Understanding how to deal with Brain snRNA-seq data
1
0
Entering edit mode
8 weeks ago
AlexStar ▴ 170

I have obtained normal brain snRNA-seq data, but due to my limited experience and knowledge in this tissue, I need guidance on applying pre-processing steps.

Firstly, what is the usual threshold for filtering out mitochondrial genes based on their percentage of total counts? In one brain tumor dataset, a 5% cutoff was used (i.e., cells with more than 5% mitochondrial gene counts were removed). Is this the standard for this tissue?

Additionally, what is the cutoff for the number of genes with at least one count in a cell (in Scanpy, this is n_genes_by_counts)?

These cutoffs can significantly impact the analysis, so it's crucial for me to get them right.

Note: The data at hand is composed of neurons and glial cells. Should the thresholds change for each cell type?

scanpy python single-cell anndata RNA • 430 views
ADD COMMENT
0
Entering edit mode
8 weeks ago
ATpoint 87k

Please don't ask the same question twice, it was answered by multiple people before: snRNA-seq of the healthy human brain

Note: The data at hand is composed of neurons and glial cells. Should the thresholds change for each cell type?

Maybe yes, I often put celltyper-specific thresholds. For example in immune cells, monocyte express many thousands of genes in scRNA-seq while neutrophile express ~ 1500 in most conditions. Cutoffs are different here.

ADD COMMENT
0
Entering edit mode

ATpoint All I need is the mitochondrial cutoff used in the brain. I have no idea how to decide that. I hoped someone here has knowledge in this domain and could help.

ADD REPLY
0
Entering edit mode

Take a look at this paper: https://pubmed.ncbi.nlm.nih.gov/32840568/

ADD REPLY

Login before adding your answer.

Traffic: 2858 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6