Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

. 2024 Feb 20;15:1551. doi: 10.1038/s41467-024-45000-z

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

© The Author(s) 2024

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

PMC Copyright notice

Fig. 2 — Correlation matrices were built to highlight direct correlations between genomic variables. All aberrations (with frequency>5%) were included in the analysis for (a) BO dataset, n = 513 patients, and (b) CoMMpass dataset, n = 752 patients; rare aberrations were excluded from the plot but not from the analyses, to avoid an excessive scattering of the correlation matrix. The heatmap resumed results coming from Pearson correlation tests, performed for each couple of variables, as called when detected within a clonality range between 50% and 100%, as defined above. Direct and indirect correlations were both highlighted in red and blue, and defined by the ovals’ orientation (left-oriented and right-oriented ovals highlight direct and indirect correlations, respectively); the ovals’ transparency identified the correlation’s strength (strong and weak correlations are bold and light coloured, respectively). An X highlighted not-significant correlations (two-sided p > 0.05). The approach to multiple testing correction is described in methods section (Co-occurrence analysis).