Package 'ecolitk'

Title: Meta-data and tools for E. coli
Description: Meta-data and tools to work with E. coli. The tools are mostly plotting functions to work with circular genomes. They can used with other genomes/plasmids.
Authors: Laurent Gautier
Maintainer: Laurent Gautier <[email protected]>
License: GPL (>= 2)
Version: 1.79.0
Built: 2024-12-22 05:49:48 UTC
Source: https://github.com/bioc/ecolitk

Help Index

Escherichia coli data

Description

Meta-data related to Escherichia coli

Usage

data(ecoli.m52.genome)
data(ecoligenomeCHRLOC)
data(ecoligenomeSYMBOL2AFFY)
data(ecoligenomeSYMBOL)
data(ecoligenomeSTRAND)
data(ecoligenome.operon)
ecoli.len

Format

The format for ecoli.m52.genome is character with genome sequence. The format for ecoligenomeCHRLOC is an environment (as a hash table). Each key is an Affyemtrix probe set ID, and each value is vector of two integers (begining and end - see the details below) The format for ecoligenomeSYMBOL2AFFFY is an environment (as a hash table). Each key is a gene symbol name. The format for ecoligenomeSYMBOL is an environment (as a hash table). Each key is an Affymetrix probe set id ecoli.len is a variable containing the size of the genome in ecoli.m52.genome.

Details

The environments ecoligenomeSYMBOL2AFFFY and ecoligenomeSYMBOL are like the ones in the data packages built by annBuilder.

The environment ecoligenomeCHRLOC differs: two integers are associated with each key, one corresponds to the begining of the segment the other to the end.

The environment ecoligenomeSTRAND returns a logical. TRUE means that the orientation is ‘+’, FALSE means that the orientation is '-' (and NA is used when irrelevant for the key).

Source

http://www.genome.wisc.edu/sequencing/k12.htm and http://www.biostat.harvard.edu/complab/dchip/info_file.htm

Examples

data(ecoli.m52.genome)

Known operon in E.coli - data.frame

Description

The known operon in the Escherichia coli genome.

Usage

data(ecoligenome.operon)

Format

A data frame with 932 observations (genes) on the following 4 variables.

gene.name

a character vector

gene.annotation

a character vector

operon.name

a factor with levels the names of the operons

operon.comments

a factor with levels the comments for the operons

Details

For some operons, the source of information specifies the existence of regulating elements such as promoter, terminator, box, etc... In those cases, the gene.name is set to "Regulation", and the gene.annotation gives what kind of regulating element it is. If volonteers, it would be neat to map those on the genome... Besides that, not much to add. The data structure is fairly straightforward.

Source

Built from the webpage: http://www.cib.nig.ac.jp/dda/backup/taitoh/ecoli.operon.html

Examples

library(Biobase)
data(ecoligenome.operon)
data(ecoligenomeSYMBOL2AFFY)

## something that might be useful when working with Affymetrix data:
## get the Affymetrix identifiers for the probe sets bundled in operons
## (see the vignette for more details)
ecoligenome.operon$affyid <-
unname(unlist(mget(ecoligenome.operon$gene.name,
                   ecoligenomeSYMBOL2AFFY, ifnotfound=NA)))

Environment for 'bnum' identifiers

Description

Environments to associate Affymetrix probe set IDs with 'bnum' IDs

Usage

data(ecoligenomeBNUM)
data(ecoligenomeBNUM2SYMBOL)
data(ecoligenomeBNUM2ENZYME)
data(ecoligenomeBNUM2GENBANK)
data(ecoligenomeBNUM2GENEPRODUCT)
data(ecoligenomeSYMBOL2BNUM)

Format

These are environment objects.

Details

Escherichia coli genes are sometimes identified by 'bnum's. This identfier is typically a 'b' followed by digits.

Source

BNUM numbers were parsed out of the Affymetrix identifiers. BNUM2* were obtained from the GenProtEC website.

Environment

Description

An environment to store associtations between 'bnum' identifiers (key) and 'MultiFun' identifiers (or strand information).

Usage

data(ecoligenomeBNUM2MULTIFUN)

Format

The format is: length 0 <environment> - attr(*, "comments")= chr "GenProtEC: MultiFun assignments for E. coli modules September 17th, 2003"

Details

'MultiFun' is a classification scheme. The structure is 'approximately tree-like'. Several 'MultiFun' numbers can be assigned to one 'bnum'.

Source

"http://genprotec.mbl.edu/files/MultiFun.txt"

function to compute gccontent

Description

A simple R function to compute the GC content of a sequence

Usage

gccontent(x)

Arguments

x

a vector of mode character

Details

This a simple (and not particularly fast) function to compute the GC content of sequence. When speed is an issue, one should use the function in the package matchprobes. This function only exists to avoid dependency on this package.

Value

The GC content (numeric)

A function to look for values across linked environments

Description

A function to look for values across linked environments.

Usage

linkedmultiget(x, envir.list = list(), unique = TRUE)

Arguments

x

The keys in the first environment in the list.
envir.list

A list of environments.
unique

Simplify the list returned by ensuring that the values for each key are unique.

Details

Environments can be considered as hashtables. The keys are obviously strings, but in some cases the associated values are also strings. This is the case for annotation environments (as built with the package AnnBuilder). This function helps to look for values across several environments: the keys have associated values in a first environment, these values are used as keys in the second environments, etc...

Value

A list of length the length of x.

Author(s)

Laurent Gautier

See Also

mget

Examples

data(ecoligenomeBNUM)
data(ecoligenomeBNUM2MULTIFUN)
data(multiFun)

## get 5 Affymetrix IDs
set.seed(456)
my.affyids <- sample(ls(ecoligenomeBNUM), 5)

## get the MULTIFUN annotations for them
r <- linkedmultiget(my.affyids, list(ecoligenomeBNUM,
                    ecoligenomeBNUM2MULTIFUN, multiFun))

print(r)

multiFun classification

Description

The MultiFun classification scheme

Usage

data(multiFun)
data(ecoligenomeMULTIFUN2GO)

Format

These are environments.

Source

http://genprotec.mbl.edu/files/MultiFun.txt

Examples

## To be done...

Functions to plot circular related figures

Description

Functions to plot circular related figures

Usage

linesCircle(radius, center.x = 0, center.y = 0, edges = 300, ...)
polygonDisk(radius, center.x = 0, center.y = 0, edges=300,
...)
arrowsArc(theta0, theta1, radius, center.x = 0, center.y = 0, edges = 10,
          length = 0.25, angle = 30, code = 2, ...)
pointsArc(theta0, theta1, radius, center.x = 0, center.y = 0, ...)
linesArc(theta0, theta1, radius, center.x = 0, center.y = 0, ...)
polygonArc(theta0, theta1, radius.in, radius.out,
           center.x = 0, center.y = 0,
           edges = 10,
           col = "black",
           border = NA,
           ...)

Arguments

theta0, theta1

start and end angles for the arc
radius

radius of the circle

radius.in

inner radius

radius.out

outer radius

center.x, center.y

Coordinates for the center of the circle (default to (0, 0))
edges

number of edges the shape is made of

col

color
border

border (see polygon)
length, angle, code

see the corresponding parameters for the function arrows
...

optional graphical paramaters

Details

Details to come... for now the best to run the examples and experiment by yourself...

Value

Function only used for their border effects.

Author(s)

laurent

Examples

par(mfrow=c(2,2))
n <- 10
thetas <- rev(seq(0, 2 * pi, length=n))

rhos <- rev(seq(1, n) / n)

xy <- polar2xy(rhos, thetas)
colo <- heat.colors(n)

plot(0, 0, xlim=c(-2, 2), ylim=c(-2, 2), type="n")
for (i in 1:n)
  linesCircle(rhos[i]/2, xy$x[i], xy$y[i])

plot(0, 0, xlim=c(-2, 2), ylim=c(-2, 2), type="n")
for (i in 1:n)
  polygonDisk(rhos[i]/2, xy$x[i], xy$y[i], col=colo[i])

plot(0, 0, xlim=c(-2, 2), ylim=c(-2, 2), type="n", xlab="", ylab="")
for (i in 1:n)
  polygonArc(0, thetas[i],
             rhos[i]/2, rhos[i],
             center.x = xy$x[i], center.y = xy$y[i], col=colo[i])

plot(0, 0, xlim=c(-2, 2), ylim=c(-2, 2), type="n", xlab="", ylab="")
for (i in (1:n)[-1]) {
  linesCircle(rhos[i-1], col="gray", lty=2)
  polygonArc(thetas[i-1], thetas[i],
             rhos[i-1], rhos[i], col=colo[i],
             edges=20)
  arrowsArc(thetas[i-1], thetas[i],
             rhos[i] + 1, col=colo[i],
             edges=20)
}

Functions to perform polar coordinate related functions

Description

Functions to perform polar coordinate related functions

Usage

polar2xy(rho, theta)
xy2polar(x, y)
rotate(x, y, alpha)

Arguments

x

cartesian coordinate

y

cartesian coordinate

rho

polar radius rho

theta

polar angle theta
alpha

angle to perform rotation

Details

y and theta can be respectively missing. In this case, x and rho are expected to be lists with entries x, y, rho, theta respectively.

Examples

n <- 40
nn <- 2
thetas <- seq(0, nn * 2 * pi, length=n)

rhos <- seq(1, n) / n

plot(c(-1, 1), c(-1, 1), type="n")
abline(h=0, col="grey")
abline(v=0, col="grey")

xy <- polar2xy(rhos, thetas)

points(xy$x, xy$y, col=rainbow(n))

Functions to plot circular chromosomes informations

Description

Functions to plot circular chromosomes informations

Usage

cPlotCircle(radius=1, xlim=c(-2, 2), ylim=xlim, edges=300, main=NULL,
            main.inside, ...)

chromPos2angle(pos, len.chrom, rot=pi/2, clockwise=TRUE)

polygonChrom(begin, end, len.chrom, radius.in, radius.out,
             total.edges = 300,
             edges = max(round(abs(end - begin)/len.chrom *
                     total.edges), 2, na.rm = TRUE),
             rot = pi/2, clockwise = TRUE, ...)

linesChrom(begin, end, len.chrom, radius,
             total.edges = 300,
             edges = max(round(abs(end - begin)/len.chrom *
                     total.edges), 2, na.rm = TRUE),
             rot = pi/2, clockwise = TRUE, ...)

ecoli.len

Arguments

radius

radius
xlim, ylim

range for the plot. Can be used to zoom-in a particular region.
pos

position (nucleic base coordinate)
begin

begining of the segment (nucleic base number).

end

end of the segment (nucleic base number).

len.chrom

length of the chromosome in base pairs

radius.in

inner radius

radius.out

outer radius

total.edges

total number of edges for the chromosome
edges

number of edges for the specific segment(s)

rot

rotation (default is pi / 2, bringing the angle zero at 12 o'clock)
clockwise

rotate clockwise. Default to TRUE.

main, main.inside

main titles for the plot
...

optional graphical parameters

Details

The function chromPos2angle is a convenience function. The variable ecoli.len contains the size of the Escheria coli genome considered (K12).

Value

Except chromPos2angle, the function are solely used for their border effects.

Author(s)

laurent <[email protected]>

Examples

data(ecoligenomeSYMBOL2AFFY)
data(ecoligenomeCHRLOC)

## find the operon lactose ("lac*" genes)
lac.i <- grep("^lac", ls(ecoligenomeSYMBOL2AFFY))
lac.symbol <- ls(ecoligenomeSYMBOL2AFFY)[lac.i]
lac.affy <- unlist(lapply(lac.symbol, get, envir=ecoligenomeSYMBOL2AFFY))

beg.end <- lapply(lac.affy, get, envir=ecoligenomeCHRLOC)
beg.end <- matrix(unlist(beg.end), nc=2, byrow=TRUE)

lac.o <- order(beg.end[, 1])

lac.i <- lac.i[lac.o]
lac.symbol <- lac.symbol[lac.o]
lac.affy <- lac.affy[lac.o]
beg.end <- beg.end[lac.o, ]

lac.col <- rainbow(length(lac.affy))

par(mfrow=c(2,2))

## plot

cPlotCircle(main="lac genes")
polygonChrom(beg.end[, 1], beg.end[, 2], ecoli.len, 1, 1.2, col=lac.col)
rect(0, 0, 1.1, 1.1, border="red")

cPlotCircle(xlim=c(0, 1.2), ylim=c(0, 1.1))
polygonChrom(beg.end[, 1], beg.end[, 2], ecoli.len, 1, 1.1, col=lac.col)
rect(0.4, 0.8, 0.7, 1.1, border="red")

cPlotCircle(xlim=c(.45, .5), ylim=c(.85, 1.0))
polygonChrom(beg.end[, 1], beg.end[, 2], ecoli.len, 1, 1.03, col=lac.col)

mid.genes <- apply(beg.end, 1, mean)
mid.angles <- chromPos2angle(mid.genes, ecoli.len)
xy <- polar2xy(1.03, mid.angles)
xy.labels <- data.frame(x = seq(0.45, 0.5, length=4), y = seq(0.95, 1.0, length=4))
segments(xy$x, xy$y, xy.labels$x, xy.labels$y, col=lac.col)
text(xy.labels$x, xy.labels$y, lac.symbol, col=lac.col)

Apply a function on a window sliding on a string

Description

Apply a function on a window sliding on a string.

Usage

wstringapply(x, SIZE, SLIDE, FUN, ...)

Arguments

x

The string

SIZE

The size of the window (number of characters).

SLIDE

offset to move at each slide
FUN

The function to be applied

...

optional parameter for the function FUN

Details

Apply the function FUN to substrings of x of length SIZE.

Value

A list of size nchar(x) - SIZE.

Author(s)

L, Gautier