Tag: MSigDB

Immune-related Prognostic Genes of ccRCC

Introduction Kidney cancer is one of the most commonly diagnosed tumors around the globe.1 According to the statistics from the World Health Organization, annually, there are more than 140,000 RCC-related deaths.2 ccRCC is the most typical subtype of kidney cancer and contributes to the majority of kidney cancer-related deaths.3,4 Until…

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GeneTonic: an R/Bioconductor package for streamlining the interpretation of RNA-seq data | BMC Bioinformatics

1. Van den Berge K, Hembach KM, Soneson C, Tiberi S, Clement L, Love MI, Patro R, Robinson MD. RNA sequencing data: Hitchhikers guide to expression analysis. Annu Rev Biomed Data Sci. 2019;2(1):139–73. doi.org/10.1146/annurev-biodatasci-072018-021255. Article  Google Scholar  2. Conesa A, Madrigal P, Tarazona S, Gomez-Cabrero D, Cervera A, McPherson A,…

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Hypoxic Characteristic Genes Predict Response to Immunotherapy for Urothelial Carcinoma

This article was originally published here Front Cell Dev Biol. 2021 Nov 25;9:762478. doi: 10.3389/fcell.2021.762478. eCollection 2021. ABSTRACT Objective: Resistance to immune checkpoint inhibitors (ICIs) has been a massive obstacle to ICI treatment in metastatic urothelial carcinoma (MUC). Recently, increasing evidence indicates the clinical importance of the association between hypoxia…

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KINNEY_DNMT1_METHYLATION_TARGETS

Standard name KINNEY_DNMT1_METHYLATION_TARGETS Systematic name M2508 Brief description Hypomethylated genes in prostate tissue from mice carrying hypomorphic alleles of DNMT1 [GeneID=1786]. Full description or abstract Previous studies have shown that tumor progression in the transgenic adenocarcinoma of mouse prostate (TRAMP) model is characterized by global DNA hypomethylation initiated during early-stage…

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Identification of lipid metabolism-associated gene signature

Background Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer. Despite the dramatic improvement in breast cancer prognosis due to recent therapeutic advances, such as more effective adjuvant and neo-adjuvant chemotherapies, together with more radical and safer surgery, advances in early diagnosis and treatment over the…

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Classifiers for predicting coronary artery disease

Introduction Coronary artery disease (CAD) is a complex pathology associated with behavioral and environmental factors.1–3 CAD shows high prevalence and is associated with a high fatality rate among cardiovascular diseases. The main manifestations of CAD are stable or unstable angina pectoris and identifiable or unrecognized myocardial infarction.4 The main risk…

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Filtering relevant Gene Ontology (GO) results from Gene Set Enrichment Analysis (GSEA)

Filtering relevant Gene Ontology (GO) results from Gene Set Enrichment Analysis (GSEA) 1 Hi all, I am new to bioinformatics and am currently learning how to use GSEA. Background: I analyzed my RNA-Seq results using DESeq2, and am now learning to perform GSEA. For my project, in broad terms, I…

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Gene expression profiling of contralateral dorsal root gangl

Introduction Mirror-image pain (MIP) is a mysterious pain phenomenon which is accompanied with many clinical pain conditions.1 MIP develops from the healthy body region which is contralateral to the actual injured site.1–3 MIP is typically characterized by increased mechanical hypersensitivity on the uninjured mirror-image body side.4 It can be triggered…

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Error in loading files into the GSEA software

Error in loading files into the GSEA software 0 Hi everyone I have some trouble with my RNA-seq file when I try to upload it for analysis with GSEA. I am getting the following error: Can anyone help me fix it? many thanks! —- Full Error Message —- There were…

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Bioconductor – SingscoreAMLMutations

DOI: 10.18129/B9.bioc.SingscoreAMLMutations     Using singscore to predict mutations in AML from transcriptomic signatures Bioconductor version: Release (3.13) This workflow package shows how transcriptomic signatures can be used to infer phenotypes. The workflow begins by showing how the TCGA AML transcriptomic data can be downloaded and processed using the TCGAbiolinks…

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working with .gmt files

working with .gmt files 3 Hi! I have downloaded a pathway data set in .gmt format form the GSEA website. I’m wondering how can I properly read this data set in R. Could anyone help me? Thank you!   myposts • 9.5k views • link updated 2 hours ago by…

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Performing GSEA using MSigDB gene sets in R

Performing GSEA using MSigDB gene sets in R 2 I am trying to perform a gene set enrichment analysis in r using the gene sets available from msigdb and a list of gene names from my own data set. I am able to to use the msigdbr library to import…

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