threshrankfun: A closure version of the 'threshrank' function.

In phyloseq: Handling and analysis of high-throughput microbiome census data

Description

Takes the same arguments as threshrank, except for x, because the output is a single-argument function rather than a rank-transformed numeric. This is useful for higher-order functions that require a single-argument function as input, like transform_sample_counts.

Usage

threshrankfun(thresh, keep0s=FALSE, ...)

Arguments

thresh	A single numeric value giving the threshold.
keep0s	A logical determining whether 0's in x should remain a zero-value in the output. If FALSE, zeros are treated as any other value.
...	Further arguments passes to the rank function.

Value

A single-argument function with the options to threshrank set.

See Also

transform_sample_counts, threshrankfun, threshrank

Examples

data(esophagus)
x1 = transform_sample_counts(esophagus, threshrankfun(50))
otu_table(x1)
x2 = transform_sample_counts(esophagus, rank)
otu_table(x2)
identical(x1, x2)

Example output

OTU Table:          [58 taxa and 3 samples]
                     taxa are rows
           B    C  D
59_8_22 57.0 55.0 53
59_5_13 50.0 50.0 50
59_8_12 50.0 53.0 50
65_3_22 50.0 50.0 50
65_5_1  50.0 50.0 50
65_1_10 50.0 50.0 50
65_7_12 50.5 50.0 55
59_6_1  50.0 50.0 50
65_2_17 53.0 50.0 50
65_9_26 50.0 50.0 50
65_5_18 50.0 50.0 50
65_7_5  50.0 50.0 50
65_8_12 50.0 50.0 50
65_9_1  50.0 50.0 50
59_9_26 50.0 50.0 50
9_6_28  50.0 50.0 50
65_7_4  50.0 50.0 50
65_4_26 50.0 50.0 50
9_2_24  50.0 50.0 50
65_1_17 50.0 50.0 50
65_6_7  50.0 50.0 50
9_4_3   50.0 50.0 50
65_7_18 50.0 50.0 50
65_8_7  50.0 50.0 50
59_4_5  50.0 50.0 50
59_5_2  50.0 50.0 50
65_6_2  50.0 54.0 52
65_4_10 50.0 50.0 50
9_7_25  52.0 50.0 50
9_4_5   50.0 50.0 50
65_1_8  50.0 50.0 50
65_2_5  50.0 50.0 50
59_7_6  56.0 56.5 57
59_9_31 54.0 50.0 50
9_1_7   50.0 50.0 50
9_4_13  50.0 50.0 50
9_6_3   50.0 50.0 50
65_4_5  50.0 50.0 50
59_9_18 50.5 50.0 50
65_9_13 50.0 50.0 50
65_3_18 50.0 50.0 50
65_6_10 50.0 50.0 50
9_7_18  50.0 50.0 50
65_8_25 50.0 50.0 50
59_3_5  50.0 50.0 50
65_8_29 50.0 50.0 50
65_4_20 50.0 50.0 50
59_6_11 50.0 50.0 50
59_9_17 50.0 50.0 54
9_4_6   50.0 50.0 50
59_4_25 50.0 52.0 50
59_3_21 50.0 51.0 50
59_3_19 50.0 50.0 50
59_4_16 50.0 50.0 50
59_8_3  50.0 50.0 50
59_5_19 55.0 58.0 56
65_9_9  50.0 50.0 50
59_2_6  58.0 56.5 58
OTU Table:          [58 taxa and 3 samples]
                     taxa are rows
           B    C    D
59_8_22 57.0 55.0 53.0
59_5_13 15.5 38.0 10.5
59_8_12 46.5 53.0 10.5
65_3_22 15.5 38.0 31.5
65_5_1  15.5 13.0 31.5
65_1_10 15.5 13.0 31.5
65_7_12 50.5 38.0 55.0
59_6_1  15.5 30.0 10.5
65_2_17 53.0 30.0 50.0
65_9_26 15.5 13.0 50.0
65_5_18 15.5 13.0 31.5
65_7_5  15.5 13.0 45.5
65_8_12 15.5 13.0 31.5
65_9_1  15.5 13.0 50.0
59_9_26 15.5 44.5 10.5
9_6_28  37.0 13.0 10.5
65_7_4  37.0 47.0 31.5
65_4_26 15.5 13.0 31.5
9_2_24  37.0 13.0 10.5
65_1_17 15.5 38.0 31.5
65_6_7  15.5 13.0 31.5
9_4_3   37.0 13.0 10.5
65_7_18 15.5 13.0 31.5
65_8_7  46.5 13.0 31.5
59_4_5  15.5 42.0 10.5
59_5_2  37.0 48.0 45.5
65_6_2  46.5 54.0 52.0
65_4_10 15.5 44.5 31.5
9_7_25  52.0 13.0 45.5
9_4_5   46.5 13.0 31.5
65_1_8  15.5 30.0 31.5
65_2_5  37.0 38.0 31.5
59_7_6  56.0 56.5 57.0
59_9_31 54.0 49.5 31.5
9_1_7   37.0 13.0 10.5
9_4_13  37.0 13.0 10.5
9_6_3   46.5 13.0 10.5
65_4_5  15.5 13.0 31.5
59_9_18 50.5 44.5 10.5
65_9_13 15.5 38.0 45.5
65_3_18 37.0 49.5 31.5
65_6_10 15.5 13.0 31.5
9_7_18  37.0 13.0 10.5
65_8_25 37.0 13.0 31.5
59_3_5  15.5 30.0 10.5
65_8_29 15.5 13.0 45.5
65_4_20 15.5 13.0 31.5
59_6_11 15.5 30.0 10.5
59_9_17 37.0 30.0 54.0
9_4_6   46.5 38.0 45.5
59_4_25 37.0 52.0 10.5
59_3_21 15.5 51.0 10.5
59_3_19 15.5 30.0 10.5
59_4_16 15.5 30.0 10.5
59_8_3  15.5 44.5 10.5
59_5_19 55.0 58.0 56.0
65_9_9  15.5 30.0 31.5
59_2_6  58.0 56.5 58.0
[1] FALSE

phyloseq documentation built on Nov. 8, 2020, 6:41 p.m.