dacomp.generate_example_dataset_paired: Generate a simulated dataset for a paired study design.

In barakbri/dacomp: Non parametric differential abundance testing for microbiome counts data.

Description

The function generates a simulated data set for a paired study design. The first n rows correspond to ecosystems sampled, measured under condition 1. The next n rows correspond to the same ecosystems, measured under condition 2.

Usage

dacomp.generate_example_dataset_paired(
  n,
  m1 = 30,
  signal_strength_as_change_in_microbial_load = 0.1
)

Arguments

n	Number of ecosystems to sample. Actual number of samples will be twice this number.
m1	Number of differentially abundant taxa
signal_strength_as_change_in_microbial_load	A number in the range 0-0.75, indicating the fractional increase in the microbial load of a sample, when changing from condition 1 to condition 2.

Details

Data generation is similar to dacomp.generate_example_dataset.two_sample with the following difference: In the first step, samples for condition 1 are generated as in the two-sample function. In the second step, the frequencies of taxa (used for sampling in the previous step) are increased to simulate the changing condition. Samples under condition 2 are multinomial samples, generated using the modified frequency vectors.

Value

a list

• countsA counts matrix with (2 * n) rows, and 1384 columns, rows represent samples,columns represent taxa.

• select_diff_abundantA vector containing the indices of taxa that are differentially abundant.

• taxonomyA table for the taxonomic affiliation of OTUs in the simulated dataset.

References

Brill, Barak, Amnon Amir, and Ruth Heller. 2019. Testing for Differential Abundance in Compositional Counts Data, with Application to Microbiome Studies. arXiv Preprint arXiv:1904.08937.

Kostic, Aleksandar D, Dirk Gevers, Chandra Sekhar Pedamallu, Monia Michaud, Fujiko Duke, Ashlee M Earl, Akinyemi I Ojesina, et al. 2012. Genomic Analysis Identifies Association of Fusobacterium with Colorectal Carcinoma. Genome Research 22 (2). Cold Spring Harbor Lab: 292–98.

McMurdie, Paul J, and Susan Holmes. 2013. Phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PloS One 8 (4). Public Library of Science: e61217.

Examples

data = dacomp.generate_example_dataset_paired(30)

barakbri/dacomp documentation built on June 17, 2021, 11:20 p.m.