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Additional file 3 of DM-PhyClus: a Bayesian phylogenetic algorithm for infectious disease transmission cluster inference
Research datakeyboard_double_arrow_right Dataset 2018figshare CIHR, NSERC
Authors: Villandré, Luc; Labbe, Aurélie; Brenner, Bluma; Roger, Michel; +1 Authors
Villandré, Luc; Labbe, Aurélie; Brenner, Bluma; Roger, Michel; Stephens, David A;
doi: 10.6084/m9.figshare.7091165.v1 , 10.6084/m9.figshare.7091165
doi: 10.6084/m9.figshare.7091165.v1 , 10.6084/m9.figshare.7091165
This file contains an R object giving the results for the scenario in the simulation study where the concentration parameter prior is assumed to have mean 10 and we use the MAP topology. The file is compressed in gzip format. (GZ 8365 kb)
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figshare
Dataset . 2018
License: https://creativecommons.org/licenses/by/4.0/legalcode
Data sources: Datacite
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Dataset . 2018
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Dataset . 2018
License: https://creativecommons.org/licenses/by/4.0/legalcode
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Dataset . 2018
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Additional file 1 of Who or what is to blame? Examining sociodemographic relationships to beliefs about causes, control, and responsibility for cancer and chronic disease prevention in Alberta, Canada
Research datakeyboard_double_arrow_right Dataset 2021figshare CIHR
Authors: Curtin, Kimberley D.; Thomson, Mathew; Nykiforuk, Candace I. J.;
Curtin, Kimberley D.; Thomson, Mathew; Nykiforuk, Candace I. J.;
doi: 10.6084/m9.figshare.14721944.v1 , 10.6084/m9.figshare.14721944
doi: 10.6084/m9.figshare.14721944.v1 , 10.6084/m9.figshare.14721944
Additional file 1. An additional table is available describing the variables and regression results included in each binary logistic regression model created for each survey question separated by imputed and complete case datasets. The file name is “BLR-Additional Table 1-BMC.xlsx” and it titled “Logistic Regression Models”.
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Dataset . 2021
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Dataset . 2021
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Dataset . 2021
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Dataset . 2021
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Additional file 4 of Mitochondrial DNA copy number can influence mortality and cardiovascular disease via methylation of nuclear DNA CpGs
Research datakeyboard_double_arrow_right Dataset 2020figshare CIHR
Authors: Castellani, Christina A.; Longchamps, Ryan J.; Sumpter, Jason A.; Newcomb, Charles E.; +20 Authors
Castellani, Christina A.; Longchamps, Ryan J.; Sumpter, Jason A.; Newcomb, Charles E.; Lane, John A.; Grove, Megan L.; Bressler, Jan; Brody, Jennifer A.; Floyd, James S.; Bartz, Traci M.; Taylor, Kent D.; Penglong Wang; Tin, Adrienne; Coresh, Josef; Pankow, James S.; Fornage, Myriam; Guallar, Eliseo; O’Rourke, Brian; Pankratz, Nathan; Chunyu Liu; Levy, Daniel; Sotoodehnia, Nona; Boerwinkle, Eric; Arking, Dan E.;
doi: 10.6084/m9.figshare.13018026 , 10.6084/m9.figshare.13018026.v1
doi: 10.6084/m9.figshare.13018026 , 10.6084/m9.figshare.13018026.v1
Additional file 4: Table S3. A. Results for 34 independent ARIC Discovery Meta-Analysis identified mtDNA-CN associated CpGs across all studied cohorts and Validation Meta-Analysis/All Cohort Meta-Analysis. Validation meta-analysis included CHS AA, CHS EA and FHS EA cohorts (P
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Dataset . 2020
License: https://creativecommons.org/licenses/by/4.0/legalcode
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Dataset . 2020
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Dataset . 2020
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Dataset . 2020
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Research data supporting "Common variation in genes encoding small GTPases and ovarian cancer risk": GTPases candidate gene SNP genotypes
Research datakeyboard_double_arrow_right Dataset 2018Embargo end date: 08 Mar 2018 United Kingdom Apollo - University of Cambridge Repository NIH | USC COMPREHENSIVE CANCER ..., NIH | GENETIC EPIDEMIOLOGY OF O..., NIH | Core--Tissue Banking and ...
Authors: Pharoah, PDP;
Pharoah, PDP;
doi: 10.17863/cam.20843
doi: 10.17863/cam.20843
Genotype data and related phenotype data for Ovarian Cancer Association Consortium project investigating common variantion in GTPAse genes and ovarian cancer risk
Apolloarrow_drop_down
Apollo
Dataset . 2018
License: https://creativecommons.org/licenses/by/4.0/legalcode
Data sources: Datacite
Apollo
Dataset
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Data sources: Apollo
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Apollo
Dataset . 2018
License: https://creativecommons.org/licenses/by/4.0/legalcode
Data sources: Datacite
Apollo
Dataset
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Additional file 2: of The parameter sensitivity of random forests
Research datakeyboard_double_arrow_right Dataset 2016Figshare CIHR
Authors: Huang, Barbara; Boutros, Paul;
Huang, Barbara; Boutros, Paul;
doi: 10.6084/m9.figshare.c.3626282_d2 , 10.6084/m9.figshare.c.3626282_d2.v1
doi: 10.6084/m9.figshare.c.3626282_d2 , 10.6084/m9.figshare.c.3626282_d2.v1
AUC results for low p/n data. Low p/n results for prediction accuracy using AUC as the performance metric for non-cross-validation results, 10-fold cross-validation and stratified 10-fold cross-validation. Ranks indicate the relative performance of different models with lower ranks representing higher performing models i.e., a rank of 1 is the best model. The default settings (n tree = 500, m try = 3, sampsize = 720) are found on row 1502 of the table. (CSV 116 kb)
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Dataset . 2016
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Data sources: Datacite
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Dataset . 2016
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Dataset . 2016
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Dataset . 2016
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Testing the feasibility of a clinical trial comparing a pre-surgery medication cocktail and nerve-numbing injections for pain management after minimally invasive shoulder surgery
Research datakeyboard_double_arrow_right Dataset 2019Springer Science and Business Media LLC CIHR
Authors: Ana Velly;
Ana Velly;
doi: 10.1186/isrctn14069845
doi: 10.1186/isrctn14069845
https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1186/isrctn...
Dataset . 2019
Data sources: Crossref
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Dataset . 2019
Data sources: Crossref
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Additional file 2 of Genome-wide prediction of cis-regulatory regions using supervised deep learning methods
Research datakeyboard_double_arrow_right Dataset 2018Figshare NSERC, CIHR, NIH | Computational Resources f...
Authors: Yifeng Li; Wenqiang Shi; Wyeth Wasserman;
Yifeng Li; Wenqiang Shi; Wyeth Wasserman;
doi: 10.6084/m9.figshare.6401516.v1 , 10.6084/m9.figshare.6401516
doi: 10.6084/m9.figshare.6401516.v1 , 10.6084/m9.figshare.6401516
Genome-wide predictions of cis-regulatory regions for all six cell types. (ZIP 20400 kb)
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Dataset . 2018
License: https://creativecommons.org/licenses/by/4.0/legalcode
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Dataset . 2018
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Dataset . 2018
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Dataset . 2018
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Additional file 5: Table S5. of The signature of liver cancer in immune cells DNA methylation
Research datakeyboard_double_arrow_right Dataset 2018figshare CIHR
Authors: Yonghong Zhang; Petropoulos, Sophie; Jinhua Liu; Cheishvili, David; +5 Authors
Yonghong Zhang; Petropoulos, Sophie; Jinhua Liu; Cheishvili, David; Zhou, Rudy; Dymov, Sergiy; Li, Kang; Li, Ning; Szyf, Moshe;
doi: 10.6084/m9.figshare.5802207.v1
doi: 10.6084/m9.figshare.5802207.v1
Differentially methylated sites between Stage 4 HCC and healthy controls. (CSV 3562 kb)
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Dataset . 2018
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Dataset . 2018
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Additional file 7 of Contribution of genetic and epigenetic changes to escape from X-chromosome inactivation
Research datakeyboard_double_arrow_right Dataset 2022figshare CIHR
Authors: Balaton, Bradley P.; Brown, Carolyn J.;
Balaton, Bradley P.; Brown, Carolyn J.;
doi: 10.6084/m9.figshare.20375875.v1 , 10.6084/m9.figshare.20375875
doi: 10.6084/m9.figshare.20375875.v1 , 10.6084/m9.figshare.20375875
Additional file7: Table S18. DNAmeQTL analysis for the loci significantly associated with DNAme-based XCI status calls. See additional files. These loci were independently tested as DNAmeQTLs in females and males, with some columns color coded based on sex (pink female, light blue male). There are also columns with the median and mean DNAme value at the gene’s island for samples with the reference or alternate allele at that loci; these columns are color coded based on whether the allele is in the range to escape from XCI (DNAme<0.01, blue) or in the range to be subject to XCI (DNAme>0.15, orange). There are mean and median columns for both males and females, but only the female columns are color coded based on XCI status. There are boxes around the genes with female median values with one allele in the range to escape XCI and the other allele in the range to be subject to XCI.
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Dataset . 2022
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Dataset . 2022
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Dataset . 2022
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Additional file 4 of Cdk5-mediated JIP1 phosphorylation regulates axonal outgrowth through Notch1 inhibition
Research datakeyboard_double_arrow_right Dataset 2022figshare CIHR
Authors: Im, Doo Soon; Joselin, Alvin; Svoboda, Devon; Takano, Tesuya; +7 Authors
Im, Doo Soon; Joselin, Alvin; Svoboda, Devon; Takano, Tesuya; Rousseaux, Maxime W. C.; Callaghan, Steve; Slack, Ruth S.; Hisanaga, Shin-ichi; Davis, Roger J.; Park, David S.; Qu, Dianbo;
doi: 10.6084/m9.figshare.19785743.v1 , 10.6084/m9.figshare.19785743
doi: 10.6084/m9.figshare.19785743.v1 , 10.6084/m9.figshare.19785743
Additional file 4. Individual data values.
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Dataset . 2022
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Dataset . 2022
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Additional file 3 of DM-PhyClus: a Bayesian phylogenetic algorithm for infectious disease transmission cluster inference
Research datakeyboard_double_arrow_right Dataset 2018figshare CIHR, NSERC
Authors: Villandré, Luc; Labbe, Aurélie; Brenner, Bluma; Roger, Michel; +1 Authors
Villandré, Luc; Labbe, Aurélie; Brenner, Bluma; Roger, Michel; Stephens, David A;
doi: 10.6084/m9.figshare.7091165.v1 , 10.6084/m9.figshare.7091165
doi: 10.6084/m9.figshare.7091165.v1 , 10.6084/m9.figshare.7091165
This file contains an R object giving the results for the scenario in the simulation study where the concentration parameter prior is assumed to have mean 10 and we use the MAP topology. The file is compressed in gzip format. (GZ 8365 kb)
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Dataset . 2018
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Dataset . 2018
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Dataset . 2018
License: https://creativecommons.org/licenses/by/4.0/legalcode
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Dataset . 2018
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Additional file 1 of Who or what is to blame? Examining sociodemographic relationships to beliefs about causes, control, and responsibility for cancer and chronic disease prevention in Alberta, Canada
Research datakeyboard_double_arrow_right Dataset 2021figshare CIHR
Authors: Curtin, Kimberley D.; Thomson, Mathew; Nykiforuk, Candace I. J.;
Curtin, Kimberley D.; Thomson, Mathew; Nykiforuk, Candace I. J.;
doi: 10.6084/m9.figshare.14721944.v1 , 10.6084/m9.figshare.14721944
doi: 10.6084/m9.figshare.14721944.v1 , 10.6084/m9.figshare.14721944
Additional file 1. An additional table is available describing the variables and regression results included in each binary logistic regression model created for each survey question separated by imputed and complete case datasets. The file name is “BLR-Additional Table 1-BMC.xlsx” and it titled “Logistic Regression Models”.
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Dataset . 2021
License: https://creativecommons.org/licenses/by/4.0/legalcode
Data sources: Datacite
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Dataset . 2021
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Dataset . 2021
License: https://creativecommons.org/licenses/by/4.0/legalcode
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Dataset . 2021
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Additional file 4 of Mitochondrial DNA copy number can influence mortality and cardiovascular disease via methylation of nuclear DNA CpGs
Research datakeyboard_double_arrow_right Dataset 2020figshare CIHR
Authors: Castellani, Christina A.; Longchamps, Ryan J.; Sumpter, Jason A.; Newcomb, Charles E.; +20 Authors
Castellani, Christina A.; Longchamps, Ryan J.; Sumpter, Jason A.; Newcomb, Charles E.; Lane, John A.; Grove, Megan L.; Bressler, Jan; Brody, Jennifer A.; Floyd, James S.; Bartz, Traci M.; Taylor, Kent D.; Penglong Wang; Tin, Adrienne; Coresh, Josef; Pankow, James S.; Fornage, Myriam; Guallar, Eliseo; O’Rourke, Brian; Pankratz, Nathan; Chunyu Liu; Levy, Daniel; Sotoodehnia, Nona; Boerwinkle, Eric; Arking, Dan E.;
doi: 10.6084/m9.figshare.13018026 , 10.6084/m9.figshare.13018026.v1
doi: 10.6084/m9.figshare.13018026 , 10.6084/m9.figshare.13018026.v1
Additional file 4: Table S3. A. Results for 34 independent ARIC Discovery Meta-Analysis identified mtDNA-CN associated CpGs across all studied cohorts and Validation Meta-Analysis/All Cohort Meta-Analysis. Validation meta-analysis included CHS AA, CHS EA and FHS EA cohorts (P
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Dataset . 2020
License: https://creativecommons.org/licenses/by/4.0/legalcode
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Dataset . 2020
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Dataset . 2020
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Dataset . 2020
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Research data supporting "Common variation in genes encoding small GTPases and ovarian cancer risk": GTPases candidate gene SNP genotypes
Research datakeyboard_double_arrow_right Dataset 2018Embargo end date: 08 Mar 2018 United Kingdom Apollo - University of Cambridge Repository NIH | USC COMPREHENSIVE CANCER ..., NIH | GENETIC EPIDEMIOLOGY OF O..., NIH | Core--Tissue Banking and ...
Authors: Pharoah, PDP;
Pharoah, PDP;
doi: 10.17863/cam.20843
doi: 10.17863/cam.20843
Genotype data and related phenotype data for Ovarian Cancer Association Consortium project investigating common variantion in GTPAse genes and ovarian cancer risk
Apolloarrow_drop_down
Apollo
Dataset . 2018
License: https://creativecommons.org/licenses/by/4.0/legalcode
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Apollo
Dataset
License: https://creativecommons.org/licenses/by/4.0/
Data sources: Apollo
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Dataset . 2018
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Apollo
Dataset
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Additional file 2: of The parameter sensitivity of random forests
Research datakeyboard_double_arrow_right Dataset 2016Figshare CIHR
Authors: Huang, Barbara; Boutros, Paul;
Huang, Barbara; Boutros, Paul;
doi: 10.6084/m9.figshare.c.3626282_d2 , 10.6084/m9.figshare.c.3626282_d2.v1
doi: 10.6084/m9.figshare.c.3626282_d2 , 10.6084/m9.figshare.c.3626282_d2.v1
AUC results for low p/n data. Low p/n results for prediction accuracy using AUC as the performance metric for non-cross-validation results, 10-fold cross-validation and stratified 10-fold cross-validation. Ranks indicate the relative performance of different models with lower ranks representing higher performing models i.e., a rank of 1 is the best model. The default settings (n tree = 500, m try = 3, sampsize = 720) are found on row 1502 of the table. (CSV 116 kb)
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Dataset . 2016
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Dataset . 2016
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Dataset . 2016
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Dataset . 2016
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Testing the feasibility of a clinical trial comparing a pre-surgery medication cocktail and nerve-numbing injections for pain management after minimally invasive shoulder surgery
Research datakeyboard_double_arrow_right Dataset 2019Springer Science and Business Media LLC CIHR
Authors: Ana Velly;
Ana Velly;
doi: 10.1186/isrctn14069845
doi: 10.1186/isrctn14069845
https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1186/isrctn...
Dataset . 2019
Data sources: Crossref
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Additional file 3 of DM-PhyClus: a Bayesian phylogenetic algorithm for infectious disease transmission cluster inference

Additional file 1 of Who or what is to blame? Examining sociodemographic relationships to beliefs about causes, control, and responsibility for cancer and chronic disease prevention in Alberta, Canada

Additional file 4 of Mitochondrial DNA copy number can influence mortality and cardiovascular disease via methylation of nuclear DNA CpGs

Research data supporting "Common variation in genes encoding small GTPases and ovarian cancer risk": GTPases candidate gene SNP genotypes

Additional file 2: of The parameter sensitivity of random forests

Testing the feasibility of a clinical trial comparing a pre-surgery medication cocktail and nerve-numbing injections for pain management after minimally invasive shoulder surgery

Additional file 2 of Genome-wide prediction of cis-regulatory regions using supervised deep learning methods

Additional file 5: Table S5. of The signature of liver cancer in immune cells DNA methylation

Additional file 7 of Contribution of genetic and epigenetic changes to escape from X-chromosome inactivation

Additional file 4 of Cdk5-mediated JIP1 phosphorylation regulates axonal outgrowth through Notch1 inhibition

Additional file 3 of DM-PhyClus: a Bayesian phylogenetic algorithm for infectious disease transmission cluster inference

Additional file 1 of Who or what is to blame? Examining sociodemographic relationships to beliefs about causes, control, and responsibility for cancer and chronic disease prevention in Alberta, Canada

Additional file 4 of Mitochondrial DNA copy number can influence mortality and cardiovascular disease via methylation of nuclear DNA CpGs

Research data supporting "Common variation in genes encoding small GTPases and ovarian cancer risk": GTPases candidate gene SNP genotypes

Additional file 2: of The parameter sensitivity of random forests

Testing the feasibility of a clinical trial comparing a pre-surgery medication cocktail and nerve-numbing injections for pain management after minimally invasive shoulder surgery

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