Related Experiment Video
Updated: Jun 3, 2026

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR
Published on: July 11, 2025
A pseudo-R2 measure for selecting genomic markers with crossing hazards functions
Sigrid Rouam1, Thierry Moreau, Philippe Broët
1Genome Institute of Singapore, Biopolis, Singapore. sigrid.rouam@inserm.fr
Background:
In genomic medical studies, one of the major objectives is to identify genomic factors with a prognostic impact on time-to-event outcomes so as to provide new insights into the disease process. Selection usually relies on statistical univariate indices based on the Cox model. Such model assumes proportional hazards (PH) which is unlikely to hold for each genomic marker.
Methods:
In this paper, we introduce a novel pseudo-R2 measure derived from a crossing hazards model and designed for the selection of markers with crossing effects. The proposed index is related to the score statistic and quantifies the extent of a genomic factor to separate patients according to their survival times and marker measurements. We also show the importance of considering genomic markers with crossing effects as they potentially reflect the complex interplay between markers belonging to the same pathway.
Results:
Simulations show that our index is not affected by the censoring and the sample size of the study. It also performs better than classical indices under the crossing hazards assumption. The practical use of our index is illustrated in a lung cancer study. The use of the proposed pseudo-R2 allows the identification of cell-cycle dependent genes not identified when relying on the PH assumption.
Conclusions:
The proposed index is a novel and promising tool for selecting markers with crossing hazards effects.
Related Concept Videos
Hazard Ratio
For example, in a clinical trial evaluating a...
Genome-wide Association Studies-GWAS
GWAS does not require the identification of the target gene involved in...
Crossing Over
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Chi-square Analysis
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
Relative Risk
