Integrated copy number variation detection toolset
Zilu Zhou, Nancy R. Zhang
Zilu Zhou zhouzilu@upenn.edu Please comment on the Issues section for addtional questions.
iCNV is a normalization and copy number variation detection procedure for mutiple study designs: WES only, WGS only, SNP array only, or any combination of SNP and sequencing data. iCNV applies platform specific normalization, utilizes allele specific reads from sequencing and integrates matched NGS and SNP-array data by a Hidden Markov Model (HMM).
# try http:// if https:// URLs are not supported
if (!requireNamespace("BiocManager", quietly=TRUE))
install.packages("BiocManager")
BiocManager::install("CODEX")
# Install iCNV
install.packages("devtools")
library(devtools)
install_github("zhouzilu/iCNV")
iCNV has made a lot of changes on 10/31/2017 for stability, bug fixing and computation power. We strongly recommend you update iCNV to the newest version using the following command. * Update instruction
# Remove iCNV
remove.packages('iCNV')
# reinstall iCNV
install.packages("devtools")
library(devtools)
install_github("zhouzilu/iCNV")
Number in the parentheses referring to different section in Vignettes and function details can be found https://github.com/zhouzilu/iCNV/tree/master/R
NGS | Array
BAM BED(UCSC for WES or bed_generator.R for WGS 2.2) | SNP Intensity(in standard format)
| | | |
|----------------| | |
| | | |icnv_array_input (2.4)
|SAMTools(2.3) |CODEX(2.2) | |
| | | |-----------|
Variants BAF(vcf) PLR | Array LRR Array BAF
| | | | |
| | | |SVD(2.4) |
| | | | |
| | | Normalized LRR |
| | | | |
-----------------------------------------------------------------------------------
|
|iCNV_detection(2.5-2.6)
|
CNV calling
|
|icnv_output_to_gb()
|
Genome Browser input
Zilu Zhou, Weixin Wang, Li-San Wang, Nancy Ruonan Zhang; Integrative DNA copy number detection and genotyping from sequencing and array-based platforms, Bioinformatics, , bty104, https://doi.org/10.1093/bioinformatics/bty104
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.