Category: DNA / Genome Analysis

YACOP 2 – Gene Prediction for Prokaryotes

YACOP 2

:: DESCRIPTION

YACOP is a metatool for gene prediction in prokaryotic genomes. The predictions generated by the tool are based on the output of existing gene finding programs. In present YACOP supports the boolean combination of predictions from Critica 105b (with wublast2), Glimmer 2.02 or Glimmer 2.10 (with RBSfinder), Orpheus (with dps) and ZCurve1.0. The output can be adapted to different modes by customizing the enclosed ini-file, so that the tool can also be used for comparision and evaluation of different predictions.

::DEVELOPER

the Department of Bioinformatics of the University of Göttingen

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

YACOP

:: MORE INFORMATION

Citation

M. Tech and R. Merkl (2003)
YACOP: Enhanced Gene Prediction Obtained by a Combination of Existing Methods
In Silico Biology 3:4.

VCMap 3.1 – A tool for Comparative Genomics Research

VCMap 3.1

:: DESCRIPTION

VCMap (The Virtual Comparative Map) explores the conserved synteny between Rat, Mouse and Human.

:: DEVELOPER

VCMap Team

:: SCREENSHOTS

VCMap

:: REQUIREMENTS

  • Windows /Linux/MacOsX
  • Java 

:: DOWNLOAD

  VCMap

:: MORE INFORMATION

Citation

Brief Bioinform. 2013 Jul;14(4):520-6. doi: 10.1093/bib/bbt007. Epub 2013 Feb 22.
The Rat Genome Database 2013–data, tools and users.
Laulederkind SJ, Hayman GT, Wang SJ, Smith JR, Lowry TF, Nigam R, Petri V, de Pons J, Dwinell MR, Shimoyama M, Munzenmaier DH, Worthey EA, Jacob HJ.

SRCP 1.0 – Sequence Read Classification Pipeline

SRCP 1.0

:: DESCRIPTION

The SRCP is a high-throughput, automated data analysis pipeline that is used to classify genomic shotgun reads into functional/descriptive sequence categories. It represents a powerful means of rapidly describing the sequence content of a genome and a standardized method for estimating gene/repeat enrichment or reduction afforded by Cot filtration, CBCS, and/or other reduced-representation sequencing (RRS) techniques

:: DEVELOPER

the Institute for Genomics, Biocomputing & Biotechnology (IGBB).

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Perl

:: DOWNLOAD

 SRCP

:: MORE INFORMATION

Citation

Anal Biochem. 2008 Feb 1;373(1):78-87.
An automated, high-throughput sequence read classification pipeline for preliminary genome characterization.
Chouvarine P, Saha S, Peterson DG.

CotQuest 1.0 – Nonlinear Regression Analysis of DNA Reassociation Kinetics data

CotQuest 1.0

:: DESCRIPTION

CotQuest is specifically tailored to conduct nonlinear regression analysis of DNA reassociation kinetics (i.e., Cot) data when used with the statistics package SAS.  CotQuest is unique in that it does not require users to input guesses as to the final values of parameters.  The CotQuest program surpasses all existing Cot analysis programs with regard to automation, statistical robustness, user-friendliness, and graphical output.

:: DEVELOPER

the Institute for Genomics, Biocomputing & Biotechnology (IGBB).

:: SCREENSHOTS

CotQuest

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • SAS

:: DOWNLOAD

 CotQuest

:: MORE INFORMATION

Citation

Anal Biochem. 2009 May 15;388(2):322-30. doi: 10.1016/j.ab.2009.03.007.
CotQuest: improved algorithm and software for nonlinear regression analysis of DNA reassociation kinetics data.
Bunge J, Chouvarine P, Peterson DG.

SITES 1.1 – Analysis of Comparative DNA Sequence data

SITES 1.1

:: DESCRIPTION

SITES is a computer program for the analysis of comparative DNA sequence data.  Basic analyses include: data summaries by polymorphism class;  polymorphism estimates within and between groups (species); estimates of migration, neutral model, and recombination parameters; and linkage disequilibrium analyses.  SITES is primarily intended for data sets with multiple closely related sequences. It is especially useful when multiple sequences have been obtained from each of one or several closely related populations or species.

::DEVELOPER

the Hey lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOsX

:: DOWNLOAD

 SITES

:: MORE INFORMATION

Citation:

Hey, J and J. Wakeley. 1997.
A coalescent estimator of the population recombination rate.
GENETICS 145: 833-846.

Marina 1.03 – Identification of Over/under-represented TFBSs given large sets of Promoter-sequences

Marina 1.03

:: DESCRIPTION

Marina is an OS-independent GUI tool for computing TFBS abundance given two sets of promoter sequences. Marina performs such computations by harnessing 7 knowledge-discovery statistical metrics and the hypergeometric distribution so as to infer magnitude of TFBS over-representation. A standardization algorithm known as Iterative Proportional Fitting (IPF) enables “agreement” across these various metrics as to which TFBSs are the most over-represented and which are not.

::DEVELOPER

Parsa Hosseini

:: SCREENSHOTS

Marina

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • Java

:: DOWNLOAD

 Marina

:: MORE INFORMATION

Citation

Plant Methods. 2013 Apr 11;9(1):12. doi: 10.1186/1746-4811-9-12.
Using an ensemble of statistical metrics to quantify large sets of plant transcription factor binding sites.
Hosseini P, Ovcharenko I, Matthews BF.

SHREC 2.2 – Short Read Error Correction

SHREC 2.2

:: DESCRIPTION

SHREC is a new algorithm for correcting errors in short-read data that uses a generalized suffix trie on the read data as the underlying data structure. Our results show that the method can identify erroneous reads with sensitivity and specificity of over 99% and 96% for simulated data with error rates of up to 3% as well as for real data. Furthermore, it achieves an error correction accuracy of over 80% for simulated data and over 88% for real data. These results are clearly superior to previously published approaches.

::DEVELOPER

Jan Schröder

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 SHREC

:: MORE INFORMATION

Citation:

Jan Schröder, Heiko Schröder, Simon J. Puglisi, Ranjan Sinha, and Bertil Schmidt,
SHREC: A short-read error correction method,
Bioinformatics, 2009 25(17):2157-2163.

MixSIH 1.0.0 – Haplotype Assembly with Mixture Model

MixSIH 1.0.0

:: DESCRIPTION

MixSIH is a probabilistic model for solving the single individual haplotyping (SIH) or haplotype assembly problem.

::DEVELOPER

hirotaka MATSUMOTO , Kiryu Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 MixSIH

:: MORE INFORMATION

Citation

BMC Genomics. 2013;14 Suppl 2:S5. doi: 10.1186/1471-2164-14-S2-S5.
MixSIH: a mixture model for single individual haplotyping.
Matsumoto H, Kiryu H.