Package 'metaprotr'

Title: Metaproteomics Post-Processing Analysis
Description: Set of tools for descriptive analysis of metaproteomics data generated from high-throughput mass spectrometry instruments. These tools allow to cluster peptides and proteins abundance, expressed as spectral counts, and to manipulate them in groups of metaproteins. This information can be represented using multiple visualization functions to portray the global metaproteome landscape and to differentiate samples or conditions, in terms of abundance of metaproteins, taxonomic levels and/or functional annotation. The provided tools allow to implement flexible analytical pipelines that can be easily applied to studies interested in metaproteomics analysis.
Authors: Aaron Millan-Oropeza [aut, cre], Catherine Juste [aut, ctb], Ariane Bassignani [aut, ctb], Céline Henry [aut, ctb]
Maintainer: Aaron Millan-Oropeza <[email protected]>
License: GPL-3
Version: 1.2.2
Built: 2025-02-20 04:00:28 UTC
Source: https://github.com/cran/metaprotr

Help Index

add_kegg

Description

Integrates a database containing the functional annotation of the identified metaproteins into a list defined as "spectral_count_object". The proteins from the “spectral_count_object” must contain taxonomic information. The functional annotation was obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology database. This database contains the molecular functions represented in terms of functional orthologs (KO terms). Check KEGG for more details.

Usage

add_kegg(
  spectral_count_object,
  annotation_db,
  taxonomic_db,
  metaproteome_origin,
  protein_file,
  peptide_file,
  text_to_filter = "HUMAN",
  taxonomic_levels_allowed = 1
)

Arguments

spectral_count_object

List defined as "spectral_count_object" containing the abundance of the elements (groups, subgroups or peptides) expressed as spectral counts and organized by taxonomic levels. The format of this object is similar to that generated from the function "crumble_taxonomy".
annotation_db

Dataframe containing the functional annotation of the proteins. This dataframe must contain two variables: i) "gene_name": indicating the same protein names to those present in the variable "Accession" from the "peptides_proteins", third dataframe in the list defined as "spectral_count_object"; and, ii) "ko": indicating the KEGG Orthology code assigned to a given protein. An example can be found in this repository.
taxonomic_db

Dataframe containing the taxonomic information for each protein. The first column must contain the same identifiers of those present in the column "Accession" from the dataframe "peptides_proteins" of the "metaproteome_object". Two additional columns have to be present: i) one named "organism" containing the name of the strain assigned to a given protein; and ii) the other named "species.genus.family.order.class.phylum.superkingdom". The taxonomic classification can be obtained from a tool of sequences aligment and must be ordered as follows: species, genus, family, order, class, phylum and superkingdom. The characters inside must be concatenated by a comma without spaces (ex. "Streptococcus anginosus,Streptococcus,Streptococcaceae,Lactobacillales,Bacilli,Firmicutes,Bacteria"). An example can be found in this repository.
metaproteome_origin

List defined as "metaproteome_object" generated from the function 'load_protspeps'.
protein_file

Character indicating the location of a txt file containing the list of proteins generated in X!TandemPipeline using an adapted iterative approach described by Bassignani, 2019. Separation between columns should be indicated by tabulation. For more details regarding data input check format examples.
peptide_file

Character indicating the location of a txt file containing peptides abundances expressed as spectral counts. This file is generated from X!TandemPipeline using an adapted iterative approach described by Bassignani, 2019. Separation between columns should be indicated by tabulation. For more details regarding data input check format examples.
text_to_filter

Character containig a part of text to be searched in the "Description" of the protein file. All the elements containing this character will be removed. The default value was set to "HUMAN".
taxonomic_levels_allowed

Numeric value indicating the maximal number of taxonomic levels allowed per spectral group or subgroup (in function of the type of spectral data). The default value is set to 1.

Value

A list defined as "spectral_count_object" with the functional annotation added to the identified proteins. A new column is added to the dataframe "peptides_proteins". Two quality control plot are also generated, one with the number of taxonomic entities per spectral level and another with the number of KO terms per spectral level.

Examples

## Not run: 

# Download functional and taxonmical annotation db: https://zenodo.org/record/3997093#.X0UYI6Zb_mE 
meta99_full_taxo <- read.csv2("full_taxonomy_MetaHIT99.tsv", header= TRUE, sep="\t")
kegg_db <- read.csv2("hs_9_9_igc_vs_kegg89.table", header = TRUE, sep = "\t")

# Files with spectral abundance and proteins list from X!Tandempipeline
protein_file <- "your/specific/location/protein_list.txt"
peptide_file <- "your/specific/location/peptide_counting.txt"
metadata_file <- "your/location/metadata.csv"

metaproteome_origin <- load_protspeps(protein_file, peptide_file, metadata_file)

SCsgp_species <- crumble_taxonomy(SC_subgroups, "species")

SCsgp_species_annot <- add_kegg(
  SCsgp_species, 
  kegg_db, 
  meta99_full_taxo, 
  metaproteome_origin, 
  protein_file, 
  peptide_file, 
  text_to_filter = "HUMAN"
)


## End(Not run)

add_taxonomy

Description

Integrates the database containing the taxonomic classification of the identified proteins in a "metaproteome_object". The taxonomic classification is previously obtained by aligment algorithms and must include seven taxonomic levels assigned to a given protein: species, genus, family, order, class, phylum and superkingdom

Usage

add_taxonomy(metaproteome_object, taxonomic_database)

Arguments

metaproteome_object

List defined as "metaproteome_object" containing proteins and peptides abundances. The format of this object is similar to that generated from the function "load_protspeps".
taxonomic_database

Dataframe containing the taxonomic information for each protein. The first column must contain the same identifiers of those present in the column "Accession" from the dataframe "peptides_proteins" of the "metaproteome_object". Two additional columns have to be present: i) one named "organism" containing the name of the strain assigned to a given protein; and ii) the other named "species.genus.family.order.class.phylum.superkingdom". The taxonomic classification can be obtained from a tool of sequences aligment and must be ordered as follows: species, genus, family, order, class, phylum and superkingdom. The characters inside must be concatenated by a comma (ex."Streptococcus anginosus,Streptococcus,Streptococcaceae,Lactobacillales,Bacilli,Firmicutes,Bacteria"). An example can be found in this repository.

Value

A "metaproteome_object", which is a list of six elements with format similar to that generated from the function "load_protspeps". An additional column containing the taxonomic annotation is added to the dataframe named "peptides_proteins".

Examples

## Not run: 

# Download taxonmical annotation db: https://zenodo.org/record/3997093#.X0UYI6Zb_mE 
meta99_full_taxo <- read.csv2("MetaHIT99_best_hit_taxo_complete.tsv", header = TRUE, sep="\t") 

# Files with spectral abundance and proteins list from X!Tandempipeline
protein_file <- "your/specific/location/protein_list.txt"
peptide_file <- "your/specific/location/peptide_counting.txt"
metadata_file <- "your/location/metadata.csv"

metaproteome <- load_protspeps(proteins_file, peptides_file, metadata_file)

metaproteome_taxo <- add_taxonomy(metaproteome, meta99_full_taxo) 


## End(Not run)

crumble_taxonomy

Description

Generates a list of four elements defined as "spectral_count_object" containing taxonomic classification. The first element is a dataset that contains the spectral counts abundance organized by a provided taxonomic level. The possible taxonomic levels are: species, genus, family, order, class, phylum or superkingdom.

Usage

crumble_taxonomy(spectral_count_object, taxonomic_level, filter_rate = 1)

Arguments

spectral_count_object

List defined as "spectral_count_object" containing dataframes with abundance expressed as spectral counts and organized by peptides, subgroups or groups. The format of this object is similar to that generated with the function "getsc_specific". Taxonomy must be added previously with "add_taxonomy" function.
taxonomic_level

Character indicating the taxonomic level to which the spectral abundance will be arranged in the samples of the "spectral_count_object". The possible options are: "species", "genus", "family", "order", "class", "phylum" or "superkingdom".
filter_rate

Numeric value between 0 and 1 that indicates the minimal rate of consensual annotation desired by the user within each level of the spectral category (subgroup or group). This rate is defined as the ratio between the number of the most frequent annotation entity ("species", "genus", "family", "order", "class", "phylum" or "superkingdom") divided by the total number of entities within each level of the spectral category under study (subgroup or group). The default value is set to 1, if 100 % of consensus is desired.

Value

A list of four elements defined as "spectral_count_object", the first element is a dataframe with abundance expressed as spectral counts of entities (peptides, subgroups or groups) organized by the provided taxonomic level. The second element is a dataframe that contains the experiment information. The third element is a dataframe containing the information of peptides with their associated proteins. And the fourth element is a character indicating the type of object generated.

Examples

data(fecal_waters)

superkingdom_fecalwaters <- crumble_taxonomy(fecal_waters, "superkingdom")

phylum_fecalwaters <- crumble_taxonomy(fecal_waters, "phylum")

class_fecalwaters <- crumble_taxonomy(fecal_waters, "class")

order_fecalwaters <- crumble_taxonomy(fecal_waters, "order")

family_fecalwaters <- crumble_taxonomy(fecal_waters, "family")

genus_fecalwaters <- crumble_taxonomy(fecal_waters, "genus")

species_fecalwaters <- crumble_taxonomy(fecal_waters, "species")

export_ipath3

Description

Exports the KEGG Orthology (KO) terms in the adapted format to be used in the tool iPATH3. The exported data is obtained from a "spectral_count_object" containing the functional annotation of the identified proteins from one condition or sample.

Usage

export_ipath3(
  spectral_count_object,
  type_export,
  target_variable,
  sample_condition,
  hexadecimal_color,
  taxonomic_levels = NULL,
  force = FALSE
)

Arguments

spectral_count_object

List defined as "spectral_count_object" containing protein abundance expressed as spectral counts by a taxonomic level. The functional annotation must be added to this object. The format of this object is similar to that generated from the function "add_kegg".
type_export

Character indicating the type of export to be used. The possible options are: i) "all" that selects all the KO terms from a given sample or a given condition; and, ii) "selection" that extracts the KO terms present in selected taxonomic entities (one or more).
target_variable

Character indicating the column name from metadata containing the condition or sample to be analyzed.
sample_condition

Atomic vector indicating the sample from which the functional information will be extracted.
hexadecimal_color

Character indicating the color to be used in iPATH3, this value must be indicated in hexadecimal format (eg. #ff0000).
taxonomic_levels

Optional vector indicating the taxonomic levels from which the KO terms will be extracted. This option is needed only if the type of export is "selection".
force

Logic value set at FALSE by default in order to ask permission to create a file in the workstation of the user.

Value

A csv file containing the KO terms present in a given sample or condition. The content of this file can be inserted directly in the tool iPATH3. The width of the lines in iPATH3 will be displayed by the percentage of spectra in the selected sample or condition. In this way, KO terms belonging to a given taxonomic level are represented in three intervals based on their abundace: i) below 2 percent, i) between 2 to 10 percent, or i) above 10 percent.

Examples

data(species_annot_fw)

export_ipath3(
   species_annot_fw, 
   "all", 
   "SampleID", 
   "Q1_prot", 
   "#840AA3"
)

taxonomic_entities <- c("Bacteroides caccae", "Coprococcus catus", "Merdimonas faecis")
export_ipath3(
   species_annot_fw, 
   "selection", 
   "SC_name", 
   "FW2", 
   "#28c1df", 
   taxonomic_entities
)

export_robject

Description

Exports one of the dataframes present in a "metaproteome_object" or in "spectral_count_object". The export extensions can be RDATA or RDS.

Usage

export_robject(entry_object, data_exported, format_data, force = FALSE)

Arguments

entry_object

A "metaproteome_object" or a "spectral_count_object" with similar format to that generated with the functions "load_protspeps" or "getsc_specific", respectively.
data_exported

Character indicating the type of data to be exported from a "metaproteome_object" or a "spectral_count_object". The possible options are: i) "proteins", ii) "peptides", iii) "pepProts", iv) "spectral", v) "spectral_percent", vi) "metadata".
format_data

Character indicating the file extension, this can be either "RDATA" or "RDS".
force

Logic value set at FALSE by default in order to ask permission to create object in the workstation of the user.

Value

A file with the extension "RDATA" or "RDS" containing the information from the selected dataframe from a "metaproteome_object" or a "spectral_count_object".

Examples

data(fecal_waters)
export_robject(fecal_waters, "pepProts", "rdata")

data(species_fw)
export_robject(species_fw, "spectral", "rds")

export_vennlists

Description

Exports as csv files the elements (groups, subgroups, peptides or taxonomic levels) generated from the function "plot_venn".

Usage

export_vennlists(venn_lists_object, output_repo = NULL, force = FALSE)

Arguments

venn_lists_object

List defined as "venn_lists_object" containing the elements (peptides, subgroups, groups or taxonomic elements) generated with the function "plot_venn".
output_repo

Character indicating the path of a previously created directory where the lists will be exported. This parameter is optional.
force

Logic value set at FALSE by default in order to ask permission to create csv files in the workstation of the user.

Value

csv files containing the elements present on each logic section (specific and intersections) from the list defined as "venn_lists_object".

Examples

data(venn_methods)

export_vennlists(venn_methods)

fecal waters

Description

Data containing the abundance of 474 metaproteins expressed in spectral counts. Data generated from an Orbitrap Fusion Lumos Tribrid Mass Spectrometer. The dataset contains the metaproteomes from three extraction methods: i) "Q" for Qiagen, ii) "FW" for fecal waters, and iii) "Q_FW" for the mixture of Qiagen and fecal waters. Data generated in the context of the project Microbiome Rapid Access (Université Paris-Saclay).

Usage

data(fecal_waters)

Format

A list of four elements defined as "spectral_count_object", generated with the function "getsc_specific"

SC_subgroups

dataframe with 9 samples containing 474 subgroups or metaproteins with abundance expressed as spectral counts

metadata

information related to the 9 samples from the experiment

peptides_proteins

information related to each of the 1557 identified peptides

type_object

character indicating the type of object

filter_shared

Description

Keeps the elements from a "spectral_count_object" that are common to all levels of a provided explanatory variable. This variable MUST correspond to the name of ONE column of the dataframe "metadata" (eg. conditions or samples). This function allows to identify the elements that are common to several conditions or samples.

Usage

filter_shared(spectral_count_object, metadata_feature)

Arguments

spectral_count_object

List containing dataframes with proteomics elements whose abundance is expressed as spectral counts and are organized by peptides, subgroups, groups or taxonomic levels. The format of this object is similar to that generated from the functions "getsc_specific" and "crumble_taxonomy".
metadata_feature

Character indicating the name of one explanatory variable (ONE column name) of the dataframe "metadata".

Value

A list defined as "spectral_count_object" in which the elements (groups, subgroups, peptides or taxonomic levels) of a given variable (condition or samples) from metadata will have at least ONE spectra per variable.

Examples

data(fecal_waters)
data(species_fw)

common_elements_per_sample <- filter_shared(fecal_waters, "SampleID")

common_elements_per_condition <- filter_shared(species_fw, "Condition")

filter_text

Description

Matches the entities containing a given chain of characters inside an explanatory variable (column name) of the dataframe "peptides_proteins" from a "spectral_count_object". Based on the user's decision, the peptides, subgroups, groups or taxonomic levels containig the provided chain of characters will be kept or discarted in a newly generated object.

Usage

filter_text(spectral_count_object, pepsprots_feature, text_to_filter, decision)

Arguments

spectral_count_object

List containing dataframes with proteomics elements whose abundance is expressed as spectral counts and are organized by peptides, subgroups, groups or taxonomic levels. The format of this object is similar to that generated from the functions "getsc_specific" and "crumble_taxonomy".
pepsprots_feature

Character indicating the name of one explanatory variable (ONE column name) of the dataframe "peptides_proteins".
text_to_filter

Character containig the text to be searched in the "pepsprots_feature" content.
decision

Character indicating wether the elements containing the matched text will be kept or dirscarted. The two allowed option are: "keep" or "discard".

Value

A list defined as "spectral_count_object" with or without the elements (peptides, subgroups, groups, taxonomic items) that matched the provided text in a given variable of the "peptides_proteins" dataframe.

Examples

data(fecal_waters)
data(species_fw)

cysteine_alkylations <- filter_text(fecal_waters, "Modifs", "57.02146", "keep")

exclude_medimonas <- filter_text(species_fw, "organism", "Merdimonas faecis BR31", "discard")

filter_unshared

Description

Keeps the elements from a "spectral_count_object" that are specific to one level of a provided explanatory variable. This variable MUST correspond to the name of ONE column of the dataframe "metadata" (eg. conditions or samples). This function allows to identify the elements that are specific to one condition or one sample.

Usage

filter_unshared(spectral_count_object, metadata_feature)

Arguments

spectral_count_object

List containing dataframes with proteomics elements whose abundance is expressed as spectral counts and are organized by peptides, subgroups, groups or taxonomic levels. The format of this object is similar to that generated from the functions "getsc_specific" and "crumble_taxonomy".
metadata_feature

Character indicating the name of one explanatory variable (ONE column name) of the dataframe "metadata".

Value

A list defined as "spectral_count_object" with the specific elements per sample or condition, having at least one spectra.

Examples

data(fecal_waters)
data(species_fw)

specific_elements_per_sample <- filter_unshared(fecal_waters, "SampleID")

specific_elements_per_condition <- filter_unshared(species_fw, "Condition")

getsc_specific

Description

Returns the abundances, expressed as spectral counts (SC), of the different peptides, subgroups (also referred as metaprotein) or groups within the samples of the experiment. The abundance corresponds to the sum of SC of the specific peptides present in a given subgroup or group. See X!TandemPipeline for more details concerning the grouping algorithm.

Usage

getsc_specific(metaproteome_object, type_SCspecific)

Arguments

metaproteome_object

List defined as "metaproteome_object" with dataframes having a similar format to that generated from "load_protspeps" function. It contains metaproteomics data such as peptide and protein abundances and sample information.
type_SCspecific

Character indicating the type of data to be returned. The possible options are: i) "sc_specific_peptides" for peptides, or ii) "sc_groups" for groups, or iii) "sc_subgroups" for subgroups. For more details of the identification algorithm (peptides, subgroups, groups) check X!TandemPipeline.

Value

A list of four elements defined as "spectral_count_object". The first element is a dataframe organized in function of peptides OR subgroups (also referred as metaproteins) OR groups. The entities of this dataframe have their abundance expressed as SC from specific peptides. The second element is a dataframe of metadata containing the experiment information. The third element is a dataframe containing the information of peptides with their associated proteins. The fourth element is a character indicating the type of object generated.

Examples

## Not run: 

# From a given "metaproteome_object" add the taxonomic classification

metaproteome <- load_protspeps(proteins_file, peptides_file, metadata_file)
metaproteome_taxo <- add_taxonomy(metaproteome, meta99_full_taxo) 

# Organize proteomics data by peptides OR subgroups OR groups

SC_specific_peptides <- getsc_specific(metaproteome_taxo, 'sc_specific_peptides') 
SC_specific_groups <- getsc_specific(metaproteome_taxo, 'sc_groups') 
SC_specific_subgroups <- getsc_specific(metaproteome_taxo, 'sc_subgroups') 


## End(Not run)

identify_differences

Description

Shows the most differential taxonomic elements between two conditions or samples from a list defined as "spectral_count_object" with taxonomic classification. These elements are those with an absolute log2 (condition + 1 / reference + 1) > 3. If a given condition has several replicates the mean value is taken into account.

Usage

identify_differences(
  spectral_count_object,
  target_variable,
  list_conditions,
  filter_ratio = 3,
  force = FALSE
)

Arguments

spectral_count_object

List defined as "spectral_count_object" containing dataframes with abundance expressed as spectral counts and organized by taxonomic levels. The format of this object is similar to that generated from the function "crumble_taxonomy".
target_variable

Character indicating the variable name containing the conditions or samples to be compared. This value corresponds to the name of one column from metadata.
list_conditions

Atomic vector indicating two conditions to be compared. The first element will be considered as the reference.
filter_ratio

Numeric value indicating the fold change filter to be considered for the pairwise comparison. The minimal value can be a fold change of 1.25. The default value is set at 3.
force

Logic value set at FALSE by default in order to ask permission to create an object in the workstation of the user.

Value

Barplots (pdf) and a csv file with the defferential taxonomic elements between TWO conditions or sample. These elements are those that fulfill the ratio log2 (condition + 1 / reference + 1) > filter_ratio.

Examples

data(species_fw)
identify_differences(species_fw, "Methods", c("S", "S_EF"))

identify_differences(species_fw, "Methods", c("EF", "S_EF"), filter_ratio = 1.3)

inspect_sample_elements

Description

Displays a graph that indicates the number of common elements from a "spectral_count_object" (peptides, subgroups, groups or taxonomic entities) per sample. This function is useful to distinguish heterogeneity between samples in an experimental design.

Usage

inspect_sample_elements(spectral_count_object, force = FALSE)

Arguments

spectral_count_object

List defined as "spectral_count_object" containing dataframes with abundance expressed as spectral counts. The spectral data can be organized by peptides, subgroups, groups or taxonomic levels.
force

Logic value set at FALSE by default in order to ask permission to create a pdf file in the workstation of the user.

Value

Barplots (pdf) ilustrating the common spectral elements (peptides, subgroups, groups, taxonomic elements) per sample in a "spectral_count_object".

Examples

data(fecal_waters)
inspect_sample_elements(fecal_waters)

load_protspeps

Description

Loads three files: i) peptides abundances expressed as spectral counts, ii) proteins information, and iii) metadata of the mass spectrometry samples. Combines the three files into a "metaproteome_object", a list containing these dataframes.

Usage

load_protspeps(protein_file, peptide_file, metadata_file)

Arguments

protein_file

Character indicating the location of a txt file containing the list of proteins generated in X!TandemPipeline using an adapted iterative approach described by Bassignani, 2019. Separation between columns should be indicated by tabulation. For more details regarding data input check format examples.
peptide_file

Character indicating the location of a txt file containing peptides abundances expressed as spectral counts. This file is generated from X!TandemPipeline using an adapted iterative approach described by Bassignani, 2019. Separation between columns should be indicated by tabulation. For more details regarding data input check format examples.
metadata_file

Character indicating the location of a csv file containing the samples information. The following columns names MUST be present: "SC_name" (sample ids assigned by the user), "msrunfile" (name of samples as indicated in mass spectrometry files and in the columns of peptide_file) and "SampleID" (codes indicating the experimental group). Additional columns containing complementary information can be added by the user (ex. replicates, order of injection, etc.). Separation between columns should be indicated by tabulation. For more details regarding data input check format examples.

Value

A "metaproteome_object", which is a list of six elements containing: 1) dataframe of the protein identifiers, 2) dataframe of the peptide identifiers, 3) dataframe containing the information of peptides with their associated proteins, 4) dataframe of metadata containing the experiment information, 5) dataframe of spectral counts per peptide on each sample, 6) character indicating the type of object generated.

Examples

## Not run: 

protein_file <- "location/peptides_abundances.csv"
peptide_file <- "location/proteins_list.csv"
metadata <- "location/metadata.csv"
metaproteome <- load_protspeps(protein_file, peptide_file, metadata_file)


## End(Not run)

plot_dendocluster

Description

Draws a dendogram where samples are clustered based on the number of elements present on each sample from a "spectral_count_object". This graph is constructed based on Spearman correlations transformed into distances and plotted with the logic of the package dendextend.

Usage

plot_dendocluster(
  spectral_count_object,
  target_variable,
  file_title,
  hclust_method = "ward.D",
  correlation_method = "spearman",
  force = FALSE
)

Arguments

spectral_count_object

List defined as "spectral_count_object" containing dataframes with abundance expressed as spectral counts from peptides, subgroups, groups or taxonomic levels. The format of this object is similar to that generated from the functions "getsc_specific" and "crumble_taxonomy".
target_variable

Character indicating the name of one column from metadata. The different levels in this column will be represented as different colors in the final dendogram.
file_title

Character indicating the name of the generated file.
hclust_method

Character indicating the agglomeration method to be used for the hierarchical clustering. The possible methods are discribed on hclust. The default method is "ward.D".
correlation_method

Character indicating the correlation coeficient to be computed. The possible options are discribed in the function cor. The default value is "spearman".
force

Logic value set at FALSE by default in order to ask permission to create a pdf file in the workstation of the user.

Value

A dendogram plot (pdf) indicating the number of elements per sample.

Examples

data(fecal_waters)
str(fecal_waters$metadata)

plot_dendocluster(fecal_waters, "Condition", "title_dendogram")

plot_dendocluster(fecal_waters, "Condition", "title_dendogram", 
   hclust_method = "mcquitty")

plot_dendocluster(fecal_waters, "Condition", "title_dendogram_groups", 
   correlation_method = "pearson")

plot_fulltaxo

Description

Provides the number of taxonomic entities per sample in the different taxonomic levels. The taxonomic levels are: species, genus, family, order, class, phylum and superkingdom.

Usage

plot_fulltaxo(spectral_count_object, force = FALSE)

Arguments

spectral_count_object

List defined as "spectral_count_object" containing dataframes with format similar to that generated with the function "getsc_specific". This object contains abundances expressed as spectral counts from peptides, subgroups (metaproteins) or groups. Taxonomy must have previously been added with the function "add_taxonomy".
force

Logic value set at FALSE by default in order to ask permission to create a pdf and a csv file in the workstation of the user.

Value

Bar plots (pdf) and csv file with the number of taxonomic species, genus, family, order, class, phylum and superkingdom per sample. An additional csv file is generated providing the rate of assignment. The rate of assigment corresponds to the ratio between the number of the most frequent annotation ("species", "genus", "family", "order", "class", "phylum" or "superkingdom") and the total number of elements within each level of the spectral category under study (subgroup or group). The csv file is generated only when the "spectral_count_object" is organized by subgroup or by group.

Examples

data(fecal_waters)
plot_fulltaxo(fecal_waters)

plot_intensities

Description

Draws violin plots containing the abundance intensities expressed as spectral counts per level (peptides, subgroups, groups or taxonomic entities) in provided samples or conditions from a "spectral_count_object". If the provided conditions have several replicates the mean value is taken into account.

Usage

plot_intensities(
  spectral_count_object,
  target_variable,
  image_title = NULL,
  force = FALSE
)

Arguments

spectral_count_object

List defined as "spectral_count_object" containing dataframes with abundance expressed as spectral counts from peptides, subgroups, groups or taxonomic levels. The format of this object is similar to that generated from the functions "getsc_specific" and "crumble_taxonomy".
target_variable

Character indicating the name of one column from metadata, the column must contain the conditions to be displayed.
image_title

Character indicating the title to be displayed in the generated image.
force

Logic value set at FALSE by default in order to ask for permission to create a pdf file in the workstation of the user.

Value

Violin plots (pdf) indicating the spectral counts of the different levels (peptides, subgroups, groups or taxonomic entities) per sample or condition.

Examples

data(fecal_waters)
plot_intensities(fecal_waters, "SC_name", "Title to display inside the plot")

data(species_fw)
plot_intensities(species_fw, "Condition", "Abundance per condition")

plot_intensities_ratio

Description

Generates a scatter plot of the log2 (ratio + 1) between two conditions considering the spectral counts of each entity (peptides, subgroups, groups or taxonomic levels) from a "spectral_count_object". If a given condition has several replicates the mean value is taken into account.

Usage

plot_intensities_ratio(
  spectral_count_object,
  target_variable,
  list_conditions,
  force = FALSE
)

Arguments

spectral_count_object

List defined as "spectral_count_object" containing dataframes with abundance expressed as spectral counts organized by peptides, subgroups, groups or taxonomic levels. The format of this object is similar to that generated from the functions "getsc_specific" and "crumble_taxonomy".
target_variable

Character indicating the variable name containing the conditions to be compared. This value corresponds to the name of one column from metadata.
list_conditions

Atomic vector indicating two conditions to A be compared. The first element is considered as the reference (denominator) for ratio calculations.
force

Logic value set at FALSE by default in order to ask permission to create object in the workstation of the user.

Value

A scatter plot (pdf) indicating the log2 (ratio + 1) of the entities (peptides, soubgroups, groups, taxonomic) between the two conditions provided.

Examples

data(fecal_waters)

plot_intensities_ratio(fecal_waters, "Methods", c("EF", "S"))

plot_intensities_ratio(fecal_waters, "SC_name", c("Q1", "Q2"))

plot_pca

Description

Performs a Principal Components Analysis (PCA) from the spectral counts of the entities (peptides, subgroups, groups or taxonomic elements) in a "spectral_count_object" with or without taxonomy. PCA decomposition of high dimensional data allows to observe global effects in two dimensions. For more details of the used function check dudi.pca from ade4.

Usage

plot_pca(spectral_count_object, colors_var, pc_components, force = FALSE)

Arguments

spectral_count_object

List described as "spectral_count_object" containing dataframes with abundance expressed as spectral counts from peptides, subgroups, groups or taxonomic levels. The format of this object is similar to that generated from the functions "getsc_specific" and "crumble_taxonomy". The PCA projections will be applied to these observations.
colors_var

Character indicating the name of one column from metadata. The samples will be represented in different colors in function of the levels of this variable (ex. conditions).
pc_components

Two numeric values indicating two principal components to be analyzed.
force

Logic value set as FALSE by default in order to ask permission to create a file in the workstation of the user.

Value

A pdf file containing the results of PCA applied to the two provided principal components. Including a bar plot indicating the percentage of variance per principal component.

Examples

data(fecal_waters)
plot_pca(fecal_waters, "Methods", c(1, 2))

data(species_fw)
plot_pca(species_fw, "Methods", c(1, 3))

data(species_annot_fw)
plot_pca(species_annot_fw, "Condition", c(1, 2))

plot_pietaxo

Description

Generates a pie chart with taxonomic distribution of one selected sample or condition. If the provided condition has several replicates the mean value is taken into account.

Usage

plot_pietaxo(
  spectral_count_object,
  target_variable,
  sampling,
  filter_percent = 1,
  force = FALSE
)

Arguments

spectral_count_object

list defined as "spectral_count_object" containing dataframes with spectral counts abundance of the samples organized by taxonomy (species, genus, family, order, class, phylum or superkingdom). This object is generated with the function "crumble_taxonomy".
target_variable

Character indicating the name of one column from metadata. This column must contain the identifiers of the sample or condition to be plotted.
sampling

Character indicating the name of sample or condition to be plotted. This character must be present in the "target_variable".
filter_percent

Optional numeric value between 0 and 99 that sets the minimal percentage of spectral counts at which the taxonomic elements will be displayed. The elements whose values are lower than this number will be gathered and displayed as "others". The default value is set at 1.
force

Logic value set at FALSE by default in order to ask permission to create files in the workstation of the user.

Value

A pie chart (pdf) and a csv file with the taxonomic distribution of one sample or one condition. In the csv file, all the elements have their: a) spectral counts, b) percentage of spectral count in the sample, c) the taxonomic name and d) the taxonomic elements that were assiged as 'others' in function of the filter provided.

Examples

data(species_fw)

plot_pietaxo(species_fw, "Methods", "S")

plot_pietaxo(species_fw, "SC_name", "Q1")

plot_stackedtaxo

Description

Generates stacked barplots of the spectral counts distributions among the different taxonomic entities ("species", "genus", "family", "order", "class", "phylum" or "superkingdom") within the samples or conditions of a "spectral_count_object" with taxonomy. If the provided conditions have several replicates the mean value is taken into account.

Usage

plot_stackedtaxo(
  spectral_count_object,
  target_variable,
  bars_data,
  filter_percent = 1,
  force = FALSE
)

Arguments

spectral_count_object

List defined as "spectral_count_object" containing dataframes with spectral counts abundance organized by taxonomy (species, genus, family, order, class, phylum or superkingdom). This object is generated with the function "crumble_taxonomy".
target_variable

Character indicating the name of one column from metadata. The stacked barplots will be ordered by the levels of this variable.
bars_data

Character indicating the type of labels to be displayed in the stacked bars. The possible options are "percent" or "numbers".
filter_percent

Optional numeric value between 0 and 99 that sets the minimal percentage of spectral counts at which the taxonomic elements will be displayed. The elements whose values are lower than this number will be gathered and displayed as "others". The default value is set at 1.
force

Logic value set at FALSE by default in order to ask permission to create a pdf in the workstation of the user.

Value

Barplots (pdf) of the taxonomic distribution of the samples present in a "spectral_count_object" with taxonomic levels.

Examples

data(species_fw)

plot_stackedtaxo(species_fw, 'SampleID', 'percent', 2)

plot_stackedtaxo(species_fw, 'SC_name', 'numbers')

plot_venn

Description

Generates a Venn diagram comparing up to 3 conditions. The lists of elements for each condition are also returned as a "venn_lists_object".

Usage

plot_venn(
  spectral_count_object,
  target_variable,
  list_conditions,
  force = FALSE
)

Arguments

spectral_count_object

List defined as "spectral_count_object" containing dataframes with abundance expressed as spectral counts from peptides, subgroups, groups or taxonomic levels. The format of this object is similar to that generated from the functions "getsc_specific" and "crumble_taxonomy".
target_variable

Character indicating the name of the explanatory variable that contains the conditions to be compared. This value corresponds to the name of one column from the metadata dataframe.
list_conditions

Atomic vector indicating the conditions to be compared. The provided elements (2 or 3) must be present in the variable indicated as "target_variable".
force

Logic value set at FALSE by default in order to ask permission to create a pdf file in the workstation of the user.

Value

A Venn diagram (pdf) and a list defined as "venn_list_object" containing the elements (peptides, soubgroups, groups or taxonomic levels) for each logical section of the Venn diagram (specific and intersections).

Examples

data(fecal_waters)
venn_QFW1_Q1 <- plot_venn(fecal_waters, "SC_name", c("Q1_FW1", "Q1"))

data(species_fw)
venn_all <- plot_venn(species_fw, "Methods", c("S_EF", "S", "EF"))

remove_element

Description

Removes elements from a "spectral_count_object". These elements can be: i) samples, ii) peptides, iii) proteins, iv) soubgroups, v) groups, vi) sequences, vii) species, viii) genus, ix) family, x) order, xi) class, xii) phylum or xiii) superkingdom.

Usage

remove_element(spectral_count_object, target_variable, list_elements)

Arguments

spectral_count_object

List defined as "spectral_count_object" containing dataframes with abundance expressed as spectral counts from peptides, subgroups, groups or taxonomic levels. The format of this object is similar to that generated from the functions "getsc_specific" and "crumble_taxonomy."
target_variable

Character indicating the variable that contains the elements to be removed. The options are : i) "peptides", ii) "proteins", iii) "soubgroups", iv) "groups", v) "sequences", vi) "species", vii) "genus", viii) "family", ix) "order", x) "class", xi) "phylum" or xii) "superkingdom". To select xiii) "samples", it should be indicated the name of ONE column from metadata.
list_elements

Atomic vector indicating the elements to be removed. For "samples", indicate the element(s) present in the provided variable from metadata. For "peptides", "proteins", "subgroups" and "groups" provide the X!Tandem nomenclature. For "sequences", provide the peptide sequences expressed as aminoacids. For any taxonomic level, provide the taxonomic entities.

Value

A list defined as "spectral_count_object" without the elements provided in the second argument of the function.

Examples

data(fecal_waters)
data(species_fw)

data_selected_samples <- remove_element(fecal_waters, "Methods", c("S_EF", "EF"))

data_selected_peptides <- remove_element(fecal_waters, "peptides", c("pepa3c417", "pepd4664a1"))

data_selected_proteins <- remove_element(species_fw, "proteins", c("a3.a9.a1", "a5.b81.a1"))

data_selected_subgroups <- remove_element(species_fw, "subgroups", c("a3.a9", "b73.a5"))

data_selected_groups <- remove_element(species_fw, "groups", c("a3", "b34", "c231"))

data_selected_sequences <- remove_element(species_fw, "sequences", c("AQLNFGGTIENVVIRDEFPLEK"))

select_element

Description

Keeps specific elements from a "spectral_count_object". These elements can be: i) samples, ii) peptides, iii) proteins, iv) soubgroups, v) groups, vi) sequences, vii) species, viii) genus, ix) family, x) order, xi) class, xii) phylum or xiii) superkingdom.

Usage

select_element(spectral_count_object, target_variable, list_elements)

Arguments

spectral_count_object

List defined as "spectral_count_object" containing dataframes with abundance expressed as spectral counts from peptides, subgroups, groups or taxonomic levels. The format of this object is similar to that generated from the functions "getsc_specific" and "crumble_taxonomy."
target_variable

Character indicating the variable that contains the elements to be kept. The options are : i) "peptides", ii) "proteins", iii) "soubgroups", iv) "groups", v) "sequences", vi) "species", vii) "genus", viii) "family", ix) "order", x) "class", xi) "phylum" or xii) "superkingdom". To select xiii) "samples", it should be indicated the name of ONE column from metadata.
list_elements

Atomic vector indicating the elements to be kept For "samples", indicate the element(s) present in the provided variable from metadata. For "peptides", "proteins", "subgroups" and "groups" provide the X!Tandem nomenclature. For "sequences", provide the peptide sequences expressed as aminoacids. For any taxonomic level, provide the taxonomic entities.

Value

A list defined as "spectral_count_object" with the elements provided in the second argument of the function.

Examples

data(fecal_waters)
data(species_fw)

data_selected_samples <- select_element(fecal_waters, "Methods", c("S_EF", "EF"))

data_selected_peptides <- select_element(fecal_waters, "peptides", c("pepa3c417", "pepd4664a1"))

data_selected_proteins <- select_element(species_fw, "proteins", c("a3.a9.a1", "a5.b81.a1"))

data_selected_subgroups <- select_element(species_fw, "subgroups", c("a3.a9", "b73.a5"))

data_selected_groups <- select_element(species_fw, "groups", c("a3", "b34", "c231"))

data_selected_sequences <- select_element(species_fw, "sequences", c("AQLNFGGTIENVVIRDEFPLEK"))

species_annot_fw

Description

Data containing the abundance of 15 species expressed in spectral counts and with functional annotation. Data generated from an Orbitrap Fusion Lumos Tribrid Mass Spectrometer. The dataset contains the metaproteomes from three extraction methods: i) "Q" for Qiagen, ii) "FW" for fecal waters, and iii) "Q_FW" for the mixture of Qiagen and fecal waters. Data generated in the context of the project Microbiome Rapid Access (Université Paris-Saclay).

Usage

data(species_annot_fw)

Format

A list of four elements defined as "spectral_count_object" with functional annotation, generated with the function "add_kegg"

SC_subgroups

dataframe with 9 samples containing 15 especies with abundance expressed as spectral counts

metadata

information related to the 9 samples from the experiment

peptides_proteins

information related to each of the 1315 identified peptides

type_object

character indicating the type of object

species_fw

Description

Data containing the abundance of 17 species expressed in spectral counts. Data generated from an Orbitrap Fusion Lumos Tribrid Mass Spectrometer. The dataset contains the metaproteomes from three extraction methods: i) "Q" for Qiagen, ii) "FW" for fecal waters, and iii) "Q_FW" for the mixture of Qiagen and fecal waters. Data generated in the context of the project Microbiome Rapid Access (Université Paris-Saclay).

Usage

data(species_fw)

Format

A list of four elements defined as "spectral_count_object" with taxonomic annotation generated with the function "crumble_taxonomy"

SC_subgroups

dataframe with 9 samples containing 17 especies with abundance expressed as spectral counts

metadata

information related to the 9 samples from the experiment

peptides_proteins

information related to each of the 1557 identified peptides

type_object

character indicating the type of object

venn methods

Description

Data containing the subgroups for each logical section of the Venn diagram (specific and intersections) from two methods of extraction. The extraction methods are: i) "S" for Qiagen, and ii) "S_EF" for the mixture of Qiagen and fecal waters.

Usage

data(venn_methods)

Format

A list of six elements defined as "venn_lists_object", generated with the function "plot_venn"

S_EF

385 subgroups found in the method 'S_EF'

S

242 subgroups found the method 'S'

intersection

201 subgroups in common between the methods 'S' and 'S_EF'

Specific in S_EF

184 specific subgroups found in the method 'S_EF'

S

41 specific subgroups found in the method 'S'

type_object

character indicating the type of object