Limits...
FFBSKAT: fast family-based sequence kernel association test.

Svishcheva GR, Belonogova NM, Axenovich TI - PLoS ONE (2014)

Bottom Line: We compared the performance of our software with that of two existing software for family-based sequence kernel association testing, namely, ASKAT and famSKAT, using the Genetic Analysis Workshop 17 family sample.In addition, the calculations of the three-compared software were similarly accurate.With respect to the available analysis modes, we combined the advantages of both ASKAT and famSKAT and added new options to empower FFBSKAT users.

View Article: PubMed Central - PubMed

Affiliation: Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia.

ABSTRACT
The kernel machine-based regression is an efficient approach to region-based association analysis aimed at identification of rare genetic variants. However, this method is computationally complex. The running time of kernel-based association analysis becomes especially long for samples with genetic (sub) structures, thus increasing the need to develop new and effective methods, algorithms, and software packages. We have developed a new R-package called fast family-based sequence kernel association test (FFBSKAT) for analysis of quantitative traits in samples of related individuals. This software implements a score-based variance component test to assess the association of a given set of single nucleotide polymorphisms with a continuous phenotype. We compared the performance of our software with that of two existing software for family-based sequence kernel association testing, namely, ASKAT and famSKAT, using the Genetic Analysis Workshop 17 family sample. Results demonstrate that FFBSKAT is several times faster than other available programs. In addition, the calculations of the three-compared software were similarly accurate. With respect to the available analysis modes, we combined the advantages of both ASKAT and famSKAT and added new options to empower FFBSKAT users. The FFBSKAT package is fast, user-friendly, and provides an easy-to-use method to perform whole-exome kernel machine-based regression association analysis of quantitative traits in samples of related individuals. The FFBSKAT package, along with its manual, is available for free download at http://mga.bionet.nsc.ru/soft/FFBSKAT/.

Show MeSH

Related in: MedlinePlus

Comparison of the P values (shown as minus base 10 logarithm) computed with famSKAT, ASKAT, and FFBSKAT given a sample of 500 individuals, for two causal genes, FLT1 and VEGFA.200 realizations of Q1 quantitative trait in GAW17 data were analyzed. The line indicates one-to-one correspondence.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4048315&req=5

pone-0099407-g002: Comparison of the P values (shown as minus base 10 logarithm) computed with famSKAT, ASKAT, and FFBSKAT given a sample of 500 individuals, for two causal genes, FLT1 and VEGFA.200 realizations of Q1 quantitative trait in GAW17 data were analyzed. The line indicates one-to-one correspondence.

Mentions: For two genes, VEGFA and FLT1, we compared the P values determined by using “FFBSKAT” with those values obtained by using “famSKAT” and “ASKAT” to estimate the accuracy of our software. The P values had a clear one-to-one correspondence (Fig. 2). The statistical properties of the methods implemented in ASKAT and famSKAT have been analyzed previously [22], [23]. The pure coincidence of the P values for these software and FFBSKAT warrants the identity of the statistical properties of the methods implemented in all three software.


FFBSKAT: fast family-based sequence kernel association test.

Svishcheva GR, Belonogova NM, Axenovich TI - PLoS ONE (2014)

Comparison of the P values (shown as minus base 10 logarithm) computed with famSKAT, ASKAT, and FFBSKAT given a sample of 500 individuals, for two causal genes, FLT1 and VEGFA.200 realizations of Q1 quantitative trait in GAW17 data were analyzed. The line indicates one-to-one correspondence.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4048315&req=5

pone-0099407-g002: Comparison of the P values (shown as minus base 10 logarithm) computed with famSKAT, ASKAT, and FFBSKAT given a sample of 500 individuals, for two causal genes, FLT1 and VEGFA.200 realizations of Q1 quantitative trait in GAW17 data were analyzed. The line indicates one-to-one correspondence.
Mentions: For two genes, VEGFA and FLT1, we compared the P values determined by using “FFBSKAT” with those values obtained by using “famSKAT” and “ASKAT” to estimate the accuracy of our software. The P values had a clear one-to-one correspondence (Fig. 2). The statistical properties of the methods implemented in ASKAT and famSKAT have been analyzed previously [22], [23]. The pure coincidence of the P values for these software and FFBSKAT warrants the identity of the statistical properties of the methods implemented in all three software.

Bottom Line: We compared the performance of our software with that of two existing software for family-based sequence kernel association testing, namely, ASKAT and famSKAT, using the Genetic Analysis Workshop 17 family sample.In addition, the calculations of the three-compared software were similarly accurate.With respect to the available analysis modes, we combined the advantages of both ASKAT and famSKAT and added new options to empower FFBSKAT users.

View Article: PubMed Central - PubMed

Affiliation: Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia.

ABSTRACT
The kernel machine-based regression is an efficient approach to region-based association analysis aimed at identification of rare genetic variants. However, this method is computationally complex. The running time of kernel-based association analysis becomes especially long for samples with genetic (sub) structures, thus increasing the need to develop new and effective methods, algorithms, and software packages. We have developed a new R-package called fast family-based sequence kernel association test (FFBSKAT) for analysis of quantitative traits in samples of related individuals. This software implements a score-based variance component test to assess the association of a given set of single nucleotide polymorphisms with a continuous phenotype. We compared the performance of our software with that of two existing software for family-based sequence kernel association testing, namely, ASKAT and famSKAT, using the Genetic Analysis Workshop 17 family sample. Results demonstrate that FFBSKAT is several times faster than other available programs. In addition, the calculations of the three-compared software were similarly accurate. With respect to the available analysis modes, we combined the advantages of both ASKAT and famSKAT and added new options to empower FFBSKAT users. The FFBSKAT package is fast, user-friendly, and provides an easy-to-use method to perform whole-exome kernel machine-based regression association analysis of quantitative traits in samples of related individuals. The FFBSKAT package, along with its manual, is available for free download at http://mga.bionet.nsc.ru/soft/FFBSKAT/.

Show MeSH
Related in: MedlinePlus