A statistical framework and computational procedure for identifying
the sub-populations within a tumor, determining the mutation profiles of each
subpopulation, and inferring the tumor’s phylogenetic history. The input are
variant allele frequencies (VAFs) of somatic single nucleotide alterations
(SNAs) along with allele-specific coverage ratios between the tumor and matched
normal sample for somatic copy number alterations (CNAs). These quantities can
be directly taken from the output of existing software. Canopy provides a
general mathematical framework for pooling data across samples and sites to
infer the underlying parameters. For SNAs that fall within CNA regions, Canopy
infers their temporal ordering and resolves their phase. When there are
multiple evolutionary configurations consistent with the data, Canopy outputs
all configurations along with their confidence assessment.
Installation
Install the current release from CRAN (not recommended)
install.packages('Canopy')
Install the devel version from GitHub (installation/update from GitHub HIGHLY recommended)
Jiang, Y., Qiu, Y., Minn, A.J. and Zhang, N.R., 2016. Assessing intratumor heterogeneity and tracking longitudinal and spatial clonal evolutionary history by next-generation sequencing. Proceedings of the National Academy of Sciences. [html, pdf]
It is HIGHLY recommended that the users read the common questions below carefully before applying Canopy and posting questions in the Google user group.
Canopy
Accessing Intra-Tumor Heterogeneity and Tracking Longitudinal and Spatial Clonal Evolutionary History by Next-Generation Sequencing
Author
Yuchao Jiang, Nancy R. Zhang
Maintainer
Yuchao Jiang yuchaoj@email.unc.edu
Description
A statistical framework and computational procedure for identifying the sub-populations within a tumor, determining the mutation profiles of each subpopulation, and inferring the tumor’s phylogenetic history. The input are variant allele frequencies (VAFs) of somatic single nucleotide alterations (SNAs) along with allele-specific coverage ratios between the tumor and matched normal sample for somatic copy number alterations (CNAs). These quantities can be directly taken from the output of existing software. Canopy provides a general mathematical framework for pooling data across samples and sites to infer the underlying parameters. For SNAs that fall within CNA regions, Canopy infers their temporal ordering and resolves their phase. When there are multiple evolutionary configurations consistent with the data, Canopy outputs all configurations along with their confidence assessment.
Installation
Install the current release from CRAN (not recommended)
Install the devel version from GitHub (installation/update from GitHub HIGHLY recommended)
Demo Code & Vignettes
Citation
Jiang, Y., Qiu, Y., Minn, A.J. and Zhang, N.R., 2016. Assessing intratumor heterogeneity and tracking longitudinal and spatial clonal evolutionary history by next-generation sequencing. Proceedings of the National Academy of Sciences. [html, pdf]
Google User Group (Q&A)
If you have any questions with the package, please feel free to post in our Google user group https://groups.google.com/d/forum/canopy_phylogeny or email us at canopy_phylogeny@googlegroups.com. We will try our best to reply as soon as possible.
Common Questions
It is HIGHLY recommended that the users read the common questions below carefully before applying Canopy and posting questions in the Google user group.
How do I generate SNA and CNA input for Canopy?
Which CNAs and SNAs should I use?
How do I cluster the SNAs?
What is matrix C? How do I deal with overlapping CNAs?
Error in config.summary/canopy.post?
What if I only have SNA input?
How do I get cancer cell fractions (CCFs) for the SNAs?