Sentence examples for categorised expression from inspiring English sources

The association between categorised expression of an individual gene and stage was examined using Fisher's exact test.

The relations between categorised expression data (differential expression [DE] ≥ 1.60; 1.60 > DE > – 1.60; DE ≤ – 1.60) and gene association with tumour ER status (positive or negative) were tested by Spearman rank correlation.

The association between categorised expression of COL11A1 and PFS or OS remained statistically significant even after adjusting for tumour stage (Table 5, adjusted HR=1.237, 95% CI=1.058 1.448, P=0.008 or adjusted HR=1.373, 95% CI=1.126 1.674, P=0.002, respectively).

As the prevalence of positive expression scores (cumulative scores 2 7) was low for HGF and c-Met, we chose to categorise expression as negative (0) vs positive (2 7).

Therefore, miRNA expression levels were categorised using quartiles with expression within the first quartile defined as 'low', 'med' when expression was in the second and third quartiles and otherwise 'high'high

For statistical analysis, the grades 0 and +1 were categorised as negative expression and grades +2 and +3 as positive expression.

The patients were categorised as high expression if the staining intensity was 3+, they were considered as low expression.

The expression was categorised as follows: absence (no expression); low (less than 25% of cells); moderate (between 25%and75%5% of cells) or high (more than 75% of cells).

Therefore, we compared focal expression (<25%) (categorised to the PRLR low expression group) vs moderate and/or extensive expression (categorised to the PRLR high expression group) and found that a higher degree of PRLR expression was associated with decreased disease-free and overall survival.

Expression of all markers was previously categorised as loss vs expression for classical HLA class I; no expression vs expression for HLA-E and HLA-G; infiltration absent vs infiltration present for Treg cells; and presence vs absence of PEN5 (de Kruijf et al, 2010a, 2010b, 2013).

A univariate Cox model with overall survival as the dependent variable was constructed and categorised with gene expression levels as independent variables, and the genes that were significant in the univariate analysis were included in a multivariate Cox proportional hazards model for survival.