Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

SurvivalGWAS_SV: software for the analysis of genome-wide association studies of imputed genotypes with "time-to-event" outcomes.

BMC bioinformatics - 19 May 2017

Syed Hamzah, Jorgensen Andrea L, Morris Andrew P

Abstract excerpt

BACKGROUND: Analysis of genome-wide association studies (GWAS) with "time to event" outcomes have become increasingly popular, predominantly in the context of pharmacogenetics, where the survival endpoint could be death, disease remission or the occurrence of an adverse drug reaction. However, methodology and software that can efficiently handle the scale and complexity of genetic data from GWAS with time to...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Computer Simulation
Share to Genome-Wide Association Study

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genotype

Share to Polymorphism, Single Nucleotide

Share to Proportional Hazards Models

Share to Software

Share to Time Factors

Source

Open in PubMed Open full text

Identifiers

PMID: 28525968
DOI: 10.1186/s12859-017-1683-z
PMCID: PMC5438515

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026. Manifest publication-graph-cohort-2026-09-05.1.

Source receipt: pubmed, retrieved 5 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 10 closest

SurvivalGWAS_SV: software for the analysis of genome-wide association studies of imputed genotypes with "time-to-event" outcomes.PMID 28525968Read ↗

SurvivalGWAS_Power: a user friendly tool for power calculations in pharmacogenetic studies with "time to event" outcomes.Semantic proximity Read ↗

rareSurvival: rare variant association analysis for “time-to-event” outcomesSemantic proximity Read ↗

Evaluation of methodology for the analysis of 'time-to-event' data in pharmacogenomic genome-wide association studies.Semantic proximity Read ↗

Power and sample size calculations for SNP association studies with censored time-to-event outcomes.Semantic proximity Read ↗

Kernel machine SNP-set analysis for censored survival outcomes in genome-wide association studies.Semantic proximity Read ↗

Cox regression is robust to inaccurate EHR-extracted event time: an application to EHR-based GWAS.Semantic proximity Read ↗

Tutorial on survival modeling with applications to omics dataSemantic proximity Read ↗

vcf2gwas: Python API for comprehensive GWAS analysis using GEMMA.Semantic proximity Read ↗

Gene-gene interaction analysis for the survival phenotype based on the Cox model.Semantic proximity Read ↗

surviveR: a flexible shiny application for patient survival analysisSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.