Mitochondria evidently have important roles in cancer development and progression. So when preprocessing single cell data generated from tumor tissue, is it wise to apply the "standard" filtering for mitochondrial genes?
I do not have experience with tumor tissue and I am very interested in the opinions of people who do.
If you want to include MT genes into consideration, make sure that you have filtered out the high percentage of mitochondrial genes. These reads normally due to biological and/or technical errors. it will generate noise to the dataset. you can go up to 10% if necessary. In average, you can cut down by eliminating 5-10% content. check the data distribution in violin plot, cut down errors accordingly.
Furthermore, don’t forget to normalize MT data based on you data architecture.
All the best.
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