Large-scale labeling and assessment of sex bias in publicly available expression data

Large-scale labeling and assessment of sex bias in publicly available expression data

Background: Women are at more than 1.5-fold higher risk for clinically relevant adverse drug events. While this higher prevalence is partially due to gender-related effects, biological sex differences likely also impact drug response. Publicly available gene expression databases provide a unique opp...

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Bibliographic Details
Main Authors: Altman, R.B (Author), Chang, A. (Author), Flynn, E. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
animal
Animals
Bias
Cell culture
Cell lines
Cellular levels
Databases, Factual
Drug response
Expression data
factual database
female
Female
gene expression
Gene expression
Gene Expression
Gene Expression Data
genetics
Human cancer
male
Male
Mammals
metadata
Metadata
Mice
mouse
neoplasm
Neoplasms
Sampling bias
Sex difference
sex factor
Sex Factors
statistical bias
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Internet

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