Skip to main content


Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Figure 2 | Breast Cancer Research

Figure 2

From: Novel image analysis approach for quantifying expression of nuclear proteins assessed by immunohistochemistry: application to measurement of oestrogen and progesterone receptor levels in breast cancer

Figure 2

Threshold identification and validation for oestrogen receptor and progesterone receptor data, and marker heterogeneity assessment. Random forest clustering (RFC) clusters generated using automated quantitative oestrogen receptor (ER) and progesterone receptor (PR) data in Cohort I (test set): negative cluster and positive cluster for (a) the ER and (b) the PR. (c) ER RFC and (d) PR RFC in Cohort II (validation cohort). (e) Scatter plot demonstrating strong correlation between duplicate ER cores, indicating a homogenous pattern of expression. (f) Scatter plot showing weaker correlation between duplicate PR cores, indicating a more heterogeneous pattern of expression.

Back to article page