單細(xì)胞轉(zhuǎn)錄組數(shù)據(jù)分析的時(shí)候可以加上wgcna
WGCNA分析大家都不陌生了，我在生信技能樹多次寫教程分享WGCNA的實(shí)戰(zhàn)細(xì)節(jié)：
那些教程都是針對(duì)傳統(tǒng)的bulk轉(zhuǎn)錄組測(cè)序的表達(dá)矩陣，其實(shí)單細(xì)胞轉(zhuǎn)錄組也是拿到表達(dá)矩陣，只不過是有一些特性，比如非常多的0值等等。那么有沒有這樣的研究嘗試把WGCNA融入單細(xì)胞轉(zhuǎn)錄組數(shù)據(jù)分析呢？
答案是有的，Posted March 04, 2019. 丟在預(yù)印本的文章，題目是：[Single-Cell RNA Sequencing Reveals Regulatory Mechanism for Trophoblast Cell-Fate Divergence in Human Peri-Implantation Embryo](Single-Cell RNA Sequencing Reveals Regulatory Mechanism for Trophoblast Cell-Fate Divergence in Human Peri-Implantation Embryo) 就這樣做了，讓我們一起來看看吧。
背景
To obtain transcriptomic profiles of human trophoblast cells during peri-implantation development, we harvested single cells from 19 embryos from day 6 to day 10, complement with 25 endometrial cells. Transcriptomes from 614 single cells were successfully profiled, with 0.7 million uniquely mapped reads and 24,011 detected transcripts per cell on average.數(shù)據(jù)都是在：https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE125616
主要樣品是人類著床前胚胎的 Trophoblasts 進(jìn)行單細(xì)胞轉(zhuǎn)錄組測(cè)序，其中516 embryonic cells 可以分成476 TE-, 14 EPI-and 26 PE-lineage cells. 最后的分析重點(diǎn)是 476 individual trophoblast cells isolated from 19 human embryos
- cells of epiblast (EPI),
- primitive endoderm q (PE)
- trophectoderm (TE)
當(dāng)然了，還有少量的endometrial cells,第一主成分就可以區(qū)分開來它們，如下：
Embryonic cells were assigned into three lineages, namely TE, EPI and PE, based on their expression of 300 previous identified lineage marker genes. 需要相關(guān)生物學(xué)知識(shí)。
其中時(shí)間這個(gè)屬性也是在PCA上面反映到：
不管是時(shí)間這個(gè)屬性天然對(duì)單細(xì)胞分組，還是整體的表達(dá)矩陣進(jìn)入單細(xì)胞數(shù)據(jù)分析流程后分組， 都是可以看基因表達(dá)量情況的小提琴圖等等。分析其實(shí)仍然是我們一直講解的R包及基礎(chǔ)流程，分別是: scater,monocle,Seurat,scran,M3Drop 需要熟練掌握它們的對(duì)象，：一些單細(xì)胞轉(zhuǎn)錄組R包的對(duì)象 流程也大同小異：
- step1: 創(chuàng)建對(duì)象
- step2: 質(zhì)量控制
- step3: 表達(dá)量的標(biāo)準(zhǔn)化和歸一化
- step4: 去除干擾因素(多個(gè)樣本整合)
- step5: 判斷重要的基因
- step6: 多種降維算法
- step7: 可視化降維結(jié)果
- step8: 多種聚類算法
- step9: 聚類后找每個(gè)細(xì)胞亞群的標(biāo)志基因
- step10: 繼續(xù)分類
WGCNA步驟
To systematically investigate the genetic program dynamics, we performed Weighted Gene Co-expression Network Analysis (WGCNA) on 2,464 genes that were variably expressed in trophoblast cells between different developmental stages.
WGCNA identified eight gene modules, each of which contains a set of genes that tend to be coexpressed at a certain development stage！
可以看到WGCAN其實(shí)大家需要注意的是挑選基因，然后判斷模塊，最后關(guān)聯(lián)起來性狀即可!
研究者感興趣的生物學(xué)組別
其實(shí)是：
- cytotrophoblast (CT),
- extravillous cytotrophoblast (EVT)
- syncytiotrophoblast (ST)
所以才會(huì)有如下圖表：
讓我意外的是，文章里面僅僅是提到了 Seurat 流程，沒有monocle，但是卻有l(wèi)ineage分析 ！其實(shí)這個(gè)小鼠發(fā)育研究，跟我前面的視頻課程非常類似，可以作為一個(gè)練習(xí)題，考核一下大家！
