cna.call


A dataset containing part of the The Cancer Genome Atlas acute myeloid leukemia
Affymetrix SNP6.0 array copy number alteration calls from GISTIC


datasets

A hierarchical Bayesian approach to assess functional impact of mutations on gene expression in cancer. Given a patient-gene matrix encoding the presence/absence of a mutation, a patient-gene expression matrix encoding continuous value expression data, and a graph structure encoding whether two genes are known to be functionally related, xseq outputs: a) the probability that a recurrently mutated gene g influences gene expression across the population of patients;
and b) the probability that an individual mutation in gene g in an individual patient m influences expression within that patient.

Jiarui Ding

xseq

Assessing Functional Impact on Gene Expression of Mutations in
Cancer

cna.call function

A matrix containing the GISTIC copy number calls of 454 genes in 197 patients:
<ul>
<li>Row names are patient identifiers
  </li>
<li>Colume names are official HGNC gene symbols
</li>
</ul> Each element of the matrix is coded:
<ul>
<li> -2, homozygous deletions
  </li>
<li> -1, hemizygous deletions
  </li>
<li> 0, neutral
  </li>
<li> 1, gain
  </li>
<li> 2, amplifications
  </li>
</ul>

Format

<a href="https://www.synapse.org/#!Synapse:syn300013">https://www.synapse.org/#!Synapse:syn300013</a>

cna.call: TCGA AML SNP6.0 GISTIC copy number alteration calls

Description

Usage

Arguments

Format

Source