Package 'dagLogo'

Add a custom coloring or grouping scheme.

Description

Add a custom coloring or grouping scheme for ungrouped or grouped amino acids as desired.

Usage

addScheme(
  color = vector("character"),
  symbol = vector("character"),
  group = NULL
)

Arguments

color	A named vector of character. This vector specifies different colors for visualizing the different amino acids or amino acid groups.
symbol	A named vector of character. This vector specifies the different symbols for visualizing the different amino acids or amino acid groups.
group	A list or NULL. If only coloring amino acids of similar property is desired, set group to NULL; otherwise group should be a list with same names as those of color and symbol.

Value

Add the custom coloring or grouping scheme to the environment cacheEnv.

Examples

## Add a grouping scheme based on the BLOSUM50 level 3 
color = c(LVIMC = "#33FF00", AGSTP = "#CCFF00",
         FYW = '#00FF66', EDNQKRH = "#FF0066")
symbol = c(LVIMC = "L", AGSTP = "A", FYW = "F", EDNQKRH = "E")
group = list(
   LVIMC = c("L", "V", "I", "M", "C"), 
   AGSTP = c("A", "G", "S", "T", "P"),
   FYW = c("F", "Y", "W"),
   EDNQKRH = c("E", "D", "N", "Q", "K", "R", "H"))
addScheme(color = color, symbol = symbol, group = group)

---

Get all predefined coloring and grouping schemes

Description

List all predefined coloring and grouping schemes stored in the environmetn 'cacheEnv'

Usage

availableSchemes()

Value

A vector of names of predefined coloring and grouping schemes stored in the environment 'cacheEnv'.

Author(s)

Haibo Liu

---

Build background models for DAU tests

Description

A method used to build background models for testing differential amino acid usage

Usage

buildBackgroundModel(
  dagPeptides,
  background = c("wholeProteome", "inputSet", "nonInputSet"),
  model = c("any", "anchored"),
  targetPosition = c("any", "Nterminus", "Cterminus"),
  uniqueSeq = FALSE,
  numSubsamples = 300L,
  rand.seed = 1,
  replacement = FALSE,
  testType = c("ztest", "fisher"),
  proteome
)

Arguments

dagPeptides	An object of dagPeptides-class containing peptide sequences as the input set.
background	A character vector with options: "wholeProteome", "inputSet", and "nonInputSet", indicating what set of peptide sequences should be considered to generate a background model.
model	A character vector with options: "any" and "anchored", indicating whether an anchoring position should be applied to generate a background model.
targetPosition	A character vector with options: "any", "Nterminus" and "Cterminus", indicating which part of protein sequences of choice should be used to generate a background model.
uniqueSeq	A logical vector indicating whether only unique peptide sequences are included in a background model for sampling.
numSubsamples	An integer, the number of random sampling.
rand.seed	An integer, the seed used to perform random sampling
replacement	A logical vector of length 1, indicating whether replacement is allowed for random sampling.
testType	A character vector of length 1. Available options are "ztest" and "fisher".
proteome	An object of Proteome, output of prepareProteome

Details

The background could be generated from wholeProteome, inputSet or nonInputSet. Case 1: If background ="wholeProteome" and model = "any": The background set is composed of randomly selected subsequences from the wholeProteome with each subsequence of the same length as input sequences.

Case 2: If background ="wholeProteome and model = "anchored": The background set is composed of randomly selected subsequences from the wholeProteome with each subsequence of same length as input sequences.Additionally, the amino acids at the anchoring positions must be the same amino acid as that defined in the dagPeptides object,such as "K" for lysine.

Case 3: If background ="inputSet" and model = "any": similar to Case 1, but the full length protein sequences matching the protein sequence IDs in the inputSet are used for build background model after excluding the subsequences specified in the inputSet from the full length sequences.

Case 4: If background ="inputSet" and model = "anchored": similar to Case 2, but the full-length protein sequences matching the protein sequence IDs in the inputSet are used for build background model after excluding the subsequences specified in the inputSet from the full length sequences.

Case 5: If background ="nonInputSet" and model = "any": The background set is composed of randomly selected subsequences from the wholeProteome, not including the sequences corresponding to the inpuSet sequencesm with each subsequence of same length as input sequences.

Case 6: If background ="nonInputSet" and model = "anchored": similar to Case 5, but the amino acids at the anchoring positions must be the same amino acid as that defined in the dagPeptides object, such as "K" for lysine.

Value

An object of dagBackground-class.

Author(s)

Jianhong Ou, Haibo Liu

Examples

dat <- unlist(read.delim(system.file(
                                   "extdata", "grB.txt", package = "dagLogo"),
                         header = FALSE, as.is = TRUE))
##prepare an object of Proteome Class from a fasta file
proteome <- prepareProteome(fasta = system.file("extdata",
                                                "HUMAN.fasta",
                                                package = "dagLogo"), 
                            species = "Homo sapiens")
                            
##prepare an object of dagPeptides Class
seq <- formatSequence(seq = dat, proteome = proteome, upstreamOffset = 14,
                     downstreamOffset = 15)
bg_fisher <- buildBackgroundModel(seq, background = "wholeProteome", 
                                  proteome = proteome, testType = "fisher")
bg_ztest <- buildBackgroundModel(seq, background = "wholeProteome",
                                   proteome = proteome, testType = "ztest")

---

clean up peptides

Description

clean up the input peptide subsequences. The function removes peptides which do NOT contain any anchoring amino acid. Adds peptide for each additional anchor in each peptide, and allows multiple anchoring amino acids.

Usage

cleanPeptides(dat, anchors)

Arguments

dat	input data. The input dat contains two columns 'symbol', protein ID, and 'peptides', peptide sequence.The anchoring amino acid must be in lower case.
anchors	A vector of character, anchoring amino acid must be in lower case.

Value

A data.frame with columns: 'symbol', 'peptides' and 'anchor'

Author(s)

Jianhong Ou, Julie Zhu

Examples

dat <- read.csv(system.file("extdata", "peptides2filter.csv", package="dagLogo"))
dat
dat.new <- cleanPeptides(dat, anchors = c("s", "t"))

---

retrieve color setting for logo visualization

Description

retrieve prepared color setting for logo

Usage

colorsets2(
  colorScheme = c("null", "classic", "charge", "chemistry", "hydrophobicity")
)

Arguments

colorScheme

A vector of length 1, the option could be 'null', 'charge', 'chemistry', 'classic' or 'hydrophobicity'

Value

A character vector of color scheme

Author(s)

Jianhong Ou

---

Class dagBackground.

Description

An S4 class to represent a background composed of a formatted, aligned peptides for dagLogo analysis.

Slots

background

A list of data frame, each of which represetns one subset of the background set. Within each n-by-1 dataframe is a the aligned peptides of same length.

numSubsamples

An integer. That is the length of the background list

testType

An character. The type of statistic testing for dagLogo analysis of differential usage of amino acids.

Author(s)

Jianhong Ou, Haibo Liu

---

Visualize daglogo using a heatmap.

Description

Using a heatmap to visualize results of testing differential amino acid usage.

Usage

dagHeatmap(testDAUresults, type = c("diff", "statistics"), ...)

Arguments

testDAUresults	An object of testDAUresults-class, which contains results of testing differential amino acid usage.
type	A character vector of length 1, the type of metrics to display on y-axis. The available options are "diff" and "statistics", which are differences in amino acid usage at each position between the inputSet and the backgroundSet, and the Z-scores or odds ratios when Z-test or Fisher's exact test is performed to test the differential usage of amino acid at each position between the two sets.
...	other parameters passed to thepheatmap function.

Value

The output from the pheatmap function.

Author(s)

Jianhong Ou, Haibo Liu

Examples

data("seq.example")
data("proteome.example")
bg <- buildBackgroundModel(seq.example, proteome=proteome.example, 
                           numSubsamples=10)
t0 <- testDAU(seq.example, bg)
dagHeatmap(testDAUresults = t0, type = "diff")

---

Create sequence logo.

Description

Create sequence logo for visualizing results of testing differential usage of amino acids.

Usage

dagLogo(
  testDAUresults,
  type = c("diff", "zscore"),
  pvalueCutoff = 0.05,
  groupingSymbol = getGroupingSymbol(testDAUresults@group),
  font = "Helvetica",
  fontface = "bold",
  fontsize = 8,
  title = NULL,
  legend = FALSE,
  labelRelativeToAnchor = FALSE,
  labels = NULL,
  alpha = 1,
  markers = list()
)

Arguments

testDAUresults	An object of testDAUresults-class, which cintains results of testing differential amino acid usage).
type	A character vector of length 1. Type of statistics to be displayed on y-axis. Available choices are "diff" or "zscore".
pvalueCutoff	A numeric vector of length 1. A cutoff of p-values.
groupingSymbol	A named character vector.
font	A character vector of length 1. Font type for displaying sequence Logo.
fontface	An integer, fontface of text for axis annotation and legends.
fontsize	An integer, fontsize of text for axis annotation and legends.
title	A character vector of length 1, main title for a plot.
legend	A logical vector of length 1, indicating whether to show the legend.
labelRelativeToAnchor	A logical vector of length 1, indicating whether x-axis label should be adjusted relative to the anchoring position.
labels	A character vector, x-axis labels.
alpha	Alpha channel for transparency of low affinity letters.
markers	A list of marker-class.

Value

A sequence Logo is plotted without returned values.

Author(s)

Jianhong Ou, Haibo Liu

Examples

data('seq.example') 
data('proteome.example')
bg <- buildBackgroundModel(seq.example, proteome=proteome.example, 
                           numSubsamples=10, testType = "ztest")
t0 <- testDAU(seq.example, bg)
t1 <- testDAU(dagPeptides = seq.example, dagBackground = bg, 
              groupingScheme = "hydrophobicity_KD")
t2 <- testDAU(dagPeptides = seq.example, dagBackground = bg, 
             groupingScheme = "charge_group")
t3 <- testDAU(dagPeptides = seq.example, dagBackground = bg, 
             groupingScheme = "chemistry_property_Mahler")
t4 <- testDAU(dagPeptides = seq.example, dagBackground = bg, 
              groupingScheme = "hydrophobicity_KD_group")
dagLogo(t0, markers = list(new("marker", type="rect", start=c(5, 8), 
                                gp=gpar(lty=3, fill=NA)),
                            new("marker", type="text", start=9, label="*", 
                                gp=gpar(col=3))))
dagLogo(t1, groupingSymbol = getGroupingSymbol(t1@group))
dagLogo(t2, groupingSymbol = getGroupingSymbol(t2@group))
dagLogo(t3, groupingSymbol = getGroupingSymbol(t3@group))
dagLogo(t4, groupingSymbol = getGroupingSymbol(t4@group))

---

Class dagPeptides. An S4 class to represent formatted, aligned peptides for dagLogo analysis.

Description

Class dagPeptides. An S4 class to represent formatted, aligned peptides for dagLogo analysis.

Slots

data

A data frame with column names: IDs, anchorAA, anchorPos, peptide and anchor.

peptides

A matrix of character, each element is a single-character symbol for a amino acid.

upstreamOffset

An integer, the upstream offset relative to the anchoring position.

downstreamOffset

An integer, the downstream offset relative to the anchoring position.

type

A character vector of length 1. Available options :"UniProt", and "fasta" if the dagPeptides object is generated using the function formatSequence, or "entrezgene" and "uniprotswissprot" if generated by the function fetchSequence.

Objects from the Class

Objects can be created by calls of the form

new("dagPeptides", data, peptides, upstreamOffset, downstreamOffset, type).

Author(s)

Jianhong Ou

---

An object of Proteome-class representing the Escherichia coli proteome.

Description

A dataset containing the E. coli proteome.

Usage

ecoli.proteome

Format

An object of Proteome-class for Escherichia coli proteome. The format is: A list with one data frame and an character.

*‘proteome': ’data.frame': 13780 obs. of 4 variables *‘type': ’character': "UniProt" *‘species': ’character': "Escherichia coli"

The format of proteome is *'ENTREZ_GENE': a character vector, records entrez gene id *'SEQUENCE': a character vector, peptide sequences *'ID': a character vector, Uniprot ID *'LEN': a character vector, length of peptides

Details

used as an example dataset

Annotation data obtained by:

library(UniProt.ws)

taxId(UniProt.ws) <- 562

proteome <- prepareProteome(UniProt.ws, species="Escherichia coli")

Source

http://www.uniprot.org/

Examples

data(ecoli.proteome)
 head(ecoli.proteome@proteome)
 ecoli.proteome@type

---

Fetch protein/peptide sequences and create a dagPeptides-class object.

Description

This function fetches protein/peptide sequences from a Biomart database or from a Proteome-class object based on protein/peptide IDs and create a dagPeptides-class object following restriction as specified by parameters: anchorAA or anchorPos, upstreamOffset and downstreamOffset.

Usage

fetchSequence(
  IDs,
  type = "entrezgene",
  anchorAA = NULL,
  anchorPos,
  mart,
  proteome,
  upstreamOffset,
  downstreamOffset
)

Arguments

IDs	A character vector containing protein/peptide IDs used to fetch sequences from a Biomart database or a Proteome-class object.
type	A character vector of length 1. The available options are "entrezgene" and "uniprotswissprot" if parameter mart is missing; otherwise it can be any type of IDs available in Biomart databases.
anchorAA	A character vector of length 1 or the same length as that of anchorPos, each element of which is a single letter symbol of amino acids, for example, "K" for lysine.
anchorPos	A character or numeric vector. Each element of which is (1) a single-letter symbol of amino acid followed by the position of the anchoring amino acid in the target peptide/protein sequence, for example, "K123" for lysine at position 123 or the position of the anchoring amino acid in the target peptide/protein sequence, for example, "123" for an amino acid at position 123; or (2) a vector of subsequences containing the anchoring AAs.
mart	A Biomart database name you want to connect to. Either of parameters mart or proteome should be provided.
proteome	An object of Proteome-class. Either of parameters mart or Proteome-class should be provided.
upstreamOffset	An integer, the upstream offset relative to the anchoring position.
downstreamOffset	An integer, the downstream offset relative to the anchoring position.

Value

An object of class dagPeptides-class

Examples

## Case 1: You have both positions of the anchoring AAs and the identifiers 
## of their enclosing peptide/protein sequences for fetching sequences using 
## the fetchSequence function via the Biomart.

if (interactive())
{
    try({
    mart <- useMart("ensembl")
    fly_mart <-
       useDataset(mart = mart, dataset = "dmelanogaster_gene_ensembl")
    dat <- read.csv(system.file("extdata", "dagLogoTestData.csv",
                           package = "dagLogo"))
    seq <- fetchSequence(
       IDs = as.character(dat$entrez_geneid),
       anchorPos = as.character(dat$NCBI_site),
       mart = fly_mart,
       upstreamOffset = 7,
       downstreamOffset = 7)
   head(seq@peptides)
   })
}


## Case 2: You don't have the exactly postion information, but You have the 
## interesting peptide subsequences and the identifiers of their enclosing 
## peptide/protein sequences for fetching sequences using the fetchSequence
## function via the Biomart. In the following examples, the anchoring AAs 
## are marked by asterisks. 
if (interactive())
{
    try({
        mart <- useMart("ensembl")
        fly_mart <-
            useDataset(mart = mart, dataset = "dmelanogaster_gene_ensembl")
        dat <- read.csv(system.file("extdata", "dagLogoTestData.csv",
                                    package = "dagLogo"))
        seq <- fetchSequence(
            IDs = as.character(dat$entrez_geneid),
            anchorAA = "*",
            anchorPos = as.character(dat$peptide),
            mart = fly_mart,
            upstreamOffset = 7,
            downstreamOffset = 7
        )
        head(seq@peptides)
    })
}

## In following example, the anchoring AAs are lower-case "s" for amino acid 
## serine.
if(interactive())
{
   try({
       dat <- read.csv(system.file("extdata", "peptides4dagLogo.csv",
                                   package = "dagLogo"))
        mart <- useMart("ensembl")
        human_mart <-
            useDataset(mart = mart, dataset = "hsapiens_gene_ensembl")
        seq <- fetchSequence(IDs = toupper(as.character(dat$symbol)),
                             type = "hgnc_symbol",
                             anchorAA = "s",
                             anchorPos = as.character(dat$peptides),
                             mart = human_mart,
                             upstreamOffset = 7,
                             downstreamOffset = 7)
        head(seq@peptides)
    })
}

---

Format already aligned peptide sequences.

Description

Convert already aligned peptide sequences into an object of dagPeptides-class.

Usage

formatSequence(seq, proteome, upstreamOffset, downstreamOffset)

Arguments

seq	A vector of aligned peptide sequences of the same length
proteome	An object of Proteome-class.
upstreamOffset	An integer, the upstream offset relative to the anchoring position.
downstreamOffset	An integer, the downstream offset relative to the anchoring position.

Value

An object of dagPeptides-class Class

Author(s)

Jianhong Ou, Haibo Liu

Examples

## Suppose you already have the aligned peptides sequences at hands. Then you can use 
## the formatSequence function to prepare an object of dagPeptides. Befor doing 
## that, you need prepare a Proteome object by the prepareProteome function.

dat <- unlist(read.delim(system.file(
                                   "extdata", "grB.txt", package = "dagLogo"),
                         header = FALSE, as.is = TRUE))
                         
## prepare an object of Proteome Class from a fasta file
proteome <- prepareProteome(fasta = system.file("extdata",
                                                "HUMAN.fasta",
                                                package = "dagLogo"), 
                            species = "Homo sapiens")
                            
## prepare an object of dagPeptides Class from a Proteome object
seq <- formatSequence(seq = dat, proteome = proteome, upstreamOffset = 14,
                     downstreamOffset = 15)

---

convert group name to a single character

Description

convert group name to a single character to shown in a logo

Usage

nameHash(nameScheme = c("classic", "charge", "chemistry", "hydrophobicity"))

Arguments

nameScheme

could be "classic", "charge", "chemistry", "hydrophobicity"

Value

A character vector of name scheme

Author(s)

Jianhong Ou

---

prepare proteome for background building

Description

prepare proteome from UniProt webserver or a fasta file

Usage

prepareProteome(source, fasta, species = "unknown", ...)

Arguments

source	An object of UniProt.ws or A character "UniProt".
fasta	fasta file name or an object of AAStringSet
species	an character to assign the species of the proteome
...	parameters could be passed to prepareProteomeByFTP.

Value

an object of Proteome which contain protein sequence information.

Author(s)

Jianhong Ou

See Also

formatSequence, buildBackgroundModel

Examples

if(interactive()){
   library(UniProt.ws)
   availableUniprotSpecies("Drosophila melanogaster")
   UniProt.ws <- UniProt.ws(taxId=7227)
   proteome <- prepareProteome(UniProt.ws, species="Drosophila melanogaster")
 }

---

Create an object of Proteome Class.

Description

Create an object of Proteome Class by downloading a whole proteome data from UniProt for a given organism of an NCBI taxonomy ID or species' scientific name, or by using peptide sequences in a fasta file.

Usage

prepareProteomeByFTP(
  source = "UniProt",
  taxonID = NULL,
  species = NULL,
  destDir = tempdir(check = TRUE),
  fastaFile,
  ...
)

Arguments

source	A character vector of length 1 or NULL. A database source from which the proteome sequences are to be downloaded. By default, currently it is "UniProt". If it is NULL, then fastaFile has to be specified. The priority of source is higher than fastaFile.
taxonID	An integer(1), specifying Taxonomy ID for a species of interest. Check the NCBI taxonomy database: https://www.ncbi.nlm.nih.gov/taxonomy or the UniProt database http://www.uniprot.org/taxonomy/. At least one of the two parameters, taxonID and species, should be specified. If both are specified, taxonID will be used preferentially.
species	A character vector of length 1. The Latin name of a species confirming to the Linnaean taxonomy nomenclature system. CAUTION: for species with different strains, attention should be paid. You can interactively choose the right taxonID from an output list.
destDir	A character vector of length 1. A destination directory with writing permission for saving downloaded sequences. Default is a temporary directory in the system's temporary directory.
fastaFile	A character vector of length 1. A fasta file name from which protein sequences are read in.
...	other parameters passing to the function download.file.

Value

An object of Proteome

Author(s)

Haibo Liu

Examples

## Not run: 
## Prepare an objecto of Proteome Class for a proteome from the UniProt database
#' proteome <- prepareProteomeByFTP(source = "UniProt", species = "Homo sapiens")

## End(Not run)
## Prepare an objecto of Proteome Class from a fasta file
fasta <- system.file("extdata", "HUMAN.fasta", package="dagLogo")
proteome <- prepareProteomeByFTP(source = NULL, species = "Homo sapiens", 
fastaFile=fasta)

---

Prepare a Proteome object for background building

Description

Create an object of Proteome Class by query the UniProt database of an organism of a given species' scientific name, or by using peptide sequences in a fasta file or in an AAStringSet object.

Usage

prepareProteomeByUniProtWS(UniProt.ws, fasta, species = "unknown")

Arguments

UniProt.ws	An object of UniProt.ws.
fasta	A fasta file name or an object of AAStringSet.
species	An character vector of length (1) to designate the species of the proteome

Value

An object of Proteome which contain protein sequence information.

Author(s)

Jianhong Ou

See Also

formatSequence, buildBackgroundModel

Examples

if(interactive()){
   library(UniProt.ws)
   availableUniprotSpecies("Drosophila melanogaster")
   UniProt.ws <- UniProt.ws(taxId=7227)
   proteome <- prepareProteomeByUniProtWS(UniProt.ws, species="Drosophila melanogaster")
 }

---

Class Proteome.

Description

An S4 class to represent a whole proteome for dagLogo analysis.

Slots

proteome

A data frame.

type

A character vector of length 1. Available options :"UniProt", and "fasta".

species

A character vector of length 1, such as a conventional Latin name for a species.

Objects from the Class

Objects can be created by calls of the form

new("Proteome", proteome, type, species).

Author(s)

Jianhong Ou

---

An object of Proteome-class representing the subset of Drosophila melanogaster proteome.

Description

The subset Proteome-class of fruit fly.

Usage

proteome.example

Format

An object of Proteome-class for fly subset proteome. The format is: A list with one data frame and an character.

*‘proteome': ’data.frame': 1406 obs. of 4 variables *‘type': ’character': "UniProt" *‘species': ’character': "Drosophila melanogaster"

The format of proteome is

*'ENTREZ_GENE': a character vector, records entrez gene id *'SEQUENCE': a character vector, peptide sequences *'ID': a character vector, Uniprot ID *'LEN': a character vector, length of peptides

Details

used as an example dataset

Annotation data obtained by:

library(UniProt.ws)

taxId(UniProt.ws) <- 7227

proteome <- prepareProteome(UniProt.ws)

proteome@proteome <- proteome@proteome[sample(1:19902, 1406), ]

Source

http://www.uniprot.org/

Examples

data(proteome.example)
head(proteome.example@proteome)
proteome.example@type

---

An object of dagPeptides-class representing acetylated lysine-containing peptides.

Description

A dataset containing the acetylated lysine-containing peptides from Drosophila melanogaster.

Usage

seq.example

Format

An object of dagPeptides-class Class The format is: A list.

*‘data': ’data.frame': 732 obs. of 7 variables *‘peptides': ’matrix': amnio acid in each position *'upstreamOffset': an integer, upstream offset position *'downstreamOffset': an integer, downstream offset position *'type': "character", type of identifiers

The format of data is

*'IDs': a character vector, input identifiers *'anchorAA': a character vector, anchor amino acid provided in inputs *'anchorPos': a numeric vector, anchor position in the protein *'peptide': a character vector, peptide sequences *'anchor': a character vector, anchor amino acid in the protein *'upstream': a character vector, upstream peptides *'downstream': a character vector, downstream peptides

Details

used as an example dataset

seq obtained by:

mart <- useMart("ensembl", "dmelanogaster_gene_ensembl")

dat <- read.csv(system.file("extdata", "dagLogoTestData.csv", package="dagLogo"))

seq <- fetchSequence(as.character(dat$entrez_geneid),

anchorPos=as.character(dat$NCBI_site),

mart=mart,

upstreamOffset=7,

downstreamOffset=7)

Examples

data(seq.example)
  head(seq.example@peptides)
  seq.example@upstreamOffset
  seq.example@downstreamOffset

---

Differential usage test of amino acids or amino acid groups.

Description

Test differential usage of amino acids with or without grouping between experimental sets and background sets.

Usage

testDAU(
  dagPeptides,
  dagBackground,
  groupingScheme = ls(envir = cachedEnv),
  bgNoise = NA,
  method = "none"
)

Arguments

dagPeptides	An object of Class dagPeptides-class.
dagBackground	An object of Class dagBackground-class.
groupingScheme	A character vector of length 1. Available choices are "no","bulkiness_Zimmerman","hydrophobicity_KD", "hydrophobicity_HW", "isoelectric_point_Zimmerman", "contact_potential_Maiorov", "chemistry_property_Mahler", "consensus_similarity_SF", "volume_Bigelow", "structure_alignments_Mirny", "polarity_Grantham", "sequence_alignment_Dayhoff", "bulkiness_Zimmerman_group", "hydrophobicity_KD_group", "hydrophobicity_HW_group", "charge_group", "contact_potential_Maiorov_group", "chemistry_property_Mahler_group", "consensus_similarity_SF_group", "volume_Bigelow_group", "structure_alignments_Mirny_group", "polarity_Grantham_group", "sequence_alignment_Dayhoff_group", "custom" and "custom_group". If "custom" or "custom_group" are used, users must define a grouping scheme using a list containing sublist named as "color", and "symbol" using the function addScheme, with group set as "NULL" or a list with same names as those of color and symbol. No grouping was applied for the first 12 schemes. It is used to color AAs based on similarities or group amino acids into groups of similarities.
bgNoise	A numeric vector of length 1 if not NA. It should be in the interval of (0, 1) when not NA.
method	A character vector of length 1, specifying the method used for p-value adjustment to correct for multiple testing. it can be "holm", "hochberg", "hommel","bonferroni", "BH", "BY", "fdr", or "none". For more details, see p.adjust.methods and p.adjust.

Value

An object of Class testDAUresults-class.

Author(s)

Jianhong Ou, Haibo Liu

Examples

dat <- unlist(read.delim(system.file(
                                   "extdata", "grB.txt", package = "dagLogo"),
                         header = FALSE, as.is = TRUE))
                         
##prepare an object of Proteome Class from a fasta file
proteome <- prepareProteome(fasta = system.file("extdata",
                                                "HUMAN.fasta",
                                                package = "dagLogo"), 
                            species = "Homo sapiens")
##prepare an object of dagPeptides Class
seq <- formatSequence(seq = dat, proteome = proteome, upstreamOffset = 14,
                     downstreamOffset = 15)
bg_fisher <- buildBackgroundModel(seq, background = "wholeProteome",
                                  proteome = proteome, testType = "fisher")
bg_ztest <- buildBackgroundModel(seq, background = "wholeProteome",
                                   proteome = proteome, testType = "ztest")

## no grouping and distinct coloring scheme, adjust p-values using the 
## "BH" method.
t0 <- testDAU(seq, dagBackground = bg_ztest, method = "BY")

## grouped by polarity index (Granthm, 1974)
t1 <- testDAU(dagPeptides = seq, dagBackground = bg_ztest, 
             groupingScheme = "polarity_Grantham_group")
             
## grouped by charge.
t2 <- testDAU(dagPeptides = seq, dagBackground = bg_ztest, 
              groupingScheme = "charge_group")
              
## grouped on the basis of the chemical property of side chains.
t3 <- testDAU(dagPeptides = seq, dagBackground = bg_ztest, 
              groupingScheme = "chemistry_property_Mahler_group")
              
## grouped on the basis of hydrophobicity (Kyte and Doolittle, 1982)
t4 <- testDAU(dagPeptides = seq, dagBackground = bg_ztest, 
              groupingScheme = "hydrophobicity_KD_group")

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Class testDAUresults.

Description

An S4 class to represent a DAU statistical test result from dagLogo analysis.

Slots

group

A character vector of length 1, the type of method for grouping amino acid.

testType

A character vector of length 1, the type of statistic testing. The available options are "fisher" and "z-test".

difference

A numeric matrix consisting of differences of amino acid proportions between the test set and the background set of aligned, formatted peptides at each position.

statistics

A numeric matrix consisting of Z-scores or odds ratios for Z-test and Fisher's exact test, respectively.

pvalue

A numeric matrix consisting of p-values.

background

A numeric matrix consisting of amino acid proportions in the background set of aligned, formatted peptides at each position.

motif

A numeric matrix consisting of amino acid proportions at each position for visualization by dagLogo.

upstreamOffset

A positive integer, the upstream offset relative to the anchoring position.

downstreamOffset

A positive integer, the upstream offset relative to the anchoring position.

Author(s)

Jianhong Ou, Haibo Liu

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