Strand: 染色体链的方向 Variant_Classification: 变异的分类,如突变、插入、删除等 Variant_Type: 变异的类型,如单核苷酸多态性(SNP)、插入或缺失等 Reference_Allele: 变异前的等位基因 Tumor_Seq_Allele1: 肿瘤细胞中检测到的等位基因1 Tumor_Seq_Allele2: 肿瘤细胞中检测到的等位基因2 HGVSc: HGVS基因组级别的...
dplyr::select(c("Chromosome","Start_Position","End_Position","Variant_Classification","Hugo_Symbol")) %>% distinct_all() %>% { #将 typeNames 作为全局变量,后面还要使用 typeNames <<- unique(.$Variant_Classification) type = structure(1:length(typeNames), names = typeNames) mutate(., typ...
Strand: 染色体链的方向 Variant_Classification: 变异的分类,如突变、插入、删除等 Variant_Type: 变异的类型,如单核苷酸多态性(SNP)、插入或缺失等 Reference_Allele: 变异前的等位基因 Tumor_Seq_Allele1: 肿瘤细胞中检测到的等位基因1 Tumor_Seq_Allele2: 肿瘤细胞中检测到的等位基因2 HGVSc: HGVS基因组级别的...
1:7, with = FALSE] HGNC AAPos Variant_Classification N total fraction 1: PIK3CA 545 Missense_Mutation 24 88 0.27272727 2: CDKN2A 80 Nonsense_Mutation 20 104 0.19230769 3: PIK3CA 542 Missense_Mutation 18 88 0.20454545 4: PIK3CA 1047 Missense_Mutation 15 88 0.17045455 5: TP53 273 Missense...
(必须字段):Hugo_Symbol,Chromosome,Start_Position,End_Position,Reference_Allele,Tumor_Seq_Allele2,Variant_Classification,Variant_Type andTumor_Sample_Barcode(样本名,此字段沟通样本的maf文件和临床信息的关键,前者).laml=read.maf(maf="STAD.mutectAdjustBarcode.maf.txt",clinicalData="clinical.STAD.tsv")#...
ifelse(!is.na(Variant_Classification), "Mut","WILDorNOINFO")) -> BRCA_OV.clinical_mutations BRCA_OV.clinical_mutations %>% select(times, patient.vital_status, disease, TP53) -> BRCA_OV.2plot kmTCGA( BRCA_OV.2plot, explanatory.names = c("TP53", "disease"), ...
Mandatory fields(必须字段): Hugo_Symbol, Chromosome, Start_Position, End_Position, Reference_Allele, Tumor_Seq_Allele2, Variant_Classification, Variant_Type and Tumor_Sample_Barcode(样本名,此字段沟通样本的maf文件和临床信息的关键,前者). laml = read.maf(maf="STAD.mutectAdjustBarcode.maf.txt",cli...
>maf_df%>%filter(Hugo_Symbol=="VHL")%>%+count(Variant_Classification,sort=T)Variant_Classificationn1:Missense_Mutation602:Frame_Shift_Del413:Nonsense_Mutation274:Frame_Shift_Ins225:Splice_Site166:In_Frame_Del27:Nonstop_Mutation1 顶部条形图 ...
tidydata<-snpdata[,c("Hugo_Symbol","Variant_Type","Variant_Classification","Tumor_Sample_Barcode")] 删除无义突变,因为这个没有意义。 代码语言:javascript 复制 #删除无义突变 tidydata<-tidydata[which(tidydata$Variant_Type!="Nonsense_Mutation"),c("Hugo_Symbol","Variant_Type","Tumor_Sample_Barc...
ifelse(!is.na(Variant_Classification), "Mut","WILDorNOINFO")) -> BRCA_OV.clinical_mutations BRCA_OV.clinical_mutations %>% select(times, patient.vital_status, disease, TP53) -> BRCA_OV.2plot kmTCGA( BRCA_OV.2plot, explanatory.names = c("TP53", "disease"), ...