Additional file 2: of CellSIUS provides sensitive and specific detection of rare cell populations from complex single-cell RNA-seq data
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Table S4. DE analysis between subclusters and main clusters in the neuroscience dataset. The file contains one sheet per comparison. All sheets are listed below: G.sub_1_vs_all_G: compares the G.sub_1 population to all other cells in the G cluster. G.sub_2_vs_all_G: compares the G.sub_2 population to all other cells in the G cluster. G.sub_3_vs_all_G: compares the G.sub_3 population to all other cells in the G cluster. CR.sub_vs_all_CR: compares the CR.sub population to all other cells in the CR cluster. NP.sub_vs_all_NP: compares the NP.sub population to all other cells in the NP cluster. N.sub_1_vs_all_N: compares the N.sub_1 population to all other cells in the N cluster. N.sub_2_vs_all_N: compares the N.sub_2 population to all other cells in the N cluster. Each sheet contains the following columns: Gene_id: Ensembl gene ID. Mean_exprs: Mean expression [log2(normalized counts + 1)] across the whole dataset. Mean_in_subgroup: Mean expression in the respective subgroup. Pval, adj_pval: p value (Wilcoxon test), adj_pval is adjusted p value (Benjamini-Hochberg). Log2fc: Fold change, calculated as the difference in mean[log2(normalized counts + 1)]. DE_flag: is TRUE if abs(log2fc) > 0.5 and adj_pval
表S4 神经科学数据集中亚簇与主簇间的差异表达(Differential Expression, DE)分析。本文件每份比较对应一个工作表,所有工作表如下:
G.sub_1_vs_all_G:将G.sub_1细胞群与G簇内其余所有细胞进行比较;
G.sub_2_vs_all_G:将G.sub_2细胞群与G簇内其余所有细胞进行比较;
G.sub_3_vs_all_G:将G.sub_3细胞群与G簇内其余所有细胞进行比较;
CR.sub_vs_all_CR:将CR.sub细胞群与CR簇内其余所有细胞进行比较;
NP.sub_vs_all_NP:将NP.sub细胞群与NP簇内其余所有细胞进行比较;
N.sub_1_vs_all_N:将N.sub_1细胞群与N簇内其余所有细胞进行比较;
N.sub_2_vs_all_N:将N.sub_2细胞群与N簇内其余所有细胞进行比较。
每个工作表包含以下列:
Gene_id:Ensembl基因ID(Ensembl gene ID);
Mean_exprs:全数据集平均表达量[log₂(标准化计数+1)];
Mean_in_subgroup:对应亚群的平均表达量;
Pval、adj_pval:P值(Wilcoxon秩和检验,Wilcoxon test),adj_pval为校正后P值(Benjamini-Hochberg校正法);
Log2fc:对数2倍数变化,通过两组平均[log₂(标准化计数+1)]的差值计算得到;
DE_flag:当|log2fc|>0.5且adj_pval
提供机构:
Bilada Bilican; Ajamete Kaykas
创建时间:
2019-07-18



