数据准备好了,我们接下来开始进行DEA分析。 所谓DEA,也就是Differential Expression Analysis,将Tumor组和对照组进行比较。 首先,将刚才GDCprepare好的数据进行normalization,用normalization() 这里注意geneInfo=geneInfoHT,default其实是geneInfo,但由于我们前面选择的是HTseq,所以要选择geneInfoHT > dataNorm <- TCGAanal...
1. 基因差异分析(Differential Gene Expression Analysis): 基因差异分析是最常见的差异分析方法之一,它通过比较不同组别的基因表达水平来识别差异表达的基因。在TCGA数据库中,可以使用RNA-seq测序数据或芯片数据来进行基因差异分析。常见的基因差异分析方法包括t检验、方差分析(ANOVA)和非参数检验等。具体分析流程包括数据...
(1)dds_DE: this object created by DESeq2 contains results of differential expression analysis. We need to extract log2FoldChange, gene symbol and other available information from it. (2)condition_table: this table contains the grouping info of all samples. It will be used to create a new...
Comparison of DE pathway analysis results 下面使用的对象名称和内容与前文保持一致,仍使用之前教程选择的的TCGA-LUSC白色人种肺鳞癌表达谱数据(整合后cancer=344, normal=42)。 进行基因富集分析,我们需要的R对象是:(1)dds_DE: this object created by DESeq2 contains results of differential expression analysis...
normalization and voom transformation# Normalization of RNAseq datarnaExpr<-gdcVoomNormalization(counts=rnaCounts,filter=FALSE)# Normalization of miRNAs datamirExpr<-gdcVoomNormalization(counts=mirCounts,filter=FALSE)### Differential gene expression analysisDEGAll<-gdcDEAnalysis(counts=rnaCounts,group=...
TCGAanalyze_Preprocessing: Preprocessing of Gene Expression data (IlluminaHiSeq_RNASeqV2) TCGAanalyze_DEA&TCGAanalyze_LevelTab: Differential expression analysis (DEA) TCGAanalyze_EAcomplete & TCGAvisualize_EAbarplot: Enrichment Analysis TCGAanalyze_survival: Survival Analysis ...
Results: Differential expression analysis revealed 1 130 differentially expressed genes,of which 759 were down-regulated and 371 were up-regulated. Differential methylation sites analysis obtained 375 differential methylationsites,including 8 hypomethylation sites and 367 hypermethylation sites. Comprehensive ...
TCGAanalyze_Preprocessing: Preprocessing of Gene Expression data (IlluminaHiSeq_RNASeqV2) TCGAanalyze_DEA&TCGAanalyze_LevelTab: Differential expression analysis (DEA) TCGAanalyze_EAcomplete & TCGAvisualize_EAbarplot: Enrichment Analysis TCGAanalyze_survival: Survival Analysis ...
(1) 中文名为:基于基因表达水平值的交互式分析平台,英文为:Gene Expression Profiling Interactive Analysis。 (2) GEPIA是在线生信分析工具,零代码操作。GEPIA中整理了每一个可检索的基因在不同肿瘤样本中的表达值,可以计算某个基因在某种肿瘤中的表达水平,还可以分析基因与肿瘤预后的关系、基因间的共表达等。
1. Oshlack A, Robinson MD, Young MD (2010) From RNA-seq reads to differential expression results. Genome Biol 11: 220. 2. Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SA, Behjati S, et al. (2013) Signatures of mutational processes in human cancer. Nature 500: 415-421. ...