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GEDI specifications

Information


Unique identifier OMICS_17778
Name GEDI
Alternative name Genotype Error Detection and Imputation
Software type Package/Module
Interface Command line interface
Restrictions to use None
Output data Several output files depending on the specified commands: summary statistics for each of performed step, the prefix of the population genotype file, all SNP genotypes at the end of GEDI's analysis, Mendelian inconsistencies if any discovered and corrected by GEDI, Mendelian consistent errors if any that pass the detection threshold in -ED, missing genotypes if any imputed by -MDR, file containing genotypes imputed by -IMP and file containing genotypes phased by -PHASE.
Operating system Unix/Linux
Programming languages C++
License GNU General Public License version 3.0
Computer skills Advanced
Version 1.0.3
Stability Stable
Source code URL https://dna.engr.uconn.edu/~software/GEDI/gedi-1.0.3.tar.gz
Maintained Yes

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Documentation


Maintainer


  • person_outline iim03001 <>

Additional information


http://arxiv.org/abs/0911.1765

Publication for Genotype Error Detection and Imputation

GEDI in publications

 (2)
PMCID: 3276165
PMID: 22384356
DOI: 10.1534/g3.111.001198

[…] in a dataset, beagle can run the calculations on a smaller set of clusters. similar state-reduction techniques are used by gerbil (kimmel and shamir 2005), fastphase (scheet and stephens 2006), gedi (), and other related methods. by contrast, the basic hmm used by impute2 and mach includes a state for every haplotype. using all of the states makes computation intractable, […]

PMCID: 2687951
PMID: 19477991
DOI: 10.1093/bioinformatics/btp197

[…] employed to solve the imputation problem, and hmms have been amongst the most popular. since the scope of our article is not the imputation problem, we will focus this small scale analysis only on gedi, a recently developed hmm-based method for genotype imputation (kennedy et al., ). gedi uses an hmm similar to the one of kimmel and shamir (), marchini et al. () and rastas et al. () trained […]


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GEDI institution(s)
Computer Science and Engineering Department, University of Connecticut, Storrs, CT, USA
GEDI funding source(s)
Supported in part by NSF Career award IIS-0546457 and NSF award DBI-0543365.

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