Question: CIBERSORT deconvolution advice
gravatar for joker33
8 months ago by
joker3320 wrote:

Dear community,

I was wondering if any of you could give me some advice with the following issues:

  1. All results are different when performing "absolute" deconvolution using legacy CIBERSORT source code R version (no.sumto1 & sig.score), legacy CIBERSORT online tool and the online CIBERSORTx tool (see example copied below). Has there been a change in the code between versions?
  2. I have very large matrices to deconvolute (up to 780MB). Is it possible to split up matrices for deconvolution of samples I want to compare?
  3. How does CIBERSORT accomplish to exclude non-hematopoietic genes during signature matrix genetartion? Is there an internal database of "hematopoietic" and "non-hematopoietic" genes? In this case, I am wondering which gene annotation tool and which snapshot thereof was used to define "non-hematopoietic" genes? The reason why I am asking is, that I am concerned this will affect signature matrix generation depending on which annotation tool and version I use for gene annotation of the reference file due to tool-specific annotation differences in gene names (alterantive gene names, novel transcripts etc...) that don't match the CIBERSORT internal record.
  4. For the imputation of cell fractions, how important is it to match gene annotation of signature and mixture in regard to gene-annotation differences caused by different annotation tools/versions. Do I have to assume that the results are always penalised in case the mixture and signature/reference files were annotated in different labs (with a different annotation tool / version)? How would an annotation difference of more than 15% of genes between signature and mixture affect deconvolution performance?
  5. Error during the imputation of cell fractions using CIBERSORTx: "WARNING: reaching max number of iterations". What is the cause and how can I solve it?

CIBERSORT absolute deconvolution results

Thank you!!

ADD COMMENTlink modified 5 weeks ago by starick.marick0 • written 8 months ago by joker3320

Hi, I'm using CIBERSORTx for check cell types on RNA-Seq data, and I'm not sure about which count normalization it's better for input: CPM or TPM. I'm using LM22 as the signature matrix. The tutorial recommends that we should normalize the mixture file same as signature matrix, however, LM22 is microarray and I don't know how it was normalized. I also have access only to count matrix and using CPM will be easier, but I'm not sure if this is the best way. What signature matrix did you use? How did you normalize your counts?

ADD REPLYlink written 5 weeks ago by starick.marick0
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