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 species and communities, including the prokaryotic 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 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$new(dataset = NULL)
Arguments
datasetthe object of microtable Class.
Returns
for_what: "prok" or "fungi" or NA, "prok" represent prokaryotes. "fungi" represent fungi. NA stand for unknown according to the Kingdom information.
In this case, if the user still want to use the function to identify species traits, please provide "prok" or "fungi" manually,
e.g. t1$for_what <- "prok".
Examples
data(dataset)
t1 <- trans_func$new(dataset = dataset)
Method cal_spe_func()
Identify traits of each feature by matching taxonomic assignments to functional database.
Usage
trans_func$cal_spe_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 trait 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 trait 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_spe_func stored in object.
Examples
\donttest{
t1$cal_spe_func(prok_database = "FAPROTAX")
}
Method cal_spe_func_perc()
Calculating the percentages of species with specific trait in communities.
The percentages of the taxa with specific trait can reflect corresponding functional potential in the community.
So this method is one representation of functional redundancy (FR) without the consideration of phylogenetic distance among taxa.
The FR is defined:
FR_{kj}^{unweighted} = \frac{N_{j}}{N_{k}}
FR_{kj}^{weighted} = \frac{\sum_{i=1}^{N_{j}} A_{i}}{\sum_{i=1}^{N_{k}} A_{i}}
where FR_{kj} denotes the FR for sample k and function j. N_{k} is the species number in sample k.
N_{j} is the number of species with function j in sample k.
A_{i} is the abundance (counts) of species i in sample k.
Usage
trans_func$cal_spe_func_perc(abundance_weighted = FALSE, perc = TRUE, dec = 2)
Arguments
abundance_weighteddefault FALSE; whether use abundance of taxa. If FALSE, calculate the functional population percentage.
If TRUE, calculate the functional individual percentage.
percdefault TRUE; whether to use percentages in the result. If TRUE, value is bounded between 0 and 100.
If FALSE, the result is relative proportion ('abundance_weighted = FALSE') or relative abundance ('abundance_weighted = TRUE') bounded between 0 and 1.
decdefault 2; remained decimal places.
Returns
res_spe_func_perc stored in the object.
Examples
\donttest{
t1$cal_spe_func_perc(abundance_weighted = TRUE)
}
Method show_prok_func()
Show the annotation information for a function of prokaryotes from FAPROTAX database.
Usage
trans_func$show_prok_func(use_func = NULL)
Arguments
use_funcdefault NULL; the function name.
Returns
None.
Examples
\donttest{
t1$show_prok_func(use_func = "methanotrophy")
}
Method trans_spe_func_perc()
Transform the res_spe_func_perc table to the long table format for the following visualization.
Also add the group information if the database has hierarchical groups.
Usage
trans_func$trans_spe_func_perc()
Returns
res_spe_func_perc_trans stored in the object.
Examples
\donttest{
t1$trans_spe_func_perc()
}
Method plot_spe_func_perc()
Plot the percentages of species with specific trait in communities.
Usage
trans_func$plot_spe_func_perc(
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_spe_func_perc()
}
Method cal_tax4fun()
Predict functional potential of communities using Tax4Fun package.
please cite: Tax4Fun: Predicting functional profiles from metagenomic 16S rRNA data. Bioinformatics, 31(17), 2882-2884, <doi:10.1093/bioinformatics/btv287>.
Note that this function requires a standard prefix in taxonomic table with double underlines (e.g. 'g__') .
Usage
trans_func$cal_tax4fun(keep_tem = FALSE, folderReferenceData = NULL)
Arguments
keep_temdefault FALSE; whether keep the intermediate file, that is, the feature table in local place.
folderReferenceDatadefault NULL; the folder, see Tax4Fun function in Tax4Fun package.
Returns
tax4fun_KO and tax4fun_path in object.
Method cal_tax4fun2()
Predict functional potential of communities with Tax4Fun2 method.
The function was adapted from the raw Tax4Fun2 package to make it compatible with the microtable object.
Pleas cite:
Tax4Fun2: prediction of habitat-specific functional profiles and functional redundancy based on 16S rRNA gene sequences. Environmental Microbiome 15, 11 (2020).
<doi:10.1186/s40793-020-00358-7>
Usage
trans_func$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$cal_tax4fun2_FRI()
}
Method print()
Print the trans_func object.
Usage
trans_func$print()
Method clone()
The objects of this class are cloneable with this method.
Usage
trans_func$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
Examples
## ------------------------------------------------
## Method `trans_func$new`
## ------------------------------------------------
data(dataset)
t1 <- trans_func$new(dataset = dataset)
## ------------------------------------------------
## Method `trans_func$cal_spe_func`
## ------------------------------------------------
t1$cal_spe_func(prok_database = "FAPROTAX")
## ------------------------------------------------
## Method `trans_func$cal_spe_func_perc`
## ------------------------------------------------
t1$cal_spe_func_perc(abundance_weighted = TRUE)
## ------------------------------------------------
## Method `trans_func$show_prok_func`
## ------------------------------------------------
t1$show_prok_func(use_func = "methanotrophy")
## ------------------------------------------------
## Method `trans_func$trans_spe_func_perc`
## ------------------------------------------------
t1$trans_spe_func_perc()
## ------------------------------------------------
## Method `trans_func$plot_spe_func_perc`
## ------------------------------------------------
t1$plot_spe_func_perc()
## ------------------------------------------------
## Method `trans_func$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$cal_tax4fun2_FRI()
## End(Not run)
microeco documentation built on Oct. 30, 2024, 9:12 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| trans_func | R Documentation |
Create trans_func object for functional prediction.
Description
This class is a wrapper for a series of functional prediction analysis on species and communities, including the prokaryotic trait prediction based on Louca et al. (2016) <doi:10.1126/science.aaf4507> and Lim et al. (2020) <10.1038/s41597-020-0516-5>, or fungal trait prediction based on Nguyen et al. (2016) <10.1016/j.funeco.2015.06.006> and Polme et al. (2020) <doi:10.1007/s13225-020-00466-2>; functional redundancy calculation and metabolic pathway abundance prediction Abhauer et al. (2015) <10.1093/bioinformatics/btv287>.
Active bindings
func_group_liststore and show the function group list
Methods
Public methods
Method new()
Create the trans_func object. This function can identify the data type for Prokaryotes or Fungi automatically.
Usage
trans_func$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$for_what <- "prok".
Examples
data(dataset) t1 <- trans_func$new(dataset = dataset)
Method cal_spe_func()
Identify traits of each feature by matching taxonomic assignments to functional database.
Usage
trans_func$cal_spe_func(
prok_database = c("FAPROTAX", "NJC19")[1],
fungi_database = c("FUNGuild", "FungalTraits")[1],
FUNGuild_confidence = c("Highly Probable", "Probable", "Possible")
)Arguments
prok_databasedefault "FAPROTAX";
"FAPROTAX"or"NJC19"; select a prokaryotic trait database:- 'FAPROTAX'
FAPROTAX; Reference: Louca et al. (2016). Decoupling function and taxonomy in the global ocean microbiome. Science, 353(6305), 1272. <doi:10.1126/science.aaf4507>
- 'NJC19'
NJC19: Lim et al. (2020). Large-scale metabolic interaction network of the mouse and human gut microbiota. Scientific Data, 7(1). <10.1038/s41597-020-0516-5>. Note that the matching in this database is performed at the species level, hence utilizing it demands a higher level of precision in regards to the assignments of species in the taxonomic information table.
fungi_databasedefault "FUNGuild";
"FUNGuild"or"FungalTraits"; select a fungal trait database:- 'FUNGuild'
Nguyen et al. (2016) FUNGuild: An open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecology, 20(1), 241-248, <doi:10.1016/j.funeco.2015.06.006>
- 'FungalTraits'
version: FungalTraits_1.2_ver_16Dec_2020V.1.2; Polme et al. FungalTraits: a user-friendly traits database of fungi and fungus-like stramenopiles. Fungal Diversity 105, 1-16 (2020). <doi:10.1007/s13225-020-00466-2>
FUNGuild_confidencedefault c("Highly Probable", "Probable", "Possible"). Selected 'confidenceRanking' when
fungi_database = "FUNGuild".
Returns
res_spe_func stored in object.
Examples
\donttest{
t1$cal_spe_func(prok_database = "FAPROTAX")
}
Method cal_spe_func_perc()
Calculating the percentages of species with specific trait in communities. The percentages of the taxa with specific trait can reflect corresponding functional potential in the community. So this method is one representation of functional redundancy (FR) without the consideration of phylogenetic distance among taxa. The FR is defined:
FR_{kj}^{unweighted} = \frac{N_{j}}{N_{k}}
FR_{kj}^{weighted} = \frac{\sum_{i=1}^{N_{j}} A_{i}}{\sum_{i=1}^{N_{k}} A_{i}}
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.
Usage
trans_func$cal_spe_func_perc(abundance_weighted = FALSE, perc = TRUE, dec = 2)
Arguments
abundance_weighteddefault FALSE; whether use abundance of taxa. If FALSE, calculate the functional population percentage. If TRUE, calculate the functional individual percentage.
percdefault TRUE; whether to use percentages in the result. If TRUE, value is bounded between 0 and 100. If FALSE, the result is relative proportion ('abundance_weighted = FALSE') or relative abundance ('abundance_weighted = TRUE') bounded between 0 and 1.
decdefault 2; remained decimal places.
Returns
res_spe_func_perc stored in the object.
Examples
\donttest{
t1$cal_spe_func_perc(abundance_weighted = TRUE)
}
Method show_prok_func()
Show the annotation information for a function of prokaryotes from FAPROTAX database.
Usage
trans_func$show_prok_func(use_func = NULL)
Arguments
use_funcdefault NULL; the function name.
Returns
None.
Examples
\donttest{
t1$show_prok_func(use_func = "methanotrophy")
}
Method trans_spe_func_perc()
Transform the res_spe_func_perc table to the long table format for the following visualization.
Also add the group information if the database has hierarchical groups.
Usage
trans_func$trans_spe_func_perc()
Returns
res_spe_func_perc_trans stored in the object.
Examples
\donttest{
t1$trans_spe_func_perc()
}
Method plot_spe_func_perc()
Plot the percentages of species with specific trait in communities.
Usage
trans_func$plot_spe_func_perc( add_facet = TRUE, order_x = NULL, color_gradient_low = "#00008B", color_gradient_high = "#9E0142" )
Arguments
add_facetdefault TRUE; whether use group names as the facets in the plot, see
trans_func$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$plot_spe_func_perc()
}
Method cal_tax4fun()
Predict functional potential of communities using Tax4Fun package.
please cite: Tax4Fun: Predicting functional profiles from metagenomic 16S rRNA data. Bioinformatics, 31(17), 2882-2884, <doi:10.1093/bioinformatics/btv287>.
Note that this function requires a standard prefix in taxonomic table with double underlines (e.g. 'g__') .
Usage
trans_func$cal_tax4fun(keep_tem = FALSE, folderReferenceData = NULL)
Arguments
keep_temdefault FALSE; whether keep the intermediate file, that is, the feature table in local place.
folderReferenceDatadefault NULL; the folder, see Tax4Fun function in Tax4Fun package.
Returns
tax4fun_KO and tax4fun_path in object.
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 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
deepWhether to make a deep clone.
Examples
## ------------------------------------------------
## Method `trans_func$new`
## ------------------------------------------------
data(dataset)
t1 <- trans_func$new(dataset = dataset)
## ------------------------------------------------
## Method `trans_func$cal_spe_func`
## ------------------------------------------------
t1$cal_spe_func(prok_database = "FAPROTAX")
## ------------------------------------------------
## Method `trans_func$cal_spe_func_perc`
## ------------------------------------------------
t1$cal_spe_func_perc(abundance_weighted = TRUE)
## ------------------------------------------------
## Method `trans_func$show_prok_func`
## ------------------------------------------------
t1$show_prok_func(use_func = "methanotrophy")
## ------------------------------------------------
## Method `trans_func$trans_spe_func_perc`
## ------------------------------------------------
t1$trans_spe_func_perc()
## ------------------------------------------------
## Method `trans_func$plot_spe_func_perc`
## ------------------------------------------------
t1$plot_spe_func_perc()
## ------------------------------------------------
## 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)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.