purify tumor samples and remove normal cells

Question

[fatima.m.zare]

I know the tumor samples are mixture of tumor and normal cells. I want to remove normal cells from my tumor samples. Is it possible?

[GenoMax]

If this question about "how to do this experimentally" then you are posting in the wrong forum.

[L. A. Liggett]

Agreed, without any information about what you are doing, it is hard to help. Is this already a sequenced sample? Do you have any identifiers like barcodes or tags of some kind?

[fatima.m.zare]

I have paired tumor and normal samples and they are WES data. I can calculate read count from them. Sequencing data on tumor samples are derived from a mixed population of cells. So my question is that can I separate tumor and normal cell in tumor samples?

Answer 1

[markus.riester]

Since you are not sequencing single cells, you cannot easily "remove" the normal cells. But you probably did not mean that literally anyways.

By comparing tumor and normal, you can detect alterations that are present only in tumor using somatic variant callers (GATK, MuTect, Strelka, ...).

Quantifying the normal contamination in the tumor sample is a bit more complicated, but there are a lot of other tools published recently (e.g. FACETS, Sequenza, ...) for paired whole-exome sequencing.

We recently published the Bioconductor package PureCN that in addition adjusts read counts of somatic and germline variants in a VCF for normal contamination and allele-specific copy number (paired or unpaired whole-exome sequencing).

You can finally use tools like PyClone or SciClone to "cluster" the tumor cells into different clones.

[fatima.m.zare]

Thank you. I will try FACETS and also your package.

Answer 2

[dyollluap]

If you process them as tumor-normal pairs using variant calling pipelines you can identify variant features unique to the tumor. Try GATK for best practice pipeline guidelines and a ready package.