D MDR Ref [62, 63] [64] [65, 66] [67, 68] [69] [70] [12] Implementation Java R Java R C��/CUDA C

D MDR Ref [62, 63] [64] [65, 66] [67, 68] [69] [70] [12] Implementation Java R Java R C��/CUDA C�� Java URL www.epistasis.org/software.html Out there upon request, speak to authors sourceforge.net/projects/mdr/files/mdrpt/ cran.r-project.org/web/packages/MDR/index.html 369158 sourceforge.net/projects/mdr/files/mdrgpu/ ritchielab.psu.edu/software/mdr-download www.medicine.virginia.edu/clinical/departments/ psychiatry/sections/neurobiologicalstudies/ genomics/gmdr-software-request www.medicine.virginia.edu/clinical/departments/ psychiatry/sections/neurobiologicalstudies/ genomics/pgmdr-software-request Offered upon request, contact authors www.epistasis.org/software.html Obtainable upon request, get in touch with authors residence.ustc.edu.cn/ zhanghan/ocp/ocp.html sourceforge.net/projects/KB-R7943 (mesylate) web sdrproject/ Obtainable upon request, contact authors www.epistasis.org/software.html Available upon request, contact authors ritchielab.psu.edu/software/mdr-download www.statgen.ulg.ac.be/software.html cran.r-project.org/web/packages/mbmdr/index.html www.statgen.ulg.ac.be/software.html Consist/Sig KN-93 (phosphate) chemical information k-fold CV k-fold CV, bootstrapping k-fold CV, permutation k-fold CV, 3WS, permutation k-fold CV, permutation k-fold CV, permutation k-fold CV Cov Yes No No No No No YesGMDRPGMDR[34]Javak-fold CVYesSVM-GMDR RMDR OR-MDR Opt-MDR SDR Surv-MDR QMDR Ord-MDR MDR-PDT MB-MDR[35] [39] [41] [42] [46] [47] [48] [49] [50] [55, 71, 72] [73] [74]MATLAB Java R C�� Python R Java C�� C�� C�� R Rk-fold CV, permutation k-fold CV, permutation k-fold CV, bootstrapping GEVD k-fold CV, permutation k-fold CV, permutation k-fold CV, permutation k-fold CV, permutation k-fold CV, permutation Permutation Permutation PermutationYes Yes No No No Yes Yes No No No Yes YesRef ?Reference, Cov ?Covariate adjustment doable, Consist/Sig ?Strategies used to figure out the consistency or significance of model.Figure 3. Overview in the original MDR algorithm as described in [2] on the left with categories of extensions or modifications around the right. The initial stage is dar.12324 information input, and extensions to the original MDR technique coping with other phenotypes or data structures are presented in the section `Different phenotypes or information structures’. The second stage comprises CV and permutation loops, and approaches addressing this stage are provided in section `Permutation and cross-validation strategies’. The following stages encompass the core algorithm (see Figure 4 for specifics), which classifies the multifactor combinations into risk groups, plus the evaluation of this classification (see Figure 5 for facts). Solutions, extensions and approaches primarily addressing these stages are described in sections `Classification of cells into risk groups’ and `Evaluation in the classification result’, respectively.A roadmap to multifactor dimensionality reduction methods|Figure 4. The MDR core algorithm as described in [2]. The following measures are executed for each quantity of elements (d). (1) In the exhaustive list of all attainable d-factor combinations select 1. (two) Represent the chosen components in d-dimensional space and estimate the situations to controls ratio in the instruction set. (three) A cell is labeled as higher threat (H) when the ratio exceeds some threshold (T) or as low risk otherwise.Figure five. Evaluation of cell classification as described in [2]. The accuracy of just about every d-model, i.e. d-factor combination, is assessed with regards to classification error (CE), cross-validation consistency (CVC) and prediction error (PE). Amongst all d-models the single m.D MDR Ref [62, 63] [64] [65, 66] [67, 68] [69] [70] [12] Implementation Java R Java R C��/CUDA C�� Java URL www.epistasis.org/software.html Accessible upon request, get in touch with authors sourceforge.net/projects/mdr/files/mdrpt/ cran.r-project.org/web/packages/MDR/index.html 369158 sourceforge.net/projects/mdr/files/mdrgpu/ ritchielab.psu.edu/software/mdr-download www.medicine.virginia.edu/clinical/departments/ psychiatry/sections/neurobiologicalstudies/ genomics/gmdr-software-request www.medicine.virginia.edu/clinical/departments/ psychiatry/sections/neurobiologicalstudies/ genomics/pgmdr-software-request Readily available upon request, speak to authors www.epistasis.org/software.html Accessible upon request, make contact with authors home.ustc.edu.cn/ zhanghan/ocp/ocp.html sourceforge.net/projects/sdrproject/ Readily available upon request, contact authors www.epistasis.org/software.html Offered upon request, contact authors ritchielab.psu.edu/software/mdr-download www.statgen.ulg.ac.be/software.html cran.r-project.org/web/packages/mbmdr/index.html www.statgen.ulg.ac.be/software.html Consist/Sig k-fold CV k-fold CV, bootstrapping k-fold CV, permutation k-fold CV, 3WS, permutation k-fold CV, permutation k-fold CV, permutation k-fold CV Cov Yes No No No No No YesGMDRPGMDR[34]Javak-fold CVYesSVM-GMDR RMDR OR-MDR Opt-MDR SDR Surv-MDR QMDR Ord-MDR MDR-PDT MB-MDR[35] [39] [41] [42] [46] [47] [48] [49] [50] [55, 71, 72] [73] [74]MATLAB Java R C�� Python R Java C�� C�� C�� R Rk-fold CV, permutation k-fold CV, permutation k-fold CV, bootstrapping GEVD k-fold CV, permutation k-fold CV, permutation k-fold CV, permutation k-fold CV, permutation k-fold CV, permutation Permutation Permutation PermutationYes Yes No No No Yes Yes No No No Yes YesRef ?Reference, Cov ?Covariate adjustment attainable, Consist/Sig ?Approaches utilised to identify the consistency or significance of model.Figure three. Overview of the original MDR algorithm as described in [2] around the left with categories of extensions or modifications around the right. The first stage is dar.12324 data input, and extensions towards the original MDR process dealing with other phenotypes or data structures are presented in the section `Different phenotypes or information structures’. The second stage comprises CV and permutation loops, and approaches addressing this stage are offered in section `Permutation and cross-validation strategies’. The following stages encompass the core algorithm (see Figure 4 for details), which classifies the multifactor combinations into threat groups, plus the evaluation of this classification (see Figure 5 for specifics). Techniques, extensions and approaches mostly addressing these stages are described in sections `Classification of cells into threat groups’ and `Evaluation with the classification result’, respectively.A roadmap to multifactor dimensionality reduction procedures|Figure four. The MDR core algorithm as described in [2]. The following measures are executed for every single variety of factors (d). (1) In the exhaustive list of all attainable d-factor combinations pick a single. (two) Represent the chosen factors in d-dimensional space and estimate the circumstances to controls ratio in the training set. (three) A cell is labeled as higher risk (H) in the event the ratio exceeds some threshold (T) or as low threat otherwise.Figure five. Evaluation of cell classification as described in [2]. The accuracy of every d-model, i.e. d-factor mixture, is assessed with regards to classification error (CE), cross-validation consistency (CVC) and prediction error (PE). Amongst all d-models the single m.

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