microeco (version 0.3.1)

trans_func: Create trans_func object for functional analysis.

Description

This class is a wrapper for a series of functional analysis on species and communities, including the prokaryotes function identification based on Louca et al. (2016) <doi:10.1126/science.aaf4507> or fungi function identification based on Nguyen et al. (2016) <10.1016/j.funeco.2015.06.006>, functional redundancy calculation and metabolic pathway abundance prediction A<U+00DF>hauer et al. (2015) <10.1093/bioinformatics/btv287>.

Active bindings

func_group_list

store and show the function group list

Methods

Public methods

• trans_func$new()

• trans_func$cal_spe_func()

• trans_func$cal_spe_func_perc()

• trans_func$show_prok_func()

• trans_func$plot_spe_func_perc()

• trans_func$cal_FAPROTAX()

• trans_func$cal_tax4fun()

• trans_func$print()

• trans_func$clone()

Method new()

Usage

trans_func$new(dataset = NULL)

Arguments

dataset

the object of microtable Class.

Returns

for_what : "prok" or "fungi" or NA, "prok" represent prokaryotes. "fungi" represent fungi. NA represent not identified according to the Kingdom information, at this time, if you want to use the functions to identify species traits, you need provide "prok" or "fungi" manually, e.g. dataset$for_what <- "prok".

Examples

data(dataset)
t1 <- trans_func$new(dataset = dataset)

Method cal_spe_func()

Confirm traits of each OTU by matching the taxonomic assignments to the functional database; Prokaryotes: based on the FAPROTAX database, please also cite the original FAPROTAX paper: Louca, S., Parfrey, L. W., & Doebeli, M. (2016). Decoupling function and taxonomy in the global ocean microbiome. Science, 353(6305), 1272. <doi:10.1126/science.aaf4507>; Fungi, based on the FUNGuild database, please also cite: Nguyen, N. H., Song, Z., Bates, S. T., Branco, S., Tedersoo, L., Menke, J., <U+2026> Kennedy, P. G. (2016). FUNGuild: An open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecology, 20(1), 241<U+2013>248. <doi:10.1016/j.funeco.2015.06.006>

Usage

trans_func$cal_spe_func()

Returns

res_spe_func in object.

Examples

\donttest{
t1$cal_spe_func()
}

Method cal_spe_func_perc()

Calculating the percentages of species with specific trait in communities or modules. The percentages of the OTUs with specific trait can reflect the potential of the corresponding function in the community or the module in the network.

Usage

trans_func$cal_spe_func_perc(
  use_community = TRUE,
  node_type_table = NULL,
  abundance_weighted = FALSE
)

Arguments

use_community

default TRUE; whether calculate community; if FALSE, use module.

node_type_table

default NULL; If use_community FALSE; provide the node_type_table with the module information, such as the result of cal_node_type.

abundance_weighted

default FALSE; whether use abundance. If FALSE, calculate the functional population percentage. If TRUE, calculate the functional individual percentage.

Returns

res_spe_func_perc in object.

Examples

\donttest{
t1$cal_spe_func_perc(use_community = TRUE)
}

Method show_prok_func()

Show the basic information for a specific function of prokaryotes.

Usage

trans_func$show_prok_func(use_func = NULL)

Arguments

use_func

default NULL; the function name.

Returns

None.

Examples

\donttest{
t1$show_prok_func(use_func = "methanotrophy")
}

Method plot_spe_func_perc()

Plot the percentages of species with specific trait in communities or modules.

Usage

trans_func$plot_spe_func_perc(
  filter_func = NULL,
  use_group_list = TRUE,
  add_facet = TRUE,
  select_samples = NULL
)

Arguments

filter_func

default NULL; a vector of function names.

use_group_list

default TRUE; If TRUE, use default group list; If use personalized group list, first set trans_func$func_group_list object with a list of group names and functions.

add_facet

default TRUE; whether use group names as the facets in the plot, see trans_func$func_group_list object.

select_samples

default NULL; character vector, select partial samples to show

Returns

ggplot2.

Examples

\donttest{
t1$plot_spe_func_perc(use_group_list = TRUE)
}

Method cal_FAPROTAX()

Predict functional potential of communities using FAPROTAX. please also cite the original FAPROTAX paper: Louca, S., Parfrey, L. W., & Doebeli, M. (2016). Decoupling function and taxonomy in the global ocean microbiome. Science, 353(6305), 1272. <doi:10.1126/science.aaf4507>;

Usage

trans_func$cal_FAPROTAX(keep_tem = TRUE, Ref_folder = "./FAPROTAX_1.2.1")

Arguments

keep_tem

default FALSE; whether keep the intermediate file, that is, the otu_table_for_FAPROTAX.txt in local place.

Ref_folder

default "./FAPROTAX_1.2.1"; see http://www.loucalab.com/archive/FAPROTAX

Returns

res_FAPROTAX in object.

Method cal_tax4fun()

Predict functional potential of communities using tax4fun. please also cite: A<U+00DF>hauer, K. P., Wemheuer, B., Daniel, R., & Meinicke, P. (2015). Tax4Fun: Predicting functional profiles from metagenomic 16S rRNA data. Bioinformatics, 31(17), 2882<U+2013>2884. <doi:10.1093/bioinformatics/btv287>

Usage

trans_func$cal_tax4fun(keep_tem = FALSE, folderReferenceData = NULL)

Arguments

keep_tem

default FALSE; whether keep the intermediate file, that is, the otu table in local place.

folderReferenceData

default NULL; the folder, see http://tax4fun.gobics.de/ and Tax4Fun function in Tax4Fun package.

Returns

tax4fun_KO and tax4fun_path in object.

Method print()

Print the trans_func object.

Usage

trans_func$print()

Method clone()

The objects of this class are cloneable with this method.

Usage

trans_func$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

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

data(dataset)
t1 <- trans_func$new(dataset = dataset)

## ------------------------------------------------
## Method `trans_func$cal_spe_func`
## ------------------------------------------------

# }
# NOT RUN {
t1$cal_spe_func()
# }
# NOT RUN {
## ------------------------------------------------
## Method `trans_func$cal_spe_func_perc`
## ------------------------------------------------

# }
# NOT RUN {
t1$cal_spe_func_perc(use_community = TRUE)
# }
# NOT RUN {
## ------------------------------------------------
## Method `trans_func$show_prok_func`
## ------------------------------------------------

# }
# NOT RUN {
t1$show_prok_func(use_func = "methanotrophy")
# }
# NOT RUN {
## ------------------------------------------------
## Method `trans_func$plot_spe_func_perc`
## ------------------------------------------------

# }
# NOT RUN {
t1$plot_spe_func_perc(use_group_list = TRUE)
# }