Software Application Profile: PHESANT: a tool for performing automated phenome scans in UK Biobank

Abstract

MotivationEpidemiological cohorts typically contain a diverse set of phenotypes such that automation of phenome scans is non-trivial, because they require highly heterogeneous models. For this reason, phenome scans have to date tended to use a smaller homogeneous set of phenotypes that can be analysed in a consistent fashion. We present PHESANT (PHEnome Scan ANalysis Tool), a software package for performing comprehensive phenome scans in UK Biobank.General featuresPHESANT tests the association of a specified trait with all continuous, integer and categorical variables in UK Biobank, or a specified subset. PHESANT uses a novel rule-based algorithm to determine how to appropriately test each trait, then performs the analyses and produces plots and summary tables.ImplementationThe PHESANT phenome scan is implemented in R. PHESANT includes a novel Javascript D3.js visualization and accompanying Java code that converts the phenome scan results to the required JavaScript Object Notation (JSON) format.AvailabilityPHESANT is available on GitHub at [https://github.com/MRCIEU/PHESANT]. Git tag v0.5 corresponds to the version presented here.

Cancer PRSweb – an Online Repository with Polygenic Risk Scores (PRS) for Major Cancer Traits and Their Phenome-wide Exploration in Two Independent Biobanks

“…Alternative and growing sources for publicly available GWAS summary statistics across a large ensemble of diseases use UK Biobank genotype and phenotype data [16], adjusting for population stratification and/or relatedness between individuals ( [17]; http://www.nealelab.is/uk-biobank and https://www.leelabsg.org/resources). These biobank-based approaches accessed thousands of phenotypes and traits that were defined in efficient automated fashion, e.g., by ICD10 diagnosis category, with specific phenotype defining algorithms like PHESANT [18] or PHEWAS CODES [19], or even with consortium-based curated phenotype constructs using the content of the electronic health records (EHR) (FINNGEN; https://www.finngen.fi/en/researchers/clinicalendpoints).…”

“…http://www.nealelab.is/uk-biobank and https://www.leelabsg.org/resources). These biobank-based approaches accessed thousands of phenotypes and traits that were defined in efficient automated fashion, e.g., by ICD10 diagnosis category, with specific phenotype defining algorithms like PHESANT [18] or PHEWAS CODES [19], or even with consortium-based curated phenotype constructs using the content of the electronic health records (EHR) (FINNGEN; https://www.finngen.fi/en/researchers/clinical-endpoints).…”

Low-frequency variation in TP53 has large effects on head circumference and intracranial volume

“…Finally, we characterized the TP53 association signals for final HC and combined final ICV+HC phenotypically using a phenome-wide scan in the UK Biobank, as implemented in PHESANT [29] (rs35850753: Supplementary Table S18; rs78378222: Supplementary Table S19). For rs35850753, standing height is increased by 0.012 cm (SE=0.002) and sitting height by 0.015 cm (SE=0.003) for each increase in minor effect allele.…”

“…To characterize the phenotypic spectrum of identified HC signals, we conducted a phenome scan on 2,143 phenotypes in the UK Biobank cohort [66], using PHESANT [29] software. Analyses were restricted to participants of UK ancestry (UK Biobank specified variable).…”

GWAS meta-analysis highlights the hypothalamic-pituitary-gonadal axis (HPG axis) in the genetic regulation of menstrual cycle length

“…This question was asked of women who had indicated they were not menopausal and still had menstrual periods in their answer to data field 2724 ("Have you had your menopause (periods stopped)?"). The phenotype was transformed according to the default PHESANT pipeline [37], whereby the integer phenotype is split into three ordered bins if a single value represents >20% of all respondents answers. As a result, length of menstrual cycle was split into <26, 26-28, and…”