Question: Detecting copy number alterations based on RNA-seq data
gravatar for igor
19 months ago by
United States
igor7.6k wrote:

I've seen a few papers use RNA-seq data to detect CNVs. However, it's always using "custom scripts" in my experience. Is there a publicly available tool for performing that analysis?

I found inferCNV, but that is designed for single-cell data which will have a very different profile from bulk RNA-seq and have a lot more replicates.

cnv rna-seq copy number • 2.2k views
ADD COMMENTlink modified 5 months ago by bhaas110 • written 19 months ago by igor7.6k
gravatar for igor
12 months ago by
United States
igor7.6k wrote:

I just found HoneyBADGER, another method for single-cell RNA-seq:

HoneyBADGER (hidden Markov model integrated Bayesian approach for detecting CNV and LOH events from single-cell RNA-seq data) identifies and infers the presence of CNV and LOH events in single cells and reconstructs subclonal architecture using allele and expression information from single-cell RNA-sequencing data.

ADD COMMENTlink written 12 months ago by igor7.6k

There is also CONICS:

CONICSmat is an R package that can be used to identify CNVs in single cell RNA-seq data from a gene expression table, without the need of an explicit normal control dataset. CONICSmat works with either full transcript (e.g. Fluidigm C1) or 5'/3' tagged (e.g. 10X Genomics) data.

ADD REPLYlink written 7 months ago by igor7.6k

Yet another option is CaSpER:

CaSpER is an algorithm for identification, visualization and integrative analysis of CNV events in multiscale resolution using single-cell or bulk RNA sequencing data.

ADD REPLYlink written 4 months ago by igor7.6k
gravatar for bhaas
5 months ago by
United States
bhaas110 wrote:

The InferCNV software aims to make the Tirosh & Regev method available as a toolkit:

ADD COMMENTlink written 5 months ago by bhaas110
gravatar for Chris Miller
19 months ago by
Chris Miller20k
Washington University in St. Louis, MO
Chris Miller20k wrote:

To my amazement, Aviv Regev's lab did it, but I cannot find the paper at the moment (please link it here if you find it!). Suffice to say, it's a complex process, and one which produces only very rough outlines of the CN landscape. You will probably only pick up very large events (multi-Mb), and it will likely depend on having a large cohort with which to average out the noise inherent in expression.

ADD COMMENTlink written 19 months ago by Chris Miller20k

Is this the paper you are referring to?

ADD REPLYlink written 19 months ago by cbst150

Yeah, I saw Aviv talk at a conference, but that seems like the right paper. Even more flabbergasted that it works with single-cell RNAseq. Amazing stuff!

ADD REPLYlink written 19 months ago by Chris Miller20k
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