研究人员对13名疑似或已知患有免疫相关疾病的患者进行了260个基因的靶向RNA测序,平均每个样本为11.5 M read pair。对每个样本都完成了 RNA的全面分析,包括call变异、异常剪接识别和异常基因表达。 表1 主要研究结果摘要 ACMG 指南将变异...
} final_DEGs_list<-do.call(cbind, lapply(lapply(final_genelist, unlist), `length<-`, max(lengths(final_genelist))) final_DEGs_list out_final2 = cbind(condition_name, gene_num_out) colnames(out_final2) = c("Tests", "DEG number") write.table(final_DEGs_list, file=file_final_gen...
真阳性率(TPR,true positive rate)不断提高,且提高幅度很大; 而差异表达基因所占比例(call rate)也是不断提高。 这说明生物学重复对真阳性率即数据准确性,以及差异基因检出的影响很大。 生物学重复的增加可以提高数据准确性,检测出更多的差异基因。 表1:生物学重复对差异基因检出率的影响 Liu等[4]以人类细胞MCF7...
SCBN<-function(orth_gene,hkind,a=0.05){if(all(!is.na(orth_gene))==FALSE){stop("The dataset of orthologous genes has NA values.",call.=TRUE)}elseif(all(hkind%in%(seq_len(nrow(orth_gene)))==FALSE){stop("The conserved genes are not included in dataset of orthologous genes.",call....
eff_length<-do.call(rbind,lapply(exonic.gene.sizes,data.frame))eff_length<-data.frame(gene_id=rownames(eff_length),effLen=eff_length[,1])rownames(eff_length)<-eff_length$gene_idrownames(eff_length)<-do.call(rbind,strsplit(as.character(eff_length$gene_id),'\\.'))[,1]head(eff_le...
TP53 and PIK3CA mutation calls, including SNPs and indels, were derived from TCGA’s MC3 public call set (v0.2.8)40. Our evaluation approach changed slightly for predicting mutation status. Given the higher prevalence of TP53 and PIK3CA mutations in some expression-based subtypes, we wanted to...
callback = function(hc, ...){dendsort(hc)} pheatmap(test, clustering_callback = callback) ## End(Not run) 想要了解更多scripts,可以在我的GitHub主页查看: 231Charlie/Heatmap-plot-for-RNA-seq (github.com)github.com/231Charlie/Heatmap-plot-for-RNA-seq...
另一篇是海南大学热带作物学院探索的,基于多组学关联探究《槟榔花性别调控分子机制》。相关文章也已在《 Horticulture Research 》《 New Phytologist 》中发表,真心为老师实力打call。再次祝贺老师们在各自的领域中又有了新的收获! 这两篇文章也各有千秋,侧重点不同~小编愿称之为,转录组应用的两大经典代表:1.分子...
学习完snakemake后写的第一个流程是RNA-seq上游定量和下游的质控和差异分析。 使用fastp处理fastq文件,在使用START比对到基因组同时得到raw count,使用非冗余外显子长度作为基因的长度计算FPKM、TPM,同时也生成了CPM的结果。 非冗余外显子长度计算可以参考之前的推文转录组实战02: 计算非冗余外显子长度之和 ...
Metatranscriptomic differential RNA-Seq (mdRNA-Seq) identifies the suite of active transcriptional start sites at single-nucleotide resolution through enrichment of primary transcript 5′ ends. Here we analyzed the microbial community at 45 m depth at