Oligomap 1.01 – Identification of nearly-perfect matches of small RNAs in Sequence databases

Oligomap 1.01

:: DESCRIPTION

Oligomap is a program for fast identification of nearly-perfect matches of small RNAs in sequence databases. It allows to exhaustively identify all the perfect and 1-error (where an error is defined to be a mismatch, insertion or deletion) matches of large sets of small RNAs to target sequences. Optimal performance is achieved at about 500000 query sequences

::DEVELOPER

Zavolan Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 Oligomap

:: MORE INFORMATION

Citation

Berninger P, Gaidatzis D, van Nimwegen E, Zavolan M.
Computational analysis of small RNA cloning data“,
Methods, 44(13-21), 2008

Rocket – Confirm Clones Match the Annotations provided by the Supplier

Rocket

:: DESCRIPTION

Rocket is a set of perl scripts and modules used to confirm that the clones sequenced in our Core Laboratory match the annotations provided by the supplier. (More precisely, Rocket provides a graphical interface using perl/Tk to a command line perl script.) Rocket will require some customization before you can use it. It assumes the existence of a local database containing the supplier’s clone annotations; you’ll have to create such a database separately and make sure the names of the fields in the database match those used by Rocket.

::DEVELOPER

Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 Rocket

:: MORE INFORMATION

GSM 0.3 – Genotype-based Matching

GSM 0.3

:: DESCRIPTION

GSM (genetic similarity score matching)is a software for efficient matched analysis of cases and controls in a genome-wide or large-scale candidate gene association study. GSM comprises three steps: (1) calculating similarity scores for pairs of individuals using the genotype data; (2) matching sets of cases and controls based on the similarity scores so that matched cases and controls have similar genetic background; and (3) using conditional logistic regression to perform association tests. Through computer simulation we show that GSM correctly controls false-positive rates and improves power to detect true disease predisposing variants

::DEVELOPER

Liming Liang, @ the Center for Statistical Genetics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux /  Windows

:: DOWNLOAD

 GSM

:: MORE INFORMATION

Citation

Weihua Guan*, Liming Liang*, Michael Boehnke, Gonçalo R. Abecasis (2009).
Genotype-based matching to correct for population stratification in large-scale case-control genetic association studies.
Genet Epidemiol DOI:10.1002/gepi.20403