把tcga大计划的CNS级别文章标题画一个词云

Comprehensive genomic characterization defines human glioblastoma genes and core pathwaysIntegrated genomic analyses of ovarian carcinomaComprehensive molecular characterization of human colon and rectal cancerComprehensive molecular portraits of human breast tumoursComprehensive genomic characterization of squamous cell lung cancersIntegrated genomic characterization of endometrial carcinomaGenomic and epigenomic landscapes of adult de novo acute myeloid leukemiaComprehensive molecular characterization of clear cell renal cell carcinomaThe Cancer Genome Atlas Pan-Cancer analysis projectThe somatic genomic landscape of glioblastomaComprehensive molecular characterization of urothelial bladder carcinomaComprehensive molecular profiling of lung adenocarcinomaMultiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of originThe Somatic Genomic Landscape of Chromophobe Renal Cell CarcinomaComprehensive molecular characterization of gastric adenocarcinomaIntegrated genomic characterization of papillary thyroid carcinomaComprehensive genomic characterization of head and neck squamous cell carcinomasGenomic Classification of Cutaneous MelanomaComprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade GliomasComprehensive Molecular Portraits of Invasive Lobular Breast CancerThe Molecular Taxonomy of Primary Prostate CancerComprehensive Molecular Characterization of Papillary Renal-Cell CarcinomaComprehensive Pan-Genomic Characterization of Adrenocortical CarcinomaDistinct patterns of somatic genome alterations in lung adenocarcinomas and squamous cell carcinomasIntegrated genomic characterization of oesophageal carcinomaComprehensive Molecular Characterization of Pheochromocytoma and ParagangliomaIntegrated Molecular Characterization of Uterine CarcinosarcomaIntegrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH-Mutant Molecular ProfilesIntegrated genomic and molecular characterization of cervical cancerComprehensive and Integrative Genomic Characterization of Hepatocellular CarcinomaIntegrative Analysis Identifies Four Molecular and Clinical Subsets in Uveal MelanomaIntegrated Genomic Characterization of Pancreatic Ductal AdenocarcinomaComprehensive Molecular Characterization of Muscle-Invasive Bladder CancerComprehensive and Integrated Genomic Characterization of Adult Soft Tissue SarcomasThe Integrated Genomic Landscape of Thymic Epithelial TumorsPan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome AtlasScalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic PipelinesMolecular Characterization and Clinical Relevance of Metabolic Expression Subtypes in Human CancersSystematic Analysis of Splice-Site-Creating Mutations in CancerSomatic Mutational Landscape of Splicing Factor Genes and Their Functional Consequences across 33 Cancer TypesThe Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell CarcinomaPan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor ContextSpatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology ImagesMachine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome AtlasGenomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome AtlasDriver Fusions and Their Implications in the Development and Treatment of Human CancersGenomic, Pathway Network, and Immunologic Features Distinguishing Squamous CarcinomasIntegrated Genomic Analysis of the Ubiquitin Pathway across Cancer TypesSnapShot: TCGA-Analyzed TumorsThe Cancer Genome Atlas: Creating Lasting Value beyond Its DataMachine Learning Identifies Stemness Features Associated with Oncogenic DedifferentiationOncogenic Signaling Pathways in The Cancer Genome AtlasPerspective on Oncogenic Processes at the End of the Beginning of Cancer GenomicsComprehensive Characterization of Cancer Driver Genes and Mutations




    
An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome AnalyticsPathogenic Germline Variants in 10,389 Adult CancersA Pan-Cancer Analysis of Enhancer Expression in Nearly 9000 Patient SamplesGenomic and Functional Approaches to Understanding Cancer AneuploidyA Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast CancersComparative Molecular Analysis of Gastrointestinal AdenocarcinomaslncRNA Epigenetic Landscape Analysis Identifies EPIC1 as an Oncogenic lncRNA that Interacts with MYC and Promotes Cell-Cycle Progression in CancerThe Immune Landscape of CancerIntegrated Molecular Characterization of Testicular Germ Cell TumorsComprehensive Analysis of Alternative Splicing Across Tumors from 8,705 PatientsA Pan-Cancer Analysis Reveals High-Frequency Genetic Alterations in Mediators of Signaling by the TGF-β SuperfamilyIntegrative Molecular Characterization of Malignant Pleural MesotheliomaThe chromatin accessibility landscape of primary human cancersComprehensive Molecular Characterization of the Hippo Signaling Pathway in CancerBefore and After: Comparison of Legacy and Harmonized TCGA Genomic Data Commons’ DataComprehensive Analysis of Genetic Ancestry and Its Molecular Correlates in Cancer

# 安装R包相信无需再强调了library("tm")library("SnowballC")library("wordcloud")library("RColorBrewer")# 这里我们直接读取自己电脑剪切的数据即可# 运行下面这句代码的同时，需要保证你已经复制了前面我们整理好的文章标题哦！text=readLines(pipe("pbpaste"))# 好像这里Mac系统跟Windows系统稍微不一样，大家需要自行把握# Load the data as a corpusdocs <- Corpus(VectorSource(text))toSpace <- content_transformer(function (x , pattern ) gsub(pattern, " ", x))docs <- tm_map(docs, toSpace, "/")docs <- tm_map(docs, toSpace, "@")docs <- tm_map(docs, toSpace, "\\|")# Convert the text to lower casedocs <- tm_map(docs, content_transformer(tolower))# Remove numbersdocs <- tm_map(docs, removeNumbers)# Remove english common stopwordsdocs <- tm_map(docs, removeWords, stopwords("english"))# Remove your own stop word# specify your stopwords as a character vectordocs <- tm_map(docs, removeWords, c("blabla1", "blabla2")) # Remove punctuationsdocs <- tm_map(docs, removePunctuation)# Eliminate extra white spacesdocs <- tm_map(docs, stripWhitespace)# Text stemming# docs <- tm_map(docs, stemDocument)
dtm <- TermDocumentMatrix(docs)m <- as.matrix(dtm)v <- sort(rowSums(m),decreasing=TRUE)




    
d <- data.frame(word = names(v),freq=v)head(d, 10)set.seed(1234)wordcloud(words = dfreq, min.freq = 1,          max.words=200, random.order=FALSE, rot.per=0.35,           colors=brewer.pal(8, "Dark2"))

> head(d, 10)               word freq1  characterization   252         molecular   253           genomic   244            cancer   235     comprehensive   226          analysis   137        integrated   128         carcinoma   119              cell    810           genome    8