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zhanghao-njmu / SCP

An end-to-end Single-Cell Pipeline designed to facilitate comprehensive analysis and exploration of single-cell data.
https://zhanghao-njmu.github.io/SCP/
GNU General Public License v3.0
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Some mistakes in RunCellQC function #255

Open YongjieWangSarcoma opened 3 weeks ago

YongjieWangSarcoma commented 3 weeks ago

Dear Dr. Hao Zhang,

I appreciate that you created this fantastic package. I like using it to analyze single-cell RNAseq data. However, the RunCellQC function could have a small mistake.

As you can see in the scripts and output below, after running RunCellQC, all cells' percent_mito, percent_ribo, and ribo_mito_ratio are the same value. This is not possible.

library(SCP) library(tidyverse)

data("pancreas_sub")

pancreas_sub@meta.data$orig.ident%>%unique()%>%length() pancreas_sub <- RunCellQC(srt = pancreas_sub)

unique(pancreas_sub$nCount_RNA)%>%length() unique(pancreas_sub$nFeature_RNA)%>%length() unique(pancreas_sub$percent.mito)%>%length() unique(pancreas_sub$percent.ribo)%>%length() unique(pancreas_sub$ribo.mito.ratio)%>%length()

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Total cells: 1000 Cells which are filtered out: 46 ... 32 potential doublets ... 14 outlier cells ... 0 low-UMI cells ... 0 low-gene cells ... 0 high-mito cells ... 0 high-ribo cells ... 0 ribo_mito_ratio outlier cells ... 0 species-contaminated cells Remained cells after filtering: 954 [1] 923 [1] 752 [1] 1 [1] 1 [1] 1

Best regards, Yongjie Wang, MD/PhD