:: DESCRIPTION
nondetects is a suit of methods to model and impute non-detects in the results of qPCR experiments.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
On non-detects in qPCR data.
McCall MN, McMurray HR, Land H, Almudevar A.
Bioinformatics. 2014 Apr 23. pii: btu239
:: DESCRIPTION
FINDHAP is a program to find haplotypes and impute genotypes from multiple marker sets and sequence data
::DEVELOPER
Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
J Dairy Sci. 2013 Jan;96(1):668-78. doi: 10.3168/jds.2012-5702. Epub 2012 Oct 11.
Genomic imputation and evaluation using high-density Holstein genotypes.
VanRaden PM1, Null DJ, Sargolzaei M, Wiggans GR, Tooker ME, Cole JB, Sonstegard TS, Connor EE, Winters M, van Kaam JB, Valentini A, Van Doormaal BJ, Faust MA, Doak GA.
:: DESCRIPTION
IMPUTE is a program for estimating (“imputing”) unobserved genotypes in SNP association studies. The program is designed to work seamlessly with the output of the genotype calling program CHIAMO and the population genetic simulator HAPGEN, and it produces output that can be analyzed using the program SNPTEST.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Rubinacci S, Delaneau O, Marchini J.
Genotype imputation using the Positional Burrows Wheeler Transform.
PLoS Genet. 2020 Nov 16;16(11):e1009049. doi: 10.1371/journal.pgen.1009049. PMID: 33196638; PMCID: PMC7704051.
B. N. Howie, P. Donnelly and J. Marchini (2009)
A flexible and accurate genotype imputation method for the next generation of genome-wide association studies.
PLoS Genetics 5(6): e1000529
:: DESCRIPTION
GTOOL is a program for transforming sets of genotype data for use with the programs SNPTEST and IMPUTE.
::DEVELOPER
Colin Freeman , Jonathan Marchini
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
:: DESCRIPTION
phenomeImpute is an R package to impute missing values in large-scale high-dimensional phenome data. It includes several variations of KNN, random forest and MICE methods.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Liao SG, Lin Y, Kang DD, Chandra D, Bon J, Kaminski N, Sciurba FC, Tseng GC.
Missing value imputation in high-dimensional phenomic data: imputable or not, and how?
BMC Bioinformatics. 2014 Nov 5;15(1):346. doi: 10.1186/s12859-014-0346-6. PMID: 25371041; PMCID: PMC4228077.
