Visualize significant conserved amino acid sequence pattern in groups based on probability theory

Description

We implement iceLogo by R to visualize significant conserved amino acid sequence pattern based on probability theory. Compare to iceLogo, dagLogo can also visualize significant sequence patterns by clustering the peptides by groups such as charge, chemistry, hydrophobicity and etc.

Details

DAG: Differential Amino acid Group

There are several differences between dagLogo from iceLogo:

1. The sequence patterns can be grouped by charge, chemistry, hydrophobicity and etc.

2. dagLogo accepts different length of aligned amino acid sequences.

3. Except Random, regional (called restricted in dagLogo) and terminal (called anchored) background model, the background sequence could be set to other regions of the genes in inputs and complementary set of the proteome.

Author(s)

Jianhong Ou, Julie Lihua Zhu

Maintainer: Jianhong Ou <jianhong.ou@umassmed.edu>

Examples

    data("seq.example")
    data("proteome.example")
    bg <- buildBackgroundModel(seq.example, proteome=proteome.example, permutationSize=10L)
    t <- testDAU(seq.example, bg)
    dagLogo(t)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(dagLogo)
Loading required package: biomaRt
Loading required package: grImport
Loading required package: grid
Loading required package: XML
Loading required package: motifStack
Loading required package: MotIV
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit


Attaching package: 'MotIV'

The following object is masked from 'package:stats':

    filter

Loading required package: ade4

Attaching package: 'ade4'

The following object is masked from 'package:BiocGenerics':

    score

Loading required package: Biostrings
Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: XVector
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/dagLogo/dagLogo-package.Rd_%03d_medium.png", width=480, height=480)
> ### Name: dagLogo-package
> ### Title: Visualize significant conserved amino acid sequence pattern in
> ###   groups based on probability theory
> ### Aliases: dagLogo-package
> ### Keywords: package
> 
> ### ** Examples
> 
>     data("seq.example")
>     data("proteome.example")
>     bg <- buildBackgroundModel(seq.example, proteome=proteome.example, permutationSize=10L)
>     t <- testDAU(seq.example, bg)
>     dagLogo(t)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>