microtable: Create microtable object to store and manage all the basic files.

Description

This class is a wrapper for a series of operations on the original files and the basic manipulations, including the microtable object creation, data reduction, data rarefaction based on Paul et al. (2013) <doi:10.1371/journal.pone.0061217>, taxa abundance calculation, alpha and beta diversity calculation based on the An et al. (2019) <doi:10.1016/j.geoderma.2018.09.035> and Lozupone et al. (2005) <doi:10.1128/AEM.71.12.8228<U+2013>8235.2005> and other basic operations.

Arguments

Format

microtable.

Methods

Public methods

Method `new()`

Usage

microtable$new(
  otu_table = NULL,
  sample_table = NULL,
  tax_table = NULL,
  phylo_tree = NULL
)

Arguments

otu_table: data.frame; default NULL; necessary; The species or OTU table, rows are species, cols are samples.

sample_table

data.frame; default NULL; The sample information table, rows are samples, cols are sample metadata.

tax_table

data.frame; default NULL; The taxonomic information table, rows are species, cols are taxonomic classes.

phylo_tree

phylo; default NULL; If provided, the phylogenetic tree can be used for some analysis, for example, phylogenetic diversity.

Returns

an object of class "microtable" with the following components:

sample_table: The sample information table.
otu_table: The OTU table.
tax_table: The taxonomic table.
phylo_tree: The phylogenetic tree
taxa_abund: default NULL; use cal_abund function to calculate
alpha_diversity: default NULL; use cal_alphadiv function to calculate
beta_diversity: default NULL; use cal_betadiv function to calculate

Examples

data(otu_table_16S)
data(taxonomy_table_16S)
data(sample_info_16S)
data(phylo_tree_16S)
dataset <- microtable$new(sample_table = sample_info_16S, otu_table = otu_table_16S, 
  tax_table = taxonomy_table_16S, phylo_tree = phylo_tree_16S)
# trim the dataset
dataset$tidy_dataset()

Method `print()`

Print the microtable object.

Usage

microtable$print()

Method `filter_pollution()`

Filter the taxa considered as pollution. This operation will remove any line of the tax_table containing any the word in taxa parameter regardless of word case.

Usage

microtable$filter_pollution(taxa = c("mitochondria", "chloroplast"))

Arguments

taxa: default: c("mitochondria", "chloroplast"); filter mitochondria and chloroplast, or others as needed.

Returns

None

Examples

dataset$filter_pollution(taxa = c("mitochondria", "chloroplast"))

Method `rarefy_samples()`

Rarefy communities to make all samples have same species number, modified from the rarefy_even_depth() in phyloseq package, see Paul et al. (2013) <doi:10.1371/journal.pone.0061217>.

Usage

microtable$rarefy_samples(sample.size = NULL, rngseed = 123, replace = TRUE)

Arguments

sample.size: default:NULL; the required species number, If not provided, use minimum number of all samples.

rngseed

random seed; default: 123.

replace

default: TRUE; see sample for the random sampling.

Returns

None; rarefied dataset.

Examples

\donttest{
dataset$rarefy_samples(sample.size = min(dataset$sample_sums()), replace = TRUE)
}

Method `tidy_dataset()`

Tidy the object of microtable Class. Trim the dataset to make OTUs and samples consistent across all files in the object.

Usage

microtable$tidy_dataset(main_data = TRUE)

Arguments

main_data: TRUE or FALSE, if TRUE, only basic files in microtable object is tidied, otherwise, all files, including taxa_abund, alpha_diversity and beta_diversity, are all trimed.

Returns

None, Object of microtable itself cleaned up.

Examples

dataset$tidy_dataset(main_data = TRUE)

Method `cal_abund()`

Calculate the taxonomic abundance at each taxonomic ranks.

Usage

microtable$cal_abund()

Returns

taxa_abund in object.

Examples

\donttest{
dataset$cal_abund()
}

Method `save_abund()`

Save taxonomic abundance to the computer local place.

Usage

microtable$save_abund(dirpath = "taxa_abund")

Arguments

dirpath: default "taxa_abund"; directory name to save the taxonomic abundance files.

Method `sample_sums()`

Sum the species number for each sample.

Usage

microtable$sample_sums()

Returns

species number of samples.

Examples

\donttest{
dataset$sample_sums()
}

Method `taxa_sums()`

Sum the species number for each taxa.

Usage

microtable$taxa_sums()

Returns

species number of taxa.

Examples

\donttest{
dataset$taxa_sums()
}

Method `sample_names()`

Sample names.

Usage

microtable$sample_names()

Returns

sample names.

Examples

\donttest{
dataset$sample_names()
}

Method `taxa_names()`

Taxa names.

Usage

microtable$taxa_names()

Returns

taxa names.

Examples

\donttest{
dataset$taxa_names()
}

Method `merge_samples()`

Merge samples according to specific group to generate a new microtable.

Usage

microtable$merge_samples(use_group)

Arguments

use_group: the group column in sample_table.

Returns

a new created merged microtable object.

Examples

\donttest{
dataset$merge_samples(use_group = "Group")
}

Method `merge_taxa()`

Merge taxa according to specific taxonomic rank to generate a new microtable.

Usage

microtable$merge_taxa(taxa = "Genus")

Arguments

taxa: the specific rank in tax_table.

Returns

a new created merged microtable object.

Examples

\donttest{
dataset$merge_taxa(taxa = "Genus")
}

Method `cal_alphadiv()`

Calculate alpha diversity in microtable Class.

Usage

microtable$cal_alphadiv(measures = NULL, PD = FALSE)

Arguments

measures: one or more indexes from "Observed", "Coverage", "Chao1", "ACE", "Shannon", "Simpson", "InvSimpson", "Fisher", "PD"; default NULL, using all those measures.

PD

TRUE or FALSE, whether phylogenetic tree should be calculated, default FALSE.

Returns

alpha_diversity stored in object.

Examples

\donttest{
dataset$cal_alphadiv(measures = NULL, PD = FALSE)
class(dataset$alpha_diversity)
}

Method `save_alphadiv()`

Save alpha diversity table to the computer.

Usage

microtable$save_alphadiv(dirpath = "alpha_diversity")

Arguments

dirpath: default "alpha_diversity"; directory name to save the alpha_diversity.csv file.

Method `cal_betadiv()`

Calculate beta diversity in microtable object, including Bray-Curtis, Jaccard, and UniFrac, see An et al. (2019) <doi:10.1016/j.geoderma.2018.09.035> and Lozupone et al. (2005) <doi:10.1128/AEM.71.12.8228<U+2013>8235.2005>.

Usage

microtable$cal_betadiv(unifrac = FALSE)

Arguments

unifrac: TRUE or FALSE, whether unifrac index should be calculated, default FALSE.

Returns

beta_diversity stored in object.

Examples

\donttest{
dataset$cal_betadiv(unifrac = FALSE)
class(dataset$beta_diversity)
}

Method `save_betadiv()`

Save beta diversity matrix to the computer.

Usage

microtable$save_betadiv(dirpath = "beta_diversity")

Arguments

dirpath: default "beta_diversity"; directory name to save the beta diversity matrix files.

Method `clone()`

The objects of this class are cloneable with this method.

Usage

microtable$clone(deep = FALSE)

Arguments

deep: Whether to make a deep clone.

Examples

Run this code

# NOT RUN {
## ------------------------------------------------
## Method `microtable$new`
## ------------------------------------------------

data(otu_table_16S)
data(taxonomy_table_16S)
data(sample_info_16S)
data(phylo_tree_16S)
dataset <- microtable$new(sample_table = sample_info_16S, otu_table = otu_table_16S, 
  tax_table = taxonomy_table_16S, phylo_tree = phylo_tree_16S)
# trim the dataset
dataset$tidy_dataset()

## ------------------------------------------------
## Method `microtable$filter_pollution`
## ------------------------------------------------

dataset$filter_pollution(taxa = c("mitochondria", "chloroplast"))

## ------------------------------------------------
## Method `microtable$rarefy_samples`
## ------------------------------------------------

# }
# NOT RUN {
dataset$rarefy_samples(sample.size = min(dataset$sample_sums()), replace = TRUE)
# }
# NOT RUN {
## ------------------------------------------------
## Method `microtable$tidy_dataset`
## ------------------------------------------------

dataset$tidy_dataset(main_data = TRUE)

## ------------------------------------------------
## Method `microtable$cal_abund`
## ------------------------------------------------

# }
# NOT RUN {
dataset$cal_abund()
# }
# NOT RUN {
## ------------------------------------------------
## Method `microtable$sample_sums`
## ------------------------------------------------

# }
# NOT RUN {
dataset$sample_sums()
# }
# NOT RUN {
## ------------------------------------------------
## Method `microtable$taxa_sums`
## ------------------------------------------------

# }
# NOT RUN {
dataset$taxa_sums()
# }
# NOT RUN {
## ------------------------------------------------
## Method `microtable$sample_names`
## ------------------------------------------------

# }
# NOT RUN {
dataset$sample_names()
# }
# NOT RUN {
## ------------------------------------------------
## Method `microtable$taxa_names`
## ------------------------------------------------

# }
# NOT RUN {
dataset$taxa_names()
# }
# NOT RUN {
## ------------------------------------------------
## Method `microtable$merge_samples`
## ------------------------------------------------

# }
# NOT RUN {
dataset$merge_samples(use_group = "Group")
# }
# NOT RUN {
## ------------------------------------------------
## Method `microtable$merge_taxa`
## ------------------------------------------------

# }
# NOT RUN {
dataset$merge_taxa(taxa = "Genus")
# }
# NOT RUN {
## ------------------------------------------------
## Method `microtable$cal_alphadiv`
## ------------------------------------------------

# }
# NOT RUN {
dataset$cal_alphadiv(measures = NULL, PD = FALSE)
class(dataset$alpha_diversity)
# }
# NOT RUN {
## ------------------------------------------------
## Method `microtable$cal_betadiv`
## ------------------------------------------------

# }
# NOT RUN {
dataset$cal_betadiv(unifrac = FALSE)
class(dataset$beta_diversity)
# }

Run the code above in your browser using DataLab

Description

Arguments

Format

Methods

Public methods

Method new()

Usage

Arguments

Returns

Examples

Method print()

Usage

Method filter_pollution()

Usage

Arguments

Returns

Examples

Method rarefy_samples()

Usage

Arguments

Returns

Examples

Method tidy_dataset()

Usage

Arguments

Returns

Examples

Method cal_abund()

Usage

Returns

Examples

Method save_abund()

Usage

Arguments

Method sample_sums()

Usage

Returns

Examples

Method taxa_sums()

Usage

Returns

Examples

Method sample_names()

Usage

Returns

Examples

Method taxa_names()

Usage

Returns

Examples

Method merge_samples()

Usage

Arguments

Returns

Examples

Method merge_taxa()

Usage

Arguments

Returns

Examples

Method cal_alphadiv()

Usage

Arguments

Returns

Examples

Method save_alphadiv()

Usage

Arguments

Method cal_betadiv()

Usage

Arguments

Returns

Examples

Method save_betadiv()

Usage

Arguments

Method clone()

Usage

Arguments

Examples

Method `new()`

Method `print()`

Method `filter_pollution()`

Method `rarefy_samples()`

Method `tidy_dataset()`

Method `cal_abund()`

Method `save_abund()`

Method `sample_sums()`

Method `taxa_sums()`

Method `sample_names()`

Method `taxa_names()`

Method `merge_samples()`

Method `merge_taxa()`

Method `cal_alphadiv()`

Method `save_alphadiv()`

Method `cal_betadiv()`

Method `save_betadiv()`

Method `clone()`