Searching the RRID Resource Information Network
Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
URL: https://choishingwan.gitlab.io/EraSOR/
Proper Citation: EraSOR (RRID:SCR_023544)
Description: Software Python tool for removing bias introduced from having overlapped samples between base GWAS data and target genotype data for Polygenic Risk Score analyses. Used for adjusting inflation in PRS prediction and association statistics in presence of sample overlap or close relatedness between GWAS and target samples.
Synonyms: Erase Sample Overlap and Relatedness
Resource Type: data analysis software, data processing software, software application, software resource
Defining Citation: DOI:10.1101/2021.12.10.472164
Keywords: removing bias, overlapped samples, GWAS data, target genotype data, Polygenic Risk Score, PRS prediction and association statistics,
Expand AllWe found {{ ctrl2.mentions.all_count }} mentions in open access literature.
We have not found any literature mentions for this resource.
We are searching literature mentions for this resource.
Most recent articles:
{{ mention._source.dc.creators[0].familyName }} {{ mention._source.dc.creators[0].initials }}, et al. ({{ mention._source.dc.publicationYear }}) {{ mention._source.dc.title }} {{ mention._source.dc.publishers[0].name }}, {{ mention._source.dc.publishers[0].volume }}({{ mention._source.dc.publishers[0].issue }}), {{ mention._source.dc.publishers[0].pagination }}. (PMID:{{ mention._id.replace('PMID:', '') }})
Check
for all resource mentions.
A list of researchers who have used the resource and an author search tool
A list of researchers who have used the resource and an author search tool. This is available for resources that have literature mentions.
No rating or validation information has been found for EraSOR.
No alerts have been found for EraSOR.
Source: SciCrunch Registry
The NIDDK Information Network (dkNET) serves the needs of basic and clinical investigators by providing seamless access to large pools of data and research resources relevant to the mission of The National Institute of Diabetes Digestive and Kidney Diseases (NIDDK). dkNET is hosted at University of California San Diego, and is supported by NIH NIDDK grant U24DK097771.
Email: info_at_ dknet.org
