{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:5APCAEFAP2DMYMOKLISAWQWO65","short_pith_number":"pith:5APCAEFA","schema_version":"1.0","canonical_sha256":"e81e2010a07e86cc31ca5a240b42cef741eddd0921f5fffccdd494db937e6e17","source":{"kind":"arxiv","id":"1807.10467","version":1},"attestation_state":"computed","paper":{"title":"VIMCO: Variational Inference for Multiple Correlated Outcomes in Genome-wide Association Studies","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Can Yang, Ching-Yu Cheng, Jin Liu, Xingjie Shi, Xinyi Lin, Yi Yang, Yuling Jiao","submitted_at":"2018-07-27T07:33:10Z","abstract_excerpt":"In Genome-Wide Association Studies (GWAS) where multiple correlated traits have been measured on participants, a joint analysis strategy, whereby the traits are analyzed jointly, can improve statistical power over a single-trait analysis strategy. There are two questions of interest to be addressed when conducting a joint GWAS analysis with multiple traits. The first question examines whether a genetic loci is significantly associated with any of the traits being tested. The second question focuses on identifying the specific trait(s) that is associated with the genetic loci. Since existing me"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1807.10467","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2018-07-27T07:33:10Z","cross_cats_sorted":[],"title_canon_sha256":"cc0e958fafdaa249a7f5340f161001376b6e87d829ec1032bee4cdb17b5965c6","abstract_canon_sha256":"719d28555c4dde3a4ba1106d5b3b17950232b80064ce04ea2df02d4d77943931"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:09:40.500246Z","signature_b64":"3NjFnu+Fkwu49puXOgYOSyUPi9+0S9/jToRp/jYIIP7iWn+mk4U2zO14AP9UFCTRCoZoRb4RDyZkwqtkFp0GBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e81e2010a07e86cc31ca5a240b42cef741eddd0921f5fffccdd494db937e6e17","last_reissued_at":"2026-05-18T00:09:40.499600Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:09:40.499600Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"VIMCO: Variational Inference for Multiple Correlated Outcomes in Genome-wide Association Studies","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Can Yang, Ching-Yu Cheng, Jin Liu, Xingjie Shi, Xinyi Lin, Yi Yang, Yuling Jiao","submitted_at":"2018-07-27T07:33:10Z","abstract_excerpt":"In Genome-Wide Association Studies (GWAS) where multiple correlated traits have been measured on participants, a joint analysis strategy, whereby the traits are analyzed jointly, can improve statistical power over a single-trait analysis strategy. There are two questions of interest to be addressed when conducting a joint GWAS analysis with multiple traits. The first question examines whether a genetic loci is significantly associated with any of the traits being tested. The second question focuses on identifying the specific trait(s) that is associated with the genetic loci. Since existing me"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.10467","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1807.10467","created_at":"2026-05-18T00:09:40.499713+00:00"},{"alias_kind":"arxiv_version","alias_value":"1807.10467v1","created_at":"2026-05-18T00:09:40.499713+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.10467","created_at":"2026-05-18T00:09:40.499713+00:00"},{"alias_kind":"pith_short_12","alias_value":"5APCAEFAP2DM","created_at":"2026-05-18T12:32:08.215937+00:00"},{"alias_kind":"pith_short_16","alias_value":"5APCAEFAP2DMYMOK","created_at":"2026-05-18T12:32:08.215937+00:00"},{"alias_kind":"pith_short_8","alias_value":"5APCAEFA","created_at":"2026-05-18T12:32:08.215937+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/5APCAEFAP2DMYMOKLISAWQWO65","json":"https://pith.science/pith/5APCAEFAP2DMYMOKLISAWQWO65.json","graph_json":"https://pith.science/api/pith-number/5APCAEFAP2DMYMOKLISAWQWO65/graph.json","events_json":"https://pith.science/api/pith-number/5APCAEFAP2DMYMOKLISAWQWO65/events.json","paper":"https://pith.science/paper/5APCAEFA"},"agent_actions":{"view_html":"https://pith.science/pith/5APCAEFAP2DMYMOKLISAWQWO65","download_json":"https://pith.science/pith/5APCAEFAP2DMYMOKLISAWQWO65.json","view_paper":"https://pith.science/paper/5APCAEFA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1807.10467&json=true","fetch_graph":"https://pith.science/api/pith-number/5APCAEFAP2DMYMOKLISAWQWO65/graph.json","fetch_events":"https://pith.science/api/pith-number/5APCAEFAP2DMYMOKLISAWQWO65/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5APCAEFAP2DMYMOKLISAWQWO65/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5APCAEFAP2DMYMOKLISAWQWO65/action/storage_attestation","attest_author":"https://pith.science/pith/5APCAEFAP2DMYMOKLISAWQWO65/action/author_attestation","sign_citation":"https://pith.science/pith/5APCAEFAP2DMYMOKLISAWQWO65/action/citation_signature","submit_replication":"https://pith.science/pith/5APCAEFAP2DMYMOKLISAWQWO65/action/replication_record"}},"created_at":"2026-05-18T00:09:40.499713+00:00","updated_at":"2026-05-18T00:09:40.499713+00:00"}