seqRFLP (version 1.0.1)

seqRFLP-package: Simulation and visualization of Restriction Fragment Length Polymorphism(RFLP) pattern from DNA sequences

Description

This package includes functions for handling DNA sequences, especially for simulating RFLP and TRFLP pattern based on selected restriction enzyme and DNA sequences.

Details

Package:

seqRFLP

Type:

Package

Version:

1.0.1

Date:

2010-10-13

License:

GPL-2

LazyLoad:

yes

References

Saiki RK, Scharf S, Faloona F, Mullis KB, Erlich HA, Arnheim N (1985). Enzymatic amplification of beta-globin genomic sequences and restriction site analysis for diagnosis of sickle cell anemia. Science 230 (4723):1350-4

Examples

### Featured examples
### 1. File(s) importing:

### 1.1 importing fasta files.
### read.fasta() example
### 
cat(
">No305",
"NTTCGAAAAACACACCCACTACTAAAANTTATCAGTCACT",
file = "dna1.fas", sep = "\n")
sequences <- read.fasta("dna1.fas")
unlink("dna1.fas")


### 1.2 Concatenating all fasta files in working directory to fasta data
### raw2Fas() example
cat(
">No305",
"NTTCGAAAAACACACCCACTACTAAAANTTATCAGTCACT",
file = "dna1.fas", sep = "\n")
cat(
">No304",
"ATTCGAAAAACACACCCACTACTAAAAATTATCAACCACT",
file = "dna2.fas", sep = "\n")
cat(
">No305",
"NTTCGAAAAACACACCCACTACTAAAANTTATCAGTCACT",
file = "dna3.fas", sep = "\n")

raw2Fas(getwd(), appendix = ".fas")

unlink("dna1.fas")
unlink("dna2.fas")
unlink("dna3.fas")

## 1.3 importing phy, nexus, and converting to fasta objects for further analysis.

##### read.nxs() example
data(fil.nxs)
writeLines(fil.nxs, "example.nxs")
nxs <- read.nxs("example.nxs")
as.fasta(nxs)
unlink("example.nxs")

##### read.phy() example
data(fil.phy)
writeLines(fil.phy, "example.phy")
phy <- read.phy("example.phy")
as.fasta(phy)
unlink("example.phy")

## 2 Check and visualising cutting patterns of restriction enzymes on sequences.

## 2.1 enzCut() example
data(enzdata)
enznames <- c("EcoRI", "Acc65I")
data(fil.phy)
fas <- ConvFas(fil = fil.phy, type = "phy")
enzCut(DNAsq = fas[2], enznames = "AluI", enzdata = enzdata)
rm(list = ls())

### 2.2  fragdat() example
data(enzdata)
data(fil.phy)
fas <- ConvFas(fil = fil.phy, type = "phy")
frag.dat(fil = fas, enznames = "EcoRI", enzdata = enzdata)

## 2.3 plotenz() example
data(enzdata)
data(fil.phy)
fas <- ConvFas(fil = fil.phy, type = "phy")
enznames <- c("EcoRI", "Acc65I", "HinfI")

plotenz(sequences = fas, enznames = enznames, 
        enzdata = enzdata, side = TRUE, type = "RFLP")
		
plotenz(sequences = fas, enznames = enznames, 
        enzdata = enzdata, side = FALSE, type = "RFLP")		
				
plotenz(sequences = fas, enznames = enznames, 
        enzdata = enzdata, side = TRUE, type = "TRFLP", "T3")

### 3 Sequence selection based on given primers.

### clipprobe()
## 3.1 Specify the forward and backward primer.
#clip the sequence between the backword and forward primer.
forProbe = ITS1F = 'CTTGGTCATTTAGAGGAAGTAA' # forward primer should be from the 5' to 3' end.
bacProbe = ITS4 = 'GCATATCAATAAGCGGAGGA'    # backward primer
#only sequence with two probes found could be clipped.

### 3.2 reading fasta data.
directory <- system.file("extdata", package = "seqRFLP")
path <- file.path(directory, "seqs.fasta")
fas <- read.fasta(path)

## 3.3 Clipping. Find clipped sequences, this usually takes less than 1 minunite.
## please wait for a moment.
clipped <- clipprobe(fas, forProbe, bacProbe, tol = 0, clipped.only = TRUE)

## 3.4 Checking the results.
## There are 368 selected sequences that could be clipped.
length(gnames.fas(clipped)) 
## ... in 393 original sequences.
length(gnames.fas(fas))
## Sequences that can not be clipped.
setdiff(gnames.fas(fas), gnames.fas(clipped))