Free transcription dna software for linux

Bio::Restriction::Enzyme is a single restriction endonuclease (cuts DNA at specific locations).

SYNOPSIS

# set up a single restriction enzyme. This contains lots of
# information about the enzyme that is generally parsed from a
# rebase file and can then be read back

use Bio::Restriction::Enzyme;

# define a new enzyme with the cut sequence
my $re=new Bio::Restriction::Enzyme
(-enzyme=>EcoRI, -seq=>G^AATTC);

# once the sequence has been defined a bunch of stuff is calculated
# for you:

#### PRECALCULATED

# find where the enzyme cuts after ...
my $ca=$re->cut;

# ... and where it cuts on the opposite strand
my $oca = $re->complementary_cut;

# get the cut sequence string back.
# Note that site will return the sequence with a caret
my $with_caret=$re->site; #returns G^AATTC;

# but it is also a Bio::PrimarySeq object ....
my $without_caret=$re->seq; # returns GAATTC;
# ... and so does string
$without_caret=$re->string; #returns GAATTC;

# what is the reverse complement of the cut site
my $rc=$re->revcom; # returns GAATTC;

# now the recognition length. There are two types:
# recognition_length() is the length of the sequence
# cutter() estimate of cut frequency

my $recog_length = $re->recognition_length; # returns 6
# also returns 6 in this case but would return
# 4 for GANNTC and 5 for RGATCY (BstX2I)!
$recog_length=$re->cutter;

# is the sequence a palindrome - the same forwards and backwards
my $pal= $re->palindromic; # this is a boolean

# is the sequence blunt (i.e. no overhang - the forward and reverse
# cuts are the same)
print "bluntn" if $re->overhang eq blunt;

# Overhang can have three values: "5", "3", "blunt", and undef
# Direction is very important if you use Klenow!
my $oh=$re->overhang;

# what is the overhang sequence
my $ohseq=$re->overhang_seq; # will return AATT;

# is the sequence ambiguous - does it contain non-GATC bases?
my $ambig=$re->is_ambiguous; # this is boolean

print "Stuff about the enzymenCuts after: $can",
"Complementary cut: $ocanSite:nt$with_caret orn",
"t$without_caretn";
print "Reverse of the sequence: $rcnRecognition length: $recog_lengthn",
"Is it palindromic? $paln";
print "The overhang is $oh with sequence $ohseqn",
"And is it ambiguous? $ambignn";


### THINGS YOU CAN SET, and get from rich REBASE file

# get or set the isoschizomers (enzymes that recognize the same
# site)
$re->isoschizomers(PvuII, SmaI); # not really true :)
print "Isoschizomers are ", join " ", $re->isoschizomers, "n";

# get or set the methylation sites
$re->methylation_sites(2); # not really true :)
print "Methylated at ", join " ", keys %{$re->methylation_sites},"n";

#Get or set the source microbe
$re->microbe(E. coli);
print "It came from ", $re->microbe, "n";

# get or set the person who isolated it
$re->source("Rob"); # not really true :)
print $re->source, " sent it to usn";

# get or set whether it is commercially available and the company
# that it can be bought at
$re->vendors(NEB); # my favorite
print "Is it commercially available :";
print $re->vendors ? "Yes" : "No";
print " and it can be got from ", join " ",
$re->vendors, "n";

# get or set a reference for this
$re->reference(Edwards et al. J. Bacteriology);
print "It was not published in ", $re->reference, "n";

# get or set the enzyme name
$re->name(BamHI);
print "The name of EcoRI is not really ", $re->name, "n";

This module defines a single restriction endonuclease. You can use it to make custom restriction enzymes, and it is used by Bio::Restriction::IO to define enzymes in the New England Biolabs REBASE collection.

Use Bio::Restriction::Analysis to figure out which enzymes are available and where they cut your sequence.

ESTScan project is a program that can detect coding regions in DNA sequences, even if they are of low quality. ESTScan will also detect and correct sequencing errors that lead to frameshifts.
ESTScan is not a gene prediction program , nor is it an open reading frame detector. In fact, its strength lies in the fact that it does not require an open reading frame to detect a coding region. As a result, the program may miss a few translated amino acids at either the N or the C terminus, but will detect coding regions with high selectivity and sensitivity.
Method
ESTScan takes advantages of the bias in hexanucleotide usage found in coding regions relative to non-coding regions. This bias is formalized as an inhomogeneous 3-periodic fifth-order Hidden Markov Model (HMM). Additionally, the HMM of ESTScan has been extended to allows insertions and deletions when these improve the coding region statistics.
Enhancements:
- A bug has been found and fixed in the BTLib package.
- The bug prevented the extract_mRNA script from the estscan package from functioning properly when parsing RefSeq sequences.
- The prepare_data script has also been fixed to properly report the percent of masked nucleotides.
- All users preparing score matrices for ESTScan are strongly encouraged to update.
- Updating is less important for people who only scan sequences with already existing matrices.

Bio::SAGE::Comparison module compares data from serial analysis of gene expression (SAGE) libraries.

SYNOPSIS

use Bio::SAGE::Comparison;
$sage = Bio::SAGE::Comparison->new();

This module provides several tools for comparing data generated from serial analysis of gene expression (SAGE) libraries.

BACKGROUND

Serial analysis of gene expression (SAGE) is a molecular technique for generating a near-global snapshot of a cell population’s transcriptome. Briefly, the technique extracts short sequences at defined positions of transcribed mRNA. These short sequences are then paired to form ditags. The ditags are concatamerized to form long sequences that are then cloned. The cloned DNA is then sequenced. Bioinformatic techniques are then employed to determine the original short tag sequences, and to derive their progenitor mRNA. The number of times a particular tag is observed can be used to quantitate the amount of a particular transcript. The original technique was described by Velculescu et al. (1995) and utilized an ~14bp sequence tag. A modified protocol was introduced by Saha et al. (2002) that produced ~21bp tags.

PURPOSE

This module facilitates the comparison of SAGE libraries. Specifically:

1. Calculations for determining the statistical
significance of expression differences.
2. Dynamically convert longer-tag libraries to
a shorter type for comparison (e.g. comparing
a LongSAGE vs. a regular SAGE library).

Both regular SAGE (14mer tag) and LongSAGE (21mer tag) are supported by this module.

Statistical significance in library comparisons is calculated using the method described by Audic and Claverie (1997). Code was generated by directly porting the authors original C source.

Keystroke is a tool that aids in the transcription, subtitling, and logging of video and audio. Keystroke project combines a video player and text editor and allows control of the media through keystrokes rather than through the mouse.

Furthermore, it tracks the start and end times of each entered phrase in order to use the transcription in CMML/Annodex files as subtitles. It is also unique in that it does not display each clip in the usual table layout, instead utilizing a script-like view. Output can be in SRT, CMML, and plain text.

Bio::Tools::Run::PiseApplication::fasta is a Bioperl class for sequence database search.

Parameters:

fasta (Excl)
Fasta program

query (Sequence)
Query sequence File
pipe: seqfile

seqtype (Excl)
Is it a DNA or protein sequence (-n)

protein_db (Excl)
Protein Database

nucleotid_db (Excl)
Nucleotid Database

break_long (Integer)
Break long library sequences into blocks (-N)

ktup (Integer)
ktup : sensitivity and speed of the search (protein:2, DNA:6)

optcut (Integer)
OPTCUT : the threshold for optimization. (-c)

gapinit (Integer)
Penalty for gap initiation (-12 by default for fasta with proteins, -16 for DNA) (-f)

gapext (Integer)
Penalty for gap extention (-2 by default for fasta with proteins, -4 for DNA) (-g)

high_expect (Float)
Maximal expectation value threshold for displaying scores and alignments (-E)

low_expect (Float)
Minimal expectation value threshold for displaying scores and alignments (-F)

nucleotid_match (Integer)
Reward for a nucleotid match (-r)

nucleotid_mismatch (Integer)
Penalty for a nucleotid mismatch (-r)

matrix (Excl)
Scoring matrix file (-s)

X_penalty (Integer)
Penalty for a match to X (independently of the PAM matrix) (-x)

frameshift (Integer)
Penalty for frameshift between codon (fast[xy]/tfast[xy])(-h)

frameshift_within (Integer)
Penalty for frameshift within a codon (fasty/tfasty)(-j)

threeframe (Switch)
Search only the three forward frames (tfasta) (-3)

invert (Switch)
Reverse complement the query sequence (all tfasta) (-i)

genetic_code (Excl)
Use genetic code for translation (tfasta/tfast[xy]/fast[xy]) (-t)

band (Integer)
band-width used for optimization (-y)

swalig (Switch)
unlimited Smith-Waterman alignment for DNA (-A)

noopt (Switch)
no limited optimization (-o)

stat (Excl)
Specify statistical calculation. (-z)

random (Switch)
Estimate stat parameters from shuffled copies of each library sequence (-z)

histogram (Switch)
No histogram (-H)

scores (Integer)
number of similarity scores to be shown (-b)

alns (Integer)
number of alignments to be shown (-d)

html_output (Switch)
HTML output (-m)

markx (Excl)
Alternate display of matches and mismatches in alignments

init1 (Switch)
sequences ranked by the z-score based on the init1 score (-1)

z_score_out (Excl)
Show normalize score as (-B)

showall (Switch)
both sequences are shown in their entirety in alignments (fasta only) (-a)

linlen (Integer)
output line length for sequence alignments (max. 200) (-w)

offsets (String)
Start numbering the aligned sequences at position x1 x2 (2 numbers) (-X)

info (Switch)
Display more information about the library sequence in the alignment (-L)

statfile (OutFile)
Write out the sequence identifier, superfamily number, and similarity scores to this file (-R)

filter (Switch)
Lower case filtering (-S)

outfile (OutFile)
pipe: mview_input

html_outfile (OutFile)