Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown
用HISAT, StringTie 和 Ballgown來進行轉(zhuǎn)錄組測序數(shù)據(jù)的表達水平分析
ps：文章省略了數(shù)據(jù)的質(zhì)控贝或，去除污染物术唬，去除接頭等操作围段，直接從序列比對開始
分析流程可以分成4個主要的方面：
?(i)? alignment?of? the? reads?to? the? genome;
?(ii)? assembly? of? thealignments into full-length transcripts;
?(iii) quantification of the expressionlevels of each gene and transcript; and
?(iv) calculation of? the?differences? in? expression?for? all? genes?among? the different?experimental? conditions.
1 比對reads到gene組
2將alignments?組裝成完整的轉(zhuǎn)錄本
3定量每個gene或者轉(zhuǎn)錄本的表達水平
4計算不同實驗條件下所有g(shù)ene表達差異
分析使用的3個軟件的分別作用：
HISAT：alignsRNA-seq reads to a genome and discovers transcript splice sites
HISAT：比對RNA測序的reads到基因組和已知的轉(zhuǎn)錄剪切位點
StringTie：assembles? the?alignments? into? full?and? partial? tran-scripts, creating multiple isoforms asnecessary and estimating ?the expression levels of all genes and transcripts.
StringTie：組裝?alignments到全部或者部分轉(zhuǎn)錄組漓库，生成多個isoforms徘公，計算所有g(shù)ene和transcripts的表達水平
Ballgown：takes thetranscripts and expression levels from StringTie and applies rigorous? statistical?methods? to? determine?which? transcripts are? differentially? expressed?between? two? or?more? experiments.
Ballgown：導(dǎo)入StringTie生成的轉(zhuǎn)錄本以及表達水平結(jié)果，采用嚴格的統(tǒng)計方法來確認在不同實驗條件下差異表達的?transcripts
具體流程圖：
具體流程：
*FASTQC和FASTX toolkit進行原始RNA測序數(shù)據(jù)的質(zhì)控：去除污染物逛犹，去除接頭舱呻，低質(zhì)量的序列
1 用HISAT將樣本的read比對到參考基因組
2 比對結(jié)果傳送到stringtie進行轉(zhuǎn)錄本拼接
3 用stingtie的merge功能將拼接后的轉(zhuǎn)錄本進行融合
（Cufflinks的cuffmerge功能能代替atingtie的merge功能）
4 融合后的轉(zhuǎn)錄本回送到stingtie，重新計算轉(zhuǎn)錄本的豐度
?stringtie:gffcompre確定拼接的轉(zhuǎn)錄本多少匹配到已經(jīng)注釋的gene怯晕，多少是完全新的
5 stingtie提供轉(zhuǎn)錄本的read數(shù)量
? stringtie傳送三類數(shù)據(jù)至ballgown
(i)phenotype data—information about the samples being collected;
(ii)expression data—normalized and un-normalized measures of the amount of eachexon, junction, transcript and gene expressed in each sample;
(iii)genomic information— coordinates giving the location of the exons, introns,transcripts and? genes,? as?well? as? annotation?including? information? such?as gene names.
A 表型數(shù)據(jù)：收集的樣本信息
B 表達數(shù)據(jù)：標準化或未標準化的內(nèi)顯子潜圃，junction，轉(zhuǎn)錄本舟茶，gene的表達信息
C gene組信息：內(nèi)外顯子轉(zhuǎn)錄本等的位置信息谭期，或者gene名稱等
6 ballgown根據(jù)不同實驗條件計算差異表達gene
ballgown分析流程：
A? ?loading the data into R.
載入由stingtie產(chǎn)生的豐度數(shù)據(jù)和描述樣本的表型信息數(shù)據(jù)到R?
劃重點：確保gene組樣本的id與表型數(shù)據(jù)的id一致
B?inspectthe distribution of abundance estimates for the transcripts.
檢查轉(zhuǎn)錄本豐度估計的分布
劃重點：豐度估計由FPKM表示，每1百萬個map上的reads中map到外顯子的每1K個堿基上的reads個數(shù)
ballgown的stattest功能：直接標記任何已知的干擾因子
C?The result is a table with information on thefeature tested for differential expression
差異表達的特征檢驗
具體的軟件安裝與執(zhí)行代碼吧凉，文章中有具體列出崇堵，這里就不累述。詳細請閱讀文章客燕。
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