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authorPjotr Prins2023-10-16 13:43:52 -0500
committerPjotr Prins2023-10-16 13:43:52 -0500
commit6e20f14178a260bc189a0e4df632859d1d6479d6 (patch)
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parent0069b5247c02a5d78beadb8325ec335841aa758d (diff)
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MSK home
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New MSK portal! This is initial work for providing a full community webservice for MSK.
-See this link to [edit](https://github.com/genenetwork/gn-docs/edit/master/general/brand/msk/home.md).
+With this portal we aim to unlock the potential of a massive body of genetic and genomic data from mouse and rat genetic reference populations (GRPs) and outbred stocks generated by the musculoskeletal (MSK) research community.
+Much of what we know about MSK biology today has been discovered through the use of model organisms.
+These model organisms give new insights into evolutionary shared traits and allow for experiments and treatments in controlled conditions.
+This will help solidify the NIH vision on how such research can ultimately improve human health.
+Our focus is on harvesting, restructuring, and (re-)analyzing data from key NIH/NIAMS projects by and for the MSK research communities.
+This will enable far more powerful integration of results from human genomics and genome-wide association studies (GWAS) with mechanistic, molecular, cellular, and genotype-environment interaction (GxE) data from mouse and rat.
-For markdown check [the docs](https://commonmark.org/help/). To embed images you can use a link somewhere from the internet or check it into the gn-doc repo and we'll add a link.
+For providing FAIR+ data and compute we host [GeneNetwork.org](https://genenetwork.org) (GN), its servers and our Octopus HPC (see [facilities](https://genenetwork.org/facilities/)).
+Over the past 25 years GN has evolved into a unique web service for omics data curation, trait and eQTL mapping, systems genetics, network analysis, and even causal modelling. GN is used by the wider mouse and rat research community and has accumulated over 10,000 curated datasets and over 1,500 publications that used the service. GN includes studies on bone femur mRNA and muscle mRNA datasets, for example, that have resulted in ~40 MSK publications, including NIAMS funded GWAS.
+
+We note that thousands of human GWAS have used large cohorts to link variation in disease risk to tens-of-thousands of loci and SNPs.
+These forward genetic studies highlight *loci* and candidate genes related to variant phenotypes (often dichotomous cases vs control), but do not provide insight into mechanisms or treatment.
+Meanwhile, other research communities focused on model organisms have built up impressive genetic and genomic resources and mechanistic insights. Most of these studies have used tightly controlled experimental and genetic perturbations in mouse and rat, among other species.
+
+Bridging this mass of heterogeneous experimental data in a way that integrates mechanistically with GWAS and that impacts human health is a fundamental challenge.
+Because GN is a fully open and public FAIR+ project it brings together these two great areas of research by providing a service that unlocks data and compute and makes it accessible to the community and beyond.