This weekend, cardiovascular researchers from around the globe will be meeting in Chicago for the 2018 Scientific Sessions of the American Heart Association. Members of the Knowledge Portal Network team will be there to meet and talk with geneticists and biologists who use the Portals and get your input on how we can improve them.
Please come visit us at booth #2249 in the Exhibit Hall! We'll be there on Saturday, Nov. 10 from 11am-5pm; on Sunday, Nov. 11 from 10am-4:30pm; and on Monday, Nov. 12 from 10am-3pm.
Showing posts with label Cardiovascular Disease Knowledge Portal. Show all posts
Showing posts with label Cardiovascular Disease Knowledge Portal. Show all posts
Wednesday, November 7, 2018
Wednesday, May 2, 2018
Join the Knowledge Portal Network team!
At the Knowledge Portal Network (currently consisting of the Type 2 Diabetes, Cerebrovascular Disease, and Cardiovascular Disease Knowledge Portals), we are looking for energetic, talented people to help us produce web portals that aggregate and serve genetic association results to the world in order to spark insights into complex diseases. There are positions open for a software engineer to help in developing and producing these web portals, and for a technical release manager to manage and coordinate tasks during production and maintenance of the portals.
The positions are located at the Broad Institute in Cambridge, MA, a dynamic and exciting work environment where cutting-edge science is applied to critical biomedical problems.
Find more details and apply for the software engineer or technical release manager positions at the Broad Careers site.
The positions are located at the Broad Institute in Cambridge, MA, a dynamic and exciting work environment where cutting-edge science is applied to critical biomedical problems.
Find more details and apply for the software engineer or technical release manager positions at the Broad Careers site.
Thursday, March 1, 2018
New release today, as the KPN moves to a regular release schedule
At the Knowledge Portal Network (consisting of the Type 2 Diabetes, Cardiovascular Disease, and Cerebrovascular Disease Knowledge Portals), we are establishing a regular bimonthly release schedule. Every other month, new data and features will be incorporated into the Portals. Today, we are pleased to announce the first of these releases.
New data in the Type 2 Diabetes Knowledge Portal
This release adds two new datasets to the T2DKP. The Diabetic Cohort - Singapore Prospective Study Program is a T2D case-control study to identify genetic and environmental risk factors for diabetes in Singapore Chinese. The DC-SP2 GWAS set, a meta-analysis of summary level T2D associations from 3,951 individuals, was contributed by Drs. Rob Martinus Van Dam, E Shyong Tai, and Xueling Sim from the National University of Singapore. They have also submitted individual-level data from this study to the Accelerating Medicines Partnership Data Coordinating Center (AMP DCC), and these data will be incorporated into the T2DKP after quality control and analysis are complete.
In addition to this set, we have incorporated the publicly available summary statistics from the DIAGRAM 1000G GWAS. This dataset, from the DIAGRAM (DIAbetes Genetics Replication And Meta-analysis) consortium, is a meta-analysis of 26,676 T2D cases and 132,532 control participants from 18 GWAS (Scott RA, et al. An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans. (2017) Diabetes 66:2888). Samples were imputed using the all ancestries 1000 Genomes Project reference panel.
More details about both of these datasets are available on our Data page.
New features specific to the Type 2 Diabetes Knowledge Portal
We have expanded the range of data available for interactive analysis by adding individual-level data from the CAMP GWAS, BioMe AMP T2D GWAS, and METSIM GWAS datasets to the dynamic analysis modules LocusZoom and GAIT (Genetic Association Interactive Tool). LocusZoom, powered by the Hail software developed at the Broad Institute as part of the AMP T2D project, allows you to perform custom association analysis while conditioning on specific variants or sets of variants.
GAIT offers alternative options for custom association analysis, such as filtering samples by their phenotypic characteristics (e.g., age, BMI, cholesterol levels) and choosing specific covariates. To date, seven different datasets comprised of over 67,000 samples are available for dynamic analysis in GAIT. These include datasets housed both at the AMP DCC (19k exome sequence analysis; CAMP GWAS; BioMe AMP T2D GWAS; METSIM GWAS) and at the EBI Federated node (EXTEND GWAS; Oxford Biobank exome chip analysis; GoDARTS Affymetrix GWAS).
We have also taken an initial step towards integration of the T2DKP with a new federated node, the T2DREAM database of epigenomic data relevant to T2D. In the near future, epigenomic data displayed in the T2DKP will be drawn dynamically from T2DREAM. In the meantime, we have added gene- and variant-specific links to T2DREAM from the re-styled External Resources section at the bottom of Gene and Variant pages.
New features for all Knowledge Portals
Some of the improvements in this release are visible in all the Portals of the Knowledge Portal Network. One of the most significant affects LocusZoom, the dynamic plot that displays variant associations along with their genomic coordinates, linkage disequilibrium, and other information. Previously, the only way to select a phenotype was to scroll through a long list. Now, a new phenotype filter lets you enter one or more search criteria and filter the list by those criteria. Once you have selected a phenotype, the datasets that include associations for that phenotype are presented for selection. Previously, only one dataset (the one with the largest sample size) was available for each phenotype; now, associations from all relevant datasets may be viewed in LocusZoom.
The sample filtering panel of the user interface for the custom burden test and GAIT (Genetic Association Interactive Tool) has also been improved to make it more intuitive to use. The External Resources sections of Gene and Variant pages have been re-styled, and gene- and variant-specific links to PheWeb have been added. PheWeb displays phenotypes most significantly associated with the gene or variant, based on a GWAS for over 2,400 phenotypes in UK Biobank data that was performed by Ben Neale's group. Finally, the home pages of all the Portals have been redesigned to make the appearance of the disease-specific portals more distinct.
Please browse these new data and features, and let us know what you think!
New data in the Type 2 Diabetes Knowledge Portal
This release adds two new datasets to the T2DKP. The Diabetic Cohort - Singapore Prospective Study Program is a T2D case-control study to identify genetic and environmental risk factors for diabetes in Singapore Chinese. The DC-SP2 GWAS set, a meta-analysis of summary level T2D associations from 3,951 individuals, was contributed by Drs. Rob Martinus Van Dam, E Shyong Tai, and Xueling Sim from the National University of Singapore. They have also submitted individual-level data from this study to the Accelerating Medicines Partnership Data Coordinating Center (AMP DCC), and these data will be incorporated into the T2DKP after quality control and analysis are complete.
In addition to this set, we have incorporated the publicly available summary statistics from the DIAGRAM 1000G GWAS. This dataset, from the DIAGRAM (DIAbetes Genetics Replication And Meta-analysis) consortium, is a meta-analysis of 26,676 T2D cases and 132,532 control participants from 18 GWAS (Scott RA, et al. An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans. (2017) Diabetes 66:2888). Samples were imputed using the all ancestries 1000 Genomes Project reference panel.
New features specific to the Type 2 Diabetes Knowledge Portal
We have expanded the range of data available for interactive analysis by adding individual-level data from the CAMP GWAS, BioMe AMP T2D GWAS, and METSIM GWAS datasets to the dynamic analysis modules LocusZoom and GAIT (Genetic Association Interactive Tool). LocusZoom, powered by the Hail software developed at the Broad Institute as part of the AMP T2D project, allows you to perform custom association analysis while conditioning on specific variants or sets of variants.
GAIT offers alternative options for custom association analysis, such as filtering samples by their phenotypic characteristics (e.g., age, BMI, cholesterol levels) and choosing specific covariates. To date, seven different datasets comprised of over 67,000 samples are available for dynamic analysis in GAIT. These include datasets housed both at the AMP DCC (19k exome sequence analysis; CAMP GWAS; BioMe AMP T2D GWAS; METSIM GWAS) and at the EBI Federated node (EXTEND GWAS; Oxford Biobank exome chip analysis; GoDARTS Affymetrix GWAS).
We have also taken an initial step towards integration of the T2DKP with a new federated node, the T2DREAM database of epigenomic data relevant to T2D. In the near future, epigenomic data displayed in the T2DKP will be drawn dynamically from T2DREAM. In the meantime, we have added gene- and variant-specific links to T2DREAM from the re-styled External Resources section at the bottom of Gene and Variant pages.
New features for all Knowledge Portals
Some of the improvements in this release are visible in all the Portals of the Knowledge Portal Network. One of the most significant affects LocusZoom, the dynamic plot that displays variant associations along with their genomic coordinates, linkage disequilibrium, and other information. Previously, the only way to select a phenotype was to scroll through a long list. Now, a new phenotype filter lets you enter one or more search criteria and filter the list by those criteria. Once you have selected a phenotype, the datasets that include associations for that phenotype are presented for selection. Previously, only one dataset (the one with the largest sample size) was available for each phenotype; now, associations from all relevant datasets may be viewed in LocusZoom.
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| Portion of the updated LocusZoom interface, showing phenotype filtering capability. |
The sample filtering panel of the user interface for the custom burden test and GAIT (Genetic Association Interactive Tool) has also been improved to make it more intuitive to use. The External Resources sections of Gene and Variant pages have been re-styled, and gene- and variant-specific links to PheWeb have been added. PheWeb displays phenotypes most significantly associated with the gene or variant, based on a GWAS for over 2,400 phenotypes in UK Biobank data that was performed by Ben Neale's group. Finally, the home pages of all the Portals have been redesigned to make the appearance of the disease-specific portals more distinct.
Please browse these new data and features, and let us know what you think!
Wednesday, November 15, 2017
T2DKP Fall Newsletter
The latest issue of our quarterly newsletter is now available. Download it here to find out what we've been up to!
Tuesday, November 14, 2017
Announcing the Cardiovascular Disease Knowledge Portal
We are pleased to announce the launch of the Cardiovascular Disease Knowledge Portal (CVDKP). Our collaboration with Dr. Patrick Ellinor, Dr. Sek Kathiresan, and their colleagues in the Atrial Fibrillation, Global Lipids Genetics, Myocardial Infarction Genetics, and CARDIoGRAMPlusC4D consortia has created a resource that offers world-wide open access to genetic and genomic information about atrial fibrillation, myocardial infarction, and related traits, with the goal of democratizing access to genomic data and accelerating cardiovascular genomics research.
The CVDKP is constructed on a software architecture originally developed for the Type 2 Diabetes Knowledge Portal (T2DKP), which is the central product of the Accelerating Medicines Partnership in Type 2 Diabetes (AMP T2D). AMP T2D is a public-private partnership between the National Institutes of Health, the U.S. Food and Drug Administration, biopharmaceutical companies, and non-profit organizations that is managed through the Foundation for the NIH. AMP seeks to harness collective capabilities, scale, and resources toward improving current efforts to develop new therapies for complex, heterogeneous diseases.
The ultimate goal of AMP T2D is to increase the number of new diagnostics and therapies for patients while reducing the time and cost of developing them, by jointly identifying and validating promising biological targets for type 2 diabetes. The T2DKP furthers that goal by aggregating, harmonizing, and displaying genetic association and epigenomic results along with user-friendly analysis tools, allowing research biologists who would not individually be able to amass and manipulate these large datasets to glean insights from the data.
We are working towards these same goals for other complex diseases, by extending the platform and analysis tools constructed for the T2DKP. In partnership with the International Stroke Genetics Consortium, we recently created a Knowledge Portal for cerebrovascular disease (CDKP) based on the same infrastructure. Now, with the advent of the Cardiovascular Disease Knowledge Portal, we have a three-member Knowledge Portal Network for the genetics of cardiometabolic and cerebrovascular disease.
Data in the CVDKP directly relevant to heart disease include genetic associations with atrial fibrillation, electrocardiogram traits, plasma lipid levels, and myocardial infarction. Additional association datasets are available for type 2 diabetes and glycemic traits, anthropometric traits, measures of kidney function, and psychiatric traits. You may browse the complete list of datasets and their descriptions on the CVDKP Data page.
As for the Cerebrovascular Disease Knowledge Portal, in the CVDKP we also continue to work with the American Heart Association Precision Medicine Platform (PMP) to provide an additional avenue for accessing cardiovascular genetic data. Currently, summary statistics from the AFGen GWAS and AFGen exome chip analysis datasets are deposited in the PMP.
We welcome all suggestions, comments, questions, and submission of relevant datasets for the CVDKP. Please contact us at help@cvdgenetics.org!
 |
| CVDKP home page |
The CVDKP is constructed on a software architecture originally developed for the Type 2 Diabetes Knowledge Portal (T2DKP), which is the central product of the Accelerating Medicines Partnership in Type 2 Diabetes (AMP T2D). AMP T2D is a public-private partnership between the National Institutes of Health, the U.S. Food and Drug Administration, biopharmaceutical companies, and non-profit organizations that is managed through the Foundation for the NIH. AMP seeks to harness collective capabilities, scale, and resources toward improving current efforts to develop new therapies for complex, heterogeneous diseases.
The ultimate goal of AMP T2D is to increase the number of new diagnostics and therapies for patients while reducing the time and cost of developing them, by jointly identifying and validating promising biological targets for type 2 diabetes. The T2DKP furthers that goal by aggregating, harmonizing, and displaying genetic association and epigenomic results along with user-friendly analysis tools, allowing research biologists who would not individually be able to amass and manipulate these large datasets to glean insights from the data.
We are working towards these same goals for other complex diseases, by extending the platform and analysis tools constructed for the T2DKP. In partnership with the International Stroke Genetics Consortium, we recently created a Knowledge Portal for cerebrovascular disease (CDKP) based on the same infrastructure. Now, with the advent of the Cardiovascular Disease Knowledge Portal, we have a three-member Knowledge Portal Network for the genetics of cardiometabolic and cerebrovascular disease.
Data in the CVDKP directly relevant to heart disease include genetic associations with atrial fibrillation, electrocardiogram traits, plasma lipid levels, and myocardial infarction. Additional association datasets are available for type 2 diabetes and glycemic traits, anthropometric traits, measures of kidney function, and psychiatric traits. You may browse the complete list of datasets and their descriptions on the CVDKP Data page.
As for the Cerebrovascular Disease Knowledge Portal, in the CVDKP we also continue to work with the American Heart Association Precision Medicine Platform (PMP) to provide an additional avenue for accessing cardiovascular genetic data. Currently, summary statistics from the AFGen GWAS and AFGen exome chip analysis datasets are deposited in the PMP.
We welcome all suggestions, comments, questions, and submission of relevant datasets for the CVDKP. Please contact us at help@cvdgenetics.org!
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