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

Data Engineering and BI courses are free this week!

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

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()`