sample.annot

Human papillomavirus (HPV) infection status for the n = 279 patients with head and neck
squamous cell carcinoma in the The Cancer Genoma Atlas cohort.

datasets

Pearson and Spearman correlation coefficients are commonly used to quantify the strength
of bivariate associations of genomic variables. For example, correlations of gene-level
DNA copy number and gene expression measurements may be used to assess the impact of
DNA copy number changes on gene expression in tumor tissue. 'MVisAGe' enables users to
quickly compute and visualize the correlations in order to assess the effect of regional
genomic events such as changes in DNA copy number or DNA methylation level. Please see
Walter V, Du Y, Danilova L, Hayward MC, Hayes DN, 2018. Cancer Research
<doi:10.1158/0008-5472.CAN-17-3464>.

Vonn Walter

MVisAGe

Compute and Visualize Bivariate Associations

sample.annot function

A matrix with 26417 rows and 3 columns<dl class="dl-horizontal">
<dt>Barcode</dt><dd>sample identifier</dd>
<dt>New.HPV.Status</dt><dd>HPV infection status</dd>
</dl>

Format

Sample annotation data — sample.annot

A matrix with 26417 rows and 3 columns<dl class='dl-horizontal'>
<dt>Barcode</dt><dd>sample identifier</dd>
<dt>New.HPV.Status</dt><dd>HPV infection status</dd>
</dl>

sample.annot: Sample annotation data

Description

Usage

Arguments

Format