <- accu_samp_threshold(p)

summary(val_threshold)
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#>    3551    6094    7261    7084    8251   10261 

##'  Plot the number of sequences needed to accumulate 0.95% of ASV in 50%, 75%
##'  and 100% of samples
p + geom_vline(xintercept = quantile(val_threshold, probs = c(0.50, 0.75, 1)))
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_ribbon()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_line()`).

# }