trans_func: Create 'trans_func' object for functional prediction.
In microeco: Microbial Community Ecology Data Analysis
trans_func R Documentation
Create trans_func object for functional prediction.
Description
This class is a wrapper for a series of functional prediction analysis on ASVs/OTUs/species and communities, including the prokaryotic function/trait prediction based on
Louca et al. (2016) <doi:10.1126/science.aaf4507> and Lim et al. (2020) <10.1038/s41597-020-0516-5>,
or fungal function/trait prediction based on Nguyen et al. (2016) <10.1016/j.funeco.2015.06.006> and Polme et al. (2020) <doi:10.1007/s13225-020-00466-2>;
functional redundancy calculation and metabolic pathway abundance prediction Abhauer et al. (2015) <10.1093/bioinformatics/btv287>.
Active bindings
func_group_liststore and show the function group list
Methods
Public methods
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Method new()
Create the trans_func object. This function can identify the data type for Prokaryotes or Fungi automatically.
Usage
trans_func$new(dataset = NULL)
Arguments
datasetthe object of microtable Class.
Returns
for_what: "prok" or "fungi" or NA, "prok" represent prokaryotes. "fungi" represent fungi. NA stand for unknown according to the Kingdom information.
In this case, if the user still want to use the function to identify species traits, please provide "prok" or "fungi" manually,
e.g. t1$for_what <- "prok".
Examples
\donttest{
data(dataset)
t1 <- trans_func$new(dataset = dataset)
}
Method cal_func()
Predict the functions or traits for each ASV/OTU/species by matching taxonomic assignments to functional database.
Usage
trans_func$cal_func(
prok_database = c("FAPROTAX", "NJC19")[1],
fungi_database = c("FUNGuild", "FungalTraits")[1],
FUNGuild_confidence = c("Highly Probable", "Probable", "Possible")
)
Arguments
prok_databasedefault "FAPROTAX"; "FAPROTAX" or "NJC19"; select a prokaryotic database:
- 'FAPROTAX'
FAPROTAX; Reference: Louca et al. (2016). Decoupling function and taxonomy in the global ocean microbiome.
Science, 353(6305), 1272. <doi:10.1126/science.aaf4507>
- 'NJC19'
NJC19: Lim et al. (2020). Large-scale metabolic interaction network of the mouse and human gut microbiota.
Scientific Data, 7(1). <10.1038/s41597-020-0516-5>.
Note that the matching in this database is performed at the species level,
hence utilizing it demands a higher level of precision in regards to the assignments of species in the taxonomic information table.
fungi_databasedefault "FUNGuild"; "FUNGuild" or "FungalTraits"; select a fungal database:
- 'FUNGuild'
Nguyen et al. (2016) FUNGuild: An open annotation tool for parsing fungal community datasets by ecological guild.
Fungal Ecology, 20(1), 241-248, <doi:10.1016/j.funeco.2015.06.006>
- 'FungalTraits'
version: FungalTraits_1.2_ver_16Dec_2020V.1.2; Polme et al.
FungalTraits: a user-friendly traits database of fungi and fungus-like stramenopiles.
Fungal Diversity 105, 1-16 (2020). <doi:10.1007/s13225-020-00466-2>
FUNGuild_confidencedefault c("Highly Probable", "Probable", "Possible").
Selected 'confidenceRanking' when fungi_database = "FUNGuild".
Returns
res_func stored in the object.
Examples
\donttest{
t1$cal_func(prok_database = "FAPROTAX")
}
Method cal_func_FR()
Calculating the functional redundancy (FR) of communities for each function/trait.
For each sample and each function/trait, there will be a FR value in the result table.
The FR is defined:
FR_{kj}^{unweighted} = \frac{N_{j}}{N_{k}} \cdot {AF}
FR_{kj}^{weighted} = \frac{\sum_{i=1}^{N_{j}} A_{i}}{\sum_{i=1}^{N_{k}} A_{i}} \cdot {AF}
where FR_{kj} denotes the FR for sample k and function j. N_{k} is the species number in sample k.
N_{j} is the number of species with function j in sample k.
A_{i} is the abundance (counts) of species i in sample k.
AF is adjustment factor based on taxonomic information, representing the taxonomic dispersion of ASVs/OTUs/Species. It is 1 when adj_tax = FALSE.
Please see the parameter adj_tax for detailed explanation.
Usage
trans_func$cal_func_FR(
abundance_weighted = FALSE,
adj_tax = FALSE,
adj_tax_by = "Genus",
perc = FALSE,
dec = 6,
remove_zero = TRUE
)
Arguments
abundance_weighteddefault FALSE; whether use abundance of ASVs/OTUs/species.
FALSE corresponds to FR_{kj}^{unweighted} in the formula.
TRUE corresponds to FR_{kj}^{weighted} in the formula.
adj_taxdefault FALSE;
Whether the adjustment factor (AF) is used.
The default FALSE represents the AF is 1, meaning no adjustment is made based on the taxonomic distribution.
The principle behind the calculation of the adjustment factor is that species with a certain function that are more dispersed taxonomically usually correspond to higher redundancy.
It is defined:
AF = \frac{NU_{jk}}{NU_{k}}
where NU_{jk} denotes the number of unique taxon (at adj_tax_by level) for those ASVs/OTUs/species with function j in sample k.
NU_{k} denotes the number of total unique taxon (at adj_tax_by level) in sample k.
Please use the parameter adj_tax_by to select other taxonomic rank (default Genus level).
Here is an example: Suppose a sample k contains a total of 10 genera (including unclassified ones in different lineages),
and 3 ASVs with function j are distributed among 2 genera. In this case, the AF would be \frac{2}{10}, which is 0.2.
adj_tax_bydefault "Genus"; When adj_tax = TRUE, at which taxonomic level is the adjustment factor (AF) calculated?
percdefault FALSE; whether to use percentages in the result.
The default value of FALSE means that the result is in the range of 0 to 1.
If it is TRUE, the result will be multiplied by 100, meaning the range will be from 0 to 100.
decdefault 6; remained decimal places in the result table.
remove_zerodefault TRUE; whether to remove the columns in which the sum equals 0.
Returns
res_func_FR stored in the object.
Examples
\donttest{
t1$cal_func_FR(abundance_weighted = TRUE)
}
Method trans_func_FR()
Transform the res_func_FR table to the long table format for the following visualization.
Also add the group information if the database has hierarchical groups.
Usage
trans_func$trans_func_FR()
Returns
res_func_FR_trans stored in the object.
Examples
\donttest{
t1$trans_func_FR()
}
Method plot_func_FR()
Plot the functional redundancy (FR) results generated by cal_func_FR and trans_func_FR.
Usage
trans_func$plot_func_FR(
add_facet = TRUE,
order_x = NULL,
color_gradient_low = "#00008B",
color_gradient_high = "#9E0142"
)
Arguments
add_facetdefault TRUE; whether use group names as the facets in the plot, see trans_func$func_group_list object.
order_xdefault NULL; character vector; to sort the x axis text; can be also used to select partial samples to show.
color_gradient_lowdefault "#00008B"; the color used as the low end in the color gradient.
color_gradient_highdefault "#9E0142"; the color used as the high end in the color gradient.
Returns
ggplot2.
Examples
\donttest{
t1$plot_func_FR()
}
Method cal_func_FR_comm()
Calculate the functional redundancy (FR) of communities based on the the result of cal_func_FR function.
It is the geometric mean of FR for each function/trait in a community.
It is defined:
FR_{k} = \sqrt[n]{FR_{k1} \times FR_{k2} \times \cdots \times FR_{kn}}
where FR_{k} denotes the FR at community level for sample k. FR_{kn} represents the FR of function n for sample k.
Usage
trans_func$cal_func_FR_comm()
Returns
vector.
Examples
\donttest{
t1$cal_func_FR_comm()
}
Method show_prok_func()
Show the annotation information for a function of prokaryotes from FAPROTAX database.
Usage
trans_func$show_prok_func(use_func = NULL)
Arguments
use_funcdefault NULL; the function name in FAPROTAX database.
Returns
none.
Examples
\donttest{
t1$show_prok_func(use_func = "methanotrophy")
}
Method cal_tax4fun2()
Predict functional potential of communities with Tax4Fun2 method.
The function was adapted from the raw Tax4Fun2 package to make it compatible with the microtable object.
Pleas cite:
Tax4Fun2: prediction of habitat-specific functional profiles and functional redundancy based on 16S rRNA gene sequences. Environmental Microbiome 15, 11 (2020).
<doi:10.1186/s40793-020-00358-7>
Usage
trans_func$cal_tax4fun2(
blast_tool_path = NULL,
path_to_reference_data = "Tax4Fun2_ReferenceData_v2",
path_to_temp_folder = NULL,
database_mode = "Ref99NR",
normalize_by_copy_number = T,
min_identity_to_reference = 97,
use_uproc = T,
num_threads = 1,
normalize_pathways = F
)
Arguments
blast_tool_pathdefault NULL; the folder path, e.g., ncbi-blast-2.5.0+/bin ; blast tools folder downloaded from
"ftp://ftp.ncbi.nlm.nih.gov/blast/executables/blast+" ; e.g., ncbi-blast-2.5.0+-x64-win64.tar.gz for windows system;
if blast_tool_path is NULL, search the tools in the environmental path variable.
path_to_reference_datadefault "Tax4Fun2_ReferenceData_v2"; the path that points to files used in the prediction;
The directory must contain the Ref99NR or Ref100NR folder;
download Ref99NR.zip from "https://cloudstor.aarnet.edu.au/plus/s/DkoZIyZpMNbrzSw/download" or
Ref100NR.zip from "https://cloudstor.aarnet.edu.au/plus/s/jIByczak9ZAFUB4/download".
path_to_temp_folderdefault NULL; The temporary folder to store the logfile, intermediate file and result files; if NULL,
use the default temporary in the computer system.
database_modedefault 'Ref99NR'; "Ref99NR" or "Ref100NR"; Ref99NR: 99% clustering reference database; Ref100NR: no clustering.
normalize_by_copy_numberdefault TRUE; whether normalize the result by the 16S rRNA copy number in the genomes.
min_identity_to_referencedefault 97; the sequences identity threshold used for finding the nearest species.
use_uprocdefault TRUE; whether use UProC to functionally anotate the genomes in the reference data.
num_threadsdefault 1; the threads used in the blastn.
normalize_pathwaysdefault FALSE; Different to Tax4Fun, when converting from KEGG functions to KEGG pathways,
Tax4Fun2 does not equally split KO gene abundances between pathways a functions is affiliated to. The full predicted abundance is affiliated to each pathway.
Use TRUE to split the abundances (default is FALSE).
Returns
res_tax4fun2_KO and res_tax4fun2_pathway in object.
Examples
\dontrun{
t1$cal_tax4fun2(blast_tool_path = "ncbi-blast-2.5.0+/bin",
path_to_reference_data = "Tax4Fun2_ReferenceData_v2")
}
Method cal_tax4fun2_FRI()
Calculate (multi-) functional redundancy index (FRI) of prokaryotic community with Tax4Fun2 method.
This function is used to calculating aFRI and rFRI use the intermediate files generated by the function cal_tax4fun2().
please also cite:
Tax4Fun2: prediction of habitat-specific functional profiles and functional redundancy based on 16S rRNA gene sequences.
Environmental Microbiome 15, 11 (2020). <doi:10.1186/s40793-020-00358-7>
Usage
trans_func$cal_tax4fun2_FRI()
Returns
res_tax4fun2_aFRI and res_tax4fun2_rFRI in object.
Examples
\dontrun{
t1$cal_tax4fun2_FRI()
}
Method cal_spe_func()
This is a deprecated function. Please use cal_func function instead.
Usage
trans_func$cal_spe_func(...)
Arguments
...paremeters pass to cal_func.
Method cal_spe_func_perc()
This is a deprecated function. Please use cal_func_FR function instead.
Usage
trans_func$cal_spe_func_perc(...)
Arguments
...paremeters pass to cal_func_FR.
Method trans_spe_func_perc()
This is a deprecated function. Please use trans_func_FR function instead.
Usage
trans_func$trans_spe_func_perc(...)
Arguments
...paremeters pass to trans_func_FR.
Method plot_spe_func_perc()
This is a deprecated function. Please use plot_func_FR function instead.
Usage
trans_func$plot_spe_func_perc(...)
Arguments
...paremeters pass to plot_func_FR.
Method clone()
The objects of this class are cloneable with this method.
Usage
trans_func$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
Examples
## ------------------------------------------------
## Method `trans_func$new`
## ------------------------------------------------
data(dataset)
t1 <- trans_func$new(dataset = dataset)
## ------------------------------------------------
## Method `trans_func$cal_func`
## ------------------------------------------------
t1$cal_func(prok_database = "FAPROTAX")
## ------------------------------------------------
## Method `trans_func$cal_func_FR`
## ------------------------------------------------
t1$cal_func_FR(abundance_weighted = TRUE)
## ------------------------------------------------
## Method `trans_func$trans_func_FR`
## ------------------------------------------------
t1$trans_func_FR()
## ------------------------------------------------
## Method `trans_func$plot_func_FR`
## ------------------------------------------------
t1$plot_func_FR()
## ------------------------------------------------
## Method `trans_func$cal_func_FR_comm`
## ------------------------------------------------
t1$cal_func_FR_comm()
## ------------------------------------------------
## Method `trans_func$show_prok_func`
## ------------------------------------------------
t1$show_prok_func(use_func = "methanotrophy")
## ------------------------------------------------
## Method `trans_func$cal_tax4fun2`
## ------------------------------------------------
## Not run:
t1$cal_tax4fun2(blast_tool_path = "ncbi-blast-2.5.0+/bin",
path_to_reference_data = "Tax4Fun2_ReferenceData_v2")
## End(Not run)
## ------------------------------------------------
## Method `trans_func$cal_tax4fun2_FRI`
## ------------------------------------------------
## Not run:
t1$cal_tax4fun2_FRI()
## End(Not run)
microeco documentation built on Oct. 20, 2026, 9:06 a.m.
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| trans_func | R Documentation |
Create trans_func object for functional prediction.
Description
This class is a wrapper for a series of functional prediction analysis on ASVs/OTUs/species and communities, including the prokaryotic function/trait prediction based on Louca et al. (2016) <doi:10.1126/science.aaf4507> and Lim et al. (2020) <10.1038/s41597-020-0516-5>, or fungal function/trait prediction based on Nguyen et al. (2016) <10.1016/j.funeco.2015.06.006> and Polme et al. (2020) <doi:10.1007/s13225-020-00466-2>; functional redundancy calculation and metabolic pathway abundance prediction Abhauer et al. (2015) <10.1093/bioinformatics/btv287>.
Active bindings
func_group_liststore and show the function group list
Methods
Public methods
Method new()
Create the trans_func object. This function can identify the data type for Prokaryotes or Fungi automatically.
Usage
trans_func$new(dataset = NULL)
Arguments
datasetthe object of
microtableClass.
Returns
for_what: "prok" or "fungi" or NA, "prok" represent prokaryotes. "fungi" represent fungi. NA stand for unknown according to the Kingdom information.
In this case, if the user still want to use the function to identify species traits, please provide "prok" or "fungi" manually,
e.g. t1$for_what <- "prok".
Examples
\donttest{
data(dataset)
t1 <- trans_func$new(dataset = dataset)
}
Method cal_func()
Predict the functions or traits for each ASV/OTU/species by matching taxonomic assignments to functional database.
Usage
trans_func$cal_func(
prok_database = c("FAPROTAX", "NJC19")[1],
fungi_database = c("FUNGuild", "FungalTraits")[1],
FUNGuild_confidence = c("Highly Probable", "Probable", "Possible")
)Arguments
prok_databasedefault "FAPROTAX";
"FAPROTAX"or"NJC19"; select a prokaryotic database:- 'FAPROTAX'
FAPROTAX; Reference: Louca et al. (2016). Decoupling function and taxonomy in the global ocean microbiome. Science, 353(6305), 1272. <doi:10.1126/science.aaf4507>
- 'NJC19'
NJC19: Lim et al. (2020). Large-scale metabolic interaction network of the mouse and human gut microbiota. Scientific Data, 7(1). <10.1038/s41597-020-0516-5>. Note that the matching in this database is performed at the species level, hence utilizing it demands a higher level of precision in regards to the assignments of species in the taxonomic information table.
fungi_databasedefault "FUNGuild";
"FUNGuild"or"FungalTraits"; select a fungal database:- 'FUNGuild'
Nguyen et al. (2016) FUNGuild: An open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecology, 20(1), 241-248, <doi:10.1016/j.funeco.2015.06.006>
- 'FungalTraits'
version: FungalTraits_1.2_ver_16Dec_2020V.1.2; Polme et al. FungalTraits: a user-friendly traits database of fungi and fungus-like stramenopiles. Fungal Diversity 105, 1-16 (2020). <doi:10.1007/s13225-020-00466-2>
FUNGuild_confidencedefault c("Highly Probable", "Probable", "Possible"). Selected 'confidenceRanking' when
fungi_database = "FUNGuild".
Returns
res_func stored in the object.
Examples
\donttest{
t1$cal_func(prok_database = "FAPROTAX")
}
Method cal_func_FR()
Calculating the functional redundancy (FR) of communities for each function/trait. For each sample and each function/trait, there will be a FR value in the result table. The FR is defined:
FR_{kj}^{unweighted} = \frac{N_{j}}{N_{k}} \cdot {AF}
FR_{kj}^{weighted} = \frac{\sum_{i=1}^{N_{j}} A_{i}}{\sum_{i=1}^{N_{k}} A_{i}} \cdot {AF}
where FR_{kj} denotes the FR for sample k and function j. N_{k} is the species number in sample k.
N_{j} is the number of species with function j in sample k.
A_{i} is the abundance (counts) of species i in sample k.
AF is adjustment factor based on taxonomic information, representing the taxonomic dispersion of ASVs/OTUs/Species. It is 1 when adj_tax = FALSE.
Please see the parameter adj_tax for detailed explanation.
Usage
trans_func$cal_func_FR( abundance_weighted = FALSE, adj_tax = FALSE, adj_tax_by = "Genus", perc = FALSE, dec = 6, remove_zero = TRUE )
Arguments
abundance_weighteddefault FALSE; whether use abundance of ASVs/OTUs/species.
FALSEcorresponds toFR_{kj}^{unweighted}in the formula.TRUEcorresponds toFR_{kj}^{weighted}in the formula.adj_taxdefault FALSE; Whether the adjustment factor (
AF) is used. The defaultFALSErepresents theAFis 1, meaning no adjustment is made based on the taxonomic distribution. The principle behind the calculation of the adjustment factor is that species with a certain function that are more dispersed taxonomically usually correspond to higher redundancy. It is defined:AF = \frac{NU_{jk}}{NU_{k}}where
NU_{jk}denotes the number of unique taxon (atadj_tax_bylevel) for those ASVs/OTUs/species with function j in sample k.NU_{k}denotes the number of total unique taxon (atadj_tax_bylevel) in sample k. Please use the parameteradj_tax_byto select other taxonomic rank (default Genus level). Here is an example: Suppose a sample k contains a total of 10 genera (including unclassified ones in different lineages), and 3 ASVs with function j are distributed among 2 genera. In this case, theAFwould be\frac{2}{10}, which is 0.2.adj_tax_bydefault "Genus"; When
adj_tax = TRUE, at which taxonomic level is the adjustment factor (AF) calculated?percdefault FALSE; whether to use percentages in the result. The default value of
FALSEmeans that the result is in the range of 0 to 1. If it isTRUE, the result will be multiplied by 100, meaning the range will be from 0 to 100.decdefault 6; remained decimal places in the result table.
remove_zerodefault TRUE; whether to remove the columns in which the sum equals 0.
Returns
res_func_FR stored in the object.
Examples
\donttest{
t1$cal_func_FR(abundance_weighted = TRUE)
}
Method trans_func_FR()
Transform the res_func_FR table to the long table format for the following visualization.
Also add the group information if the database has hierarchical groups.
Usage
trans_func$trans_func_FR()
Returns
res_func_FR_trans stored in the object.
Examples
\donttest{
t1$trans_func_FR()
}
Method plot_func_FR()
Plot the functional redundancy (FR) results generated by cal_func_FR and trans_func_FR.
Usage
trans_func$plot_func_FR( add_facet = TRUE, order_x = NULL, color_gradient_low = "#00008B", color_gradient_high = "#9E0142" )
Arguments
add_facetdefault TRUE; whether use group names as the facets in the plot, see
trans_func$func_group_listobject.order_xdefault NULL; character vector; to sort the x axis text; can be also used to select partial samples to show.
color_gradient_lowdefault "#00008B"; the color used as the low end in the color gradient.
color_gradient_highdefault "#9E0142"; the color used as the high end in the color gradient.
Returns
ggplot2.
Examples
\donttest{
t1$plot_func_FR()
}
Method cal_func_FR_comm()
Calculate the functional redundancy (FR) of communities based on the the result of cal_func_FR function.
It is the geometric mean of FR for each function/trait in a community.
It is defined:
FR_{k} = \sqrt[n]{FR_{k1} \times FR_{k2} \times \cdots \times FR_{kn}}
where FR_{k} denotes the FR at community level for sample k. FR_{kn} represents the FR of function n for sample k.
Usage
trans_func$cal_func_FR_comm()
Returns
vector.
Examples
\donttest{
t1$cal_func_FR_comm()
}
Method show_prok_func()
Show the annotation information for a function of prokaryotes from FAPROTAX database.
Usage
trans_func$show_prok_func(use_func = NULL)
Arguments
use_funcdefault NULL; the function name in FAPROTAX database.
Returns
none.
Examples
\donttest{
t1$show_prok_func(use_func = "methanotrophy")
}
Method cal_tax4fun2()
Predict functional potential of communities with Tax4Fun2 method. The function was adapted from the raw Tax4Fun2 package to make it compatible with the microtable object. Pleas cite: Tax4Fun2: prediction of habitat-specific functional profiles and functional redundancy based on 16S rRNA gene sequences. Environmental Microbiome 15, 11 (2020). <doi:10.1186/s40793-020-00358-7>
Usage
trans_func$cal_tax4fun2( blast_tool_path = NULL, path_to_reference_data = "Tax4Fun2_ReferenceData_v2", path_to_temp_folder = NULL, database_mode = "Ref99NR", normalize_by_copy_number = T, min_identity_to_reference = 97, use_uproc = T, num_threads = 1, normalize_pathways = F )
Arguments
blast_tool_pathdefault NULL; the folder path, e.g., ncbi-blast-2.5.0+/bin ; blast tools folder downloaded from "ftp://ftp.ncbi.nlm.nih.gov/blast/executables/blast+" ; e.g., ncbi-blast-2.5.0+-x64-win64.tar.gz for windows system; if blast_tool_path is NULL, search the tools in the environmental path variable.
path_to_reference_datadefault "Tax4Fun2_ReferenceData_v2"; the path that points to files used in the prediction; The directory must contain the Ref99NR or Ref100NR folder; download Ref99NR.zip from "https://cloudstor.aarnet.edu.au/plus/s/DkoZIyZpMNbrzSw/download" or Ref100NR.zip from "https://cloudstor.aarnet.edu.au/plus/s/jIByczak9ZAFUB4/download".
path_to_temp_folderdefault NULL; The temporary folder to store the logfile, intermediate file and result files; if NULL, use the default temporary in the computer system.
database_modedefault 'Ref99NR'; "Ref99NR" or "Ref100NR"; Ref99NR: 99% clustering reference database; Ref100NR: no clustering.
normalize_by_copy_numberdefault TRUE; whether normalize the result by the 16S rRNA copy number in the genomes.
min_identity_to_referencedefault 97; the sequences identity threshold used for finding the nearest species.
use_uprocdefault TRUE; whether use UProC to functionally anotate the genomes in the reference data.
num_threadsdefault 1; the threads used in the blastn.
normalize_pathwaysdefault FALSE; Different to Tax4Fun, when converting from KEGG functions to KEGG pathways, Tax4Fun2 does not equally split KO gene abundances between pathways a functions is affiliated to. The full predicted abundance is affiliated to each pathway. Use TRUE to split the abundances (default is FALSE).
Returns
res_tax4fun2_KO and res_tax4fun2_pathway in object.
Examples
\dontrun{
t1$cal_tax4fun2(blast_tool_path = "ncbi-blast-2.5.0+/bin",
path_to_reference_data = "Tax4Fun2_ReferenceData_v2")
}
Method cal_tax4fun2_FRI()
Calculate (multi-) functional redundancy index (FRI) of prokaryotic community with Tax4Fun2 method. This function is used to calculating aFRI and rFRI use the intermediate files generated by the function cal_tax4fun2(). please also cite: Tax4Fun2: prediction of habitat-specific functional profiles and functional redundancy based on 16S rRNA gene sequences. Environmental Microbiome 15, 11 (2020). <doi:10.1186/s40793-020-00358-7>
Usage
trans_func$cal_tax4fun2_FRI()
Returns
res_tax4fun2_aFRI and res_tax4fun2_rFRI in object.
Examples
\dontrun{
t1$cal_tax4fun2_FRI()
}
Method cal_spe_func()
This is a deprecated function. Please use cal_func function instead.
Usage
trans_func$cal_spe_func(...)
Arguments
...paremeters pass to
cal_func.
Method cal_spe_func_perc()
This is a deprecated function. Please use cal_func_FR function instead.
Usage
trans_func$cal_spe_func_perc(...)
Arguments
...paremeters pass to
cal_func_FR.
Method trans_spe_func_perc()
This is a deprecated function. Please use trans_func_FR function instead.
Usage
trans_func$trans_spe_func_perc(...)
Arguments
...paremeters pass to
trans_func_FR.
Method plot_spe_func_perc()
This is a deprecated function. Please use plot_func_FR function instead.
Usage
trans_func$plot_spe_func_perc(...)
Arguments
...paremeters pass to
plot_func_FR.
Method clone()
The objects of this class are cloneable with this method.
Usage
trans_func$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
Examples
## ------------------------------------------------
## Method `trans_func$new`
## ------------------------------------------------
data(dataset)
t1 <- trans_func$new(dataset = dataset)
## ------------------------------------------------
## Method `trans_func$cal_func`
## ------------------------------------------------
t1$cal_func(prok_database = "FAPROTAX")
## ------------------------------------------------
## Method `trans_func$cal_func_FR`
## ------------------------------------------------
t1$cal_func_FR(abundance_weighted = TRUE)
## ------------------------------------------------
## Method `trans_func$trans_func_FR`
## ------------------------------------------------
t1$trans_func_FR()
## ------------------------------------------------
## Method `trans_func$plot_func_FR`
## ------------------------------------------------
t1$plot_func_FR()
## ------------------------------------------------
## Method `trans_func$cal_func_FR_comm`
## ------------------------------------------------
t1$cal_func_FR_comm()
## ------------------------------------------------
## Method `trans_func$show_prok_func`
## ------------------------------------------------
t1$show_prok_func(use_func = "methanotrophy")
## ------------------------------------------------
## Method `trans_func$cal_tax4fun2`
## ------------------------------------------------
## Not run:
t1$cal_tax4fun2(blast_tool_path = "ncbi-blast-2.5.0+/bin",
path_to_reference_data = "Tax4Fun2_ReferenceData_v2")
## End(Not run)
## ------------------------------------------------
## Method `trans_func$cal_tax4fun2_FRI`
## ------------------------------------------------
## Not run:
t1$cal_tax4fun2_FRI()
## End(Not run)
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