Torna ai risultati
Scheda bibliografica · Consultazione e accesso
Artículo

The MR-Base platform supports systematic causal inference across the human phenome

Gibran Hemani; Jie Zheng; Benjamin Elsworth; Kaitlin H. Wade; Valeriia Haberland; Denis Baird; Charles Laurin; Stephen Burgess · eLife · 2018

Pagina della risorsa
Lettura rapida. Controlla i dati essenziali della risorsa e accedi al contenuto con il pulsante principale. La scheda mostra solo le informazioni necessarie per identificare, citare e aprire l’opera.

Accesso alla risorsa

Apri il contenuto dall’opzione principale o scegli un’altra fonte disponibile.

OpenAlex OpenAlex Works
Entrar por OpenAlex
Accesso principale

Pagina della risorsa

Pagina di riferimento della risorsa. La disponibilità del testo completo non è stata confermata automaticamente.
Apri risorsa

Riepilogo

Descripción general del contenido del recurso.

Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly and GWAS results are often insufficiently curated, undermining efficient implementation of the approach. We therefore developed MR-Base (<ext-link ext-link-type="uri" xlink:href="http://www.mrbase.org">http://www.mrbase.org</ext-link>): a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR. The software includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions. The database currently comprises 11 billion single nucleotide polymorphism-trait associations from 1673 GWAS and is updated on a regular basis. Integrating data with software ensures more rigorous application of hypothesis-driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome-wide association studies.

Come citare

Elegí el formato que necesitás y copiá la referencia al portapapeles.

APA 7

Hemani, G, Zheng, J, Elsworth, B, Wade, K. H, Haberland, V, Baird, D, Laurin, C, & Burgess, S. (2018). The MR-Base platform supports systematic causal inference across the human phenome. https://doi.org/10.7554/elife.34408

MLA

Hemani, Gibran, et al. "The MR-Base platform supports systematic causal inference across the human phenome." 2018. https://doi.org/10.7554/elife.34408.

Chicago

Hemani, Gibran, Jie Zheng, Benjamin Elsworth, Kaitlin H. Wade, Valeriia Haberland, Denis Baird, Charles Laurin, and Stephen Burgess. 2018. "The MR-Base platform supports systematic causal inference across the human phenome.". https://doi.org/10.7554/elife.34408.

Harvard

Hemani, G. et al. 2018, The MR-Base platform supports systematic causal inference across the human phenome, eLife, available at: https://doi.org/10.7554/elife.34408 [Accessed 8 Aug. 2026].

Condividi e stampa

Salva la scheda, copia il link permanente o stampala in PDF.

Esporta riferimento

Esporta il record nei formati più comuni per usarlo con un gestore bibliografico.

Dettagli della risorsa

Informazioni bibliografiche utili per verificare che sia il materiale corretto.

Titolo
The MR-Base platform supports systematic causal inference across the human phenome
Autore / collaboratori
Gibran Hemani; Jie Zheng; Benjamin Elsworth; Kaitlin H. Wade; Valeriia Haberland; Denis Baird; Charles Laurin; Stephen Burgess
Editore
eLife
Anno di pubblicazione
2018
Lingua
Inglés

Soggetti

Esplora risorse correlate a partire da questi soggetti.

Copiato