看到一篇文章做了這兩個數(shù)據(jù)，正好可以比較一下，文章是 Single-cell RNA sequencing identifies diverse roles of epithelial cells in idiopathic pulmonary fibrosis
研究是 【Idiopathic Pulmonary Fibrosis 特發(fā)性肺纖維化】
數(shù)據(jù)下載
數(shù)據(jù)存放在：GEO GSE86618 and GSE94555
scRNA-seq 采用的是 Fluidigm C1 Single-Cell Auto Prep System ， 測序詳情是：
Single-cell libraries are multiplexed and sequenced across 4 lanes of a NextSeq 500 platform (Illumina) using 75-bp single-end sequencing. On average, about 4–5 million reads were generated from each single-cell library.
放在：https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE86618 共540個細(xì)胞，數(shù)據(jù)量不小。
其中包括540 single cells from control (n = 3) and IPF patients (n = 6) reveals 4 major cell types (C1–C4), termed as
normal AT2 (C1, green)
indeterminate (C2, yellow)
basal (C3, red)
club/goblet (C4, blue) cells.
單細(xì)胞轉(zhuǎn)錄組的優(yōu)點(diǎn)就是可以分群，但是本教程需要探索單細(xì)胞轉(zhuǎn)錄組的平均值是否與其bulk測序有相關(guān)性。
bulk轉(zhuǎn)錄組測序數(shù)據(jù)在：https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE94555 EPCAM+ (CD326+) and HTII-280+ epithelial cells from control and IPF donors were isolated from peripheral lung tissue by FACS and subjected to RNA sequencing (RNA-seq).
ID處理
GSM2478109IPF_1
GSM2478110IPF_2
GSM2478111IPF_3
GSM2478112CON_1
GSM2478113CON_2
GSM2478114CON_3
提供表達(dá)量矩陣的下載： GSE94555_IPF_Epithelial_Type2_RNA-seq_Reads_and_FPKM.xlsx 當(dāng)然，也是可以下載原始數(shù)據(jù)走一波轉(zhuǎn)錄組分析流程得到表達(dá)矩陣進(jìn)行差異分析的。
如果你不會上面這樣的簡單分析，那么你可能是需要去B站看我的視頻，搜索生信技能樹即可。
進(jìn)行比較
首先需要使用R下載兩個表達(dá)矩陣，然后需要對應(yīng)單細(xì)胞來源于的病人與bulk的病人，這樣就可以計算相關(guān)性啦！！！
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