KmeansR#runningclusterofgenestostratifygrouplibrary(factoextra)library(cluster)dat<-read.csv("C:/Users/?/Desktop/dat.csv")df<-na.omit(dat)df<-scale(df)#DETERMINEHOWMANYCLUSTERSISOPTIMAL(numberatthecurve)#plotnumberofclustersvs.totalwithinsumofsquaresfviz_nbclust(df,kmeans,method="wss")#calculategapstatisticbasedonnumberofclustersgap_stat<-clusGap(df,FUN=kmeans,nstar...[
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https://bioinformatics-core-shared-training.github.io/RNAseq-R/align-and-count.nb.htmlhttps://bioinf.wehi.edu.au/Rsubread/annot/#ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_34/GRCh38.primary_assembly.genome.fa.gzlibrary(Rsubread)library(edgeR)library(limma)library(annotables)fastq.files<-list.files(path="~/Desktop/RNAseq",pattern=".fastq.gz$",full.names=T...[
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木贼15g山豆根15g板蓝根15g加水烧开,凉到不会烫伤,用纱布外洗7-10天,10分/次,1-2次/天.同时口服VitB1.[
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Watchzaharaenglishatyoutube.Thisisthebestoneformetolearnenglish.[
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D<-apply(as.matrix(dat),2,as.numeric)d<-dat%>%group_by(Group)%>%summarise_if(is.numeric,mean,na.rm=TRUE)HNSC_TT<-HNSC[,grepl("01A",names(HNSC))]packageRsubreadforfastqtobam/countpackageDESeq2fordifferentlygeneexpressionpackageDOSEforGSEApackageyarrrlibrary(Hmisc)res<-rcorr(as.matrix(data))[
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catIN1_S1_L001_R1_001.fastqIN1_S1_L002_R1_001.fastq>IN1_S1_concatenated_R1_001.fastqcatIN1_S1_L001_R2_001.fastqIN1_S1_L002_R2_001.fastq>IN1_S1_concatenated_R2_001.fastqhttps://bioinformatics-core-shared-training.github.io/RNAseq-R/align-and-count.nb.htmllibrary(readr)library(dplyr)library(ggplot2)library(tidyverse)library(DESeq2)mycounts<-read.csv("C:/Users/?/Desktop/mycounts.csv&quo...[
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https://bioconductor.org/packages/release/bioc/html/TCGAbiolinks.htmllibrary(TCGAbiolinks)library(maftools)getGDCprojects()query<-GDCquery(project="TCGA-HNSC",data.category="TranscriptomeProfiling",experimental.strategy='RNA-Seq',data.type="GeneExpressionQuantification",workflow.type="HTSeq-Counts")GDCdownload(query)d<-getResults(query)HNSC.Rna...[
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library(readr)library(dplyr)library(ggplot2)library(tidyverse)library(DESeq2)mycounts<-read.csv("C:/Users/~/Desktop/datacounts.csv")metadata<-read.csv("C:/Users/~/Desktop/datametadata.csv")countData<-mycounts[!(duplicated(mycounts[[1]])|duplicated(mycounts[[1]],fromLast=TRUE)),]rownames(mycounts)=make.names(mycounts$gene,unique=TRUE)mycounts<-as.data.frame(mycounts)...[
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library(dplyr)library(Seurat)library(patchwork)library(ggplot2)dat1<-Read10X("C:/Users/~/Desktop/data")#data(matrix.mtx.gz,barcode.tsv.gz,features.tsv.gz)dat1<-CreateSeuratObject(counts=dat1,project="NT",min.cells=3,min.features=200)dat1dat1[["percent.mt"]]<-PercentageFeatureSet(dat1,pattern="^MT-")VlnPlot(dat1,features=c("nFeature_RNA",&q...[
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