Description Usage Arguments Value Author(s) Examples
Test differential usage of amino acids with or without grouping between experimental sets and background sets.
1 2 3 4 5 6 7 | testDAU(
dagPeptides,
dagBackground,
groupingScheme = ls(envir = cachedEnv),
bgNoise = NA,
method = "none"
)
|
dagPeptides |
An object of Class |
dagBackground |
An object of 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 |
An object of Class testDAUresults-class
.
Jianhong Ou, Haibo Liu
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | 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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