Tag: GSEA

Bioconductor – EasyCellType

DOI: 10.18129/B9.bioc.EasyCellType     Annotate cell types for scRNA-seq data Bioconductor version: Release (3.16) We developed EasyCellType which can automatically examine the input marker lists obtained from existing software such as Seurat over the cell markerdatabases. Two quantification approaches to annotate cell types are provided: Gene set enrichment analysis (GSEA)…

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Phenotypic plasticity and genetic control in colorectal cancer evolution

Sample preparation and sequencing The method of sample collection and processing is described in a companion article (ref. 23). Sequencing and basic bioinformatic processing of DNA-, RNA- and ATAC-seq data are included there as well. Gene expression normalization and filtering The number of non-ribosomal protein-coding genes on the 23 canonical chromosome pairs…

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Noncoding RNAs responsive to nitric oxide and their protein-coding gene targets shed light on root hair formation in Arabidopsis thaliana

doi: 10.3389/fgene.2022.958641. eCollection 2022. Affiliations Expand Affiliations 1 Laboratório de Ecofisiologia e Bioquímica de Plantas, Núcleo de Conservação da Biodiversidade, Instituto de Pesquisas Ambientais, São Paulo, SP, Brasil. 2 Programa de Pós-Graduação em Biologia Celular e Estrutural, Universidade Estadual de Campinas, Campinas, SP, Brasil. Item in Clipboard Camilla Alves Santos et…

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Acute phase of ischemia-reperfusion in rats

Introduction Stroke is one of the leading causes of death and disability worldwide, which causes substantial economic and social burdens.1 Ischemic stroke is caused by insufficient blood and oxygen supply to the brain,2 accounting for about 85% of the casualties of stroke patients.3 The concept of treatment for ischemic injury…

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Subtype and cell type specific expression of lncRNAs provide insight into breast cancer

lncRNA expression according to breast cancer clinicopathological subtypes To identify lncRNAs expressed by specific breast cancer subtypes or associated with clinicopathological features, we analyzed RNA-sequencing data from two large independent breast cancer cohorts: SCAN-B (n = 3455)17 and TCGA-BRCA (n = 1095). We focused on lncRNAs annotated in the Ensembl18 v93 non-coding reference transcriptome…

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Transcription-independent regulation of STING activation and innate immune responses by IRF8 in monocytes

Reagents, antibodies, viruses and cells LMW-Poly(I:C), LPS, 2′3′-cGAMP and DMXAA (InvivoGen); hydroxyurea, camptothecin and mitomycin C (MCE); GM-CSF, Flt3L (peproTech); lipofectamine 2000 (Invitrogen); polybrene (Millipore); RNAiso Plus (Takara); HT-DNA (Sigma); SYBR (BIO-RAD); dual-specific luciferase assay kit (Promega); ELISA kit for murine Ifn-β (PBL); ELISA kits for murine IP-10 (Biolegend) were…

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Targeted inhibition of ubiquitin signaling reverses metabolic reprogramming and suppresses glioblastoma growth

Cell culture Human glioblastoma cells (U87MG and U87MG-Luc) and human embryonic kidney cells (HEK293) were obtained from the American Type Culture Collection (Manassas, Va.). Cells were cultured in Dulbecco’s Modified Eagle Medium supplemented with 10% fetal bovine serum (Gibco™ Fetal Bovine Serum South America, Thermo Scientific Fisher-US), 2 mM l-glutamine, 50 U/ml…

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Single-cell and bulk transcriptome sequencing identifies two epithelial tumor cell states and refines the consensus molecular classification of colorectal cancer

Cell-type annotation scRNA-seq data were filtered to discard low-quality cells and doublets (Supplementary Fig. 1, Extended Data Fig. 1 and Methods). Supervised clustering (Reference Component Analysis v2 (RCA2)) at low resolution grouped cells into 11 major cell types (Extended Data Fig. 1). To identify epithelial cell subtypes, we initially analyzed…

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Gene Set – TNFSF10

Dataset MSigDB Cancer Gene Co-expression Modules Category transcriptomics Type co-expressed gene Description tumor necrosis factor (ligand) superfamily, member 10|The protein encoded by this gene is a cytokine that belongs to the tumor necrosis factor (TNF) ligand family. This protein preferentially induces apoptosis in transformed and tumor cells, but does not…

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Role of CD68 in tumor immunity and prognosis prediction in pan-cancer

Expression of CD68 in pan-cancer First, to fully clarify the expression of CD68 in pan-cancer, we matched the GTEx normal samples with TCGA tumor samples (Fig. 1A). We found that the levels of CD68 were significantly elevated (P < 0.01) in colon adenocarcinoma (COAD), glioblastoma multiforme (GBM), kidney renal clear cell carcinoma (KIRC),…

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Identification of Potential Biomarkers for Progression and Prognosis of Bladder Cancer by Comprehensive Bioinformatics Analysis

This article was originally published here J Oncol. 2022 Apr 19;2022:1802706. doi: 10.1155/2022/1802706. eCollection 2022. ABSTRACT Background. Bladder cancer (BLCA) is a highly malignant tumor that develops in the urinary system. Identification of biomarkers in progression and prognosis is crucial for the treatment of BLCA. BLCA-related differentially expressed genes (DEGs)…

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GSEA RNASeq

GSEA RNASeq 0 Hi friends For gene set enrichment analysis (GSEA), the software from broad institute does not accept ensemble IDs, I want to do the analysis using entrez ID or hugo ID but about 2000 genes don’t have hugo ID or entrez ID. What should I do? gene enrichment…

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N6-methyladenosine modification of CENPK mRNA by ZC3H13 promotes cervical cancer stemness and chemoresistance | Military Medical Research

Bioinformatics analyses revealed the involvement of m6A modification in cervical cancer progression To better understand whether and how m6A regulators contribute to cervical cancer progression, we first identified 9 m6A writers (WTAP, ZC3H13, METTL3, METTL14, METTL16, VIRMA, RBM15B, RBM15, and CBLL1), 15 m6A readers (FMR1, hnRNPA2B1, hnRNPC, YTHDF1/2/3, YTHDC1/2, LRPPRC,…

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A hypoxia-related signature in lung squamous cell carcinoma

Introduction Lung cancer is the major leading cause of tumour-related deaths throughout the world, while lung squamous cell carcinoma (LUSC) as the second most common histological type of lung cancer.1 Each year, almost 1.8 million people are diagnosed with lung cancer worldwide and 400,000 of these die from LUSC.2,3 Due to…

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Bioconductor – neaGUI

    This package is for version 2.13 of Bioconductor; for the stable, up-to-date release version, see neaGUI. An R package to perform the network enrichment analysis (NEA). Bioconductor version: 2.13 neaGUI is an easy to use R package developed to perform the network enrichment analysis (NEA) proposed by Alexeyenko…

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Two drugs show promise in rejuvenating lung epithelial progenitor cells damaged by COPD

Overview of the transcriptomics-guided drug discovery strategy.(A) Schematic outline of the drug screening strategy. (B) Heatmap shows the gene expression pattern of the druggable genes (www.dgidb.org) identified both in CS-exposed mice and patient with COPD databases. (C) Reactome pathway enrichment analysis of genes differentially expressed from patients with COPD (8)…

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Comprehensive bioinformatics analysis reveals the hub genes and pathways associated with multiple myeloma

This article was originally published here Hematology. 2022 Dec;27(1):280-292. doi: 10.1080/16078454.2022.2040123. ABSTRACT PURPOSE: While the prognosis of multiple myeloma (MM) has significantly improved over the last decade because of new treatment options, it remains incurable. Aetiological explanations and biological targets based on genomics may provide additional help for rational disease…

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Fatty infiltration after rotator cuff tear

Introduction Rotator cuff tear (RCT) is a common shoulder disorder causing shoulder pain and disability. The prevalence of full-thickness RCT is 20.7% in the general population, and increased with age.1 Rotator cuff play essential roles in shoulder function and the treatment of proximal humeral fractures.2,3 It is important to repair…

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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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Bioinformation Analysis Reveals IFIT1 as Potential Biomarkers in Centr

Introduction Tuberculosis (TB) is considered to be one of the top ten causes of death in the world, about a quarter of the world’s population is infected with M. tuberculosis.1 The World Health Organization (WHO) divides tuberculosis into pulmonary tuberculosis (PTB) and extra-pulmonary tuberculosis (EPTB). Although breakthroughs have been made…

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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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Problem for analysing GSEA and ORA

Problem for analysing GSEA and ORA 0 I analysed two different GEO dataset individually and found DEG for each dataset .After that I compare the two dataset DEG and found some common DEG.Now i want to analyse GSEA and ORA for that common DEG.As far i know for analysing GSEA…

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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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Easy differential expression heatmap?

Easy differential expression heatmap? 0 I’m finally getting back to an RNAseq differential expression dataset I analyzed years ago and cannot remember what tool I used to generate these simple heat maps that I really like. I think it was an online interface where I could add/take away genes from…

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Frontiers | Plasma Cell-Free DNA Methylomics of Bipolar Disorder With and Without Rapid Cycling

Introduction Bipolar disorder (BD) features recurrent episodes of mania/hypomania and depression, interspersed with periods of euthymia. Symptoms usually include drastic changes in energy levels, sleep, thinking, and behaviors, which can significantly disrupt the daily life of BD patients (Craddock and Sklar, 2013). A mood cycle is defined as the period…

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GOstats doubts about significant GO terms with small “size”

Hi all, I am trying to perform a GO enrichment analysis on a list of differentially expressed genes and I am having doubts on the robustness of the results. I am using the GOstats package and the organism is Apis mellifera, so I had to make a custom gene universe…

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Genes and Pathways Involved in Postmenopausal Osteoporosis

Introduction Many postmenopausal women suffer from postmenopausal osteoporosis (PMO). A survey of 3247 Italian postmenopausal women found that according to bone mineral density (BMD) diagnostic criteria, the prevalence of osteoporosis was 36.6%.1 PMO patients may suffer from chronic pain and fractures, and as a result their quality of life is…

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Recommended bioinformatic course?

Recommended bioinformatic course? 0 Hello all, I started my PhD in medicine this year, my research includes a lot -omics analysis. Currently I am doing a transcriptomics project, but a proteomic and peptidomic project will certainly follow. Now I have mastered the basic of doing gene differential exppression myself, but…

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Count Matrix from quant.genes.sf files

Count Matrix from quant.genes.sf files 0 Hello everyone, I am having trouble understanding something and would appreciate any help or even a tutorial on this if someone can link it. I got 20 Bulk RNA samples sequenced and the bioinformatics core gave me 20 quant.genes.sf files obtained through DRAGEN RNA…

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Comparing the whole genelist by GSEA GO BP terms to adjusted pvalue genelist by DAVID GO BP terms

Comparing the whole genelist by GSEA GO BP terms to adjusted pvalue genelist by DAVID GO BP terms 0 Say I have done DESeq2 on my RNA-Seq dataset: experimental vs. control DESeq2 has a column for BH – adjusted Pvalues and I plan to take the genes with less than…

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Bioconductor – sparrow

DOI: 10.18129/B9.bioc.sparrow     Take command of set enrichment analyses through a unified interface Bioconductor version: Release (3.14) Provides a unified interface to a variety of GSEA techniques from different bioconductor packages. Results are harmonized into a single object and can be interrogated uniformly for quick exploration and interpretation of…

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replacing ensembl ID with the gene symbol?

Im a noob with a very unclear idea of what I am doing, but I’m doing my best. The other day, the ncbi webpage for downloading genomes and GTF files was down. As a result, I had to do my analysis on this RNA seq data using the ensembl files,…

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Bioconductor – Bioconductor 3.14 Released

Home Bioconductor 3.14 Released October 27, 2021 Bioconductors: We are pleased to announce Bioconductor 3.14, consisting of 2083 software packages, 408 experiment data packages, 904 annotation packages, 29 workflows and 8 books. There are 89 new software packages, 13 new data experiment packages, 10 new annotation packages, 1 new workflow,…

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single gene GSEA

single gene GSEA 0 Hello,I have a candidate gene which I want to check if it is related to important pathways/gene-sets in a dataset that its samples are from one biological group (tumor samples). I came up with two methods: Projecting the expression matrix to gene-set space using ssGSEAProjection and…

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Available GO molecular functions for AlphaFold proteins : bioinformatics

Context I’m currently exploring the AlphaFold 2 dataset. The goal is to use deep learning to generate some embeddings to represent the structures and group structurally similar proteins together using a clustering algorithm. I have my first pass at the clusters of AlphaFold proteins. Assuming that structure and function are…

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A TME-Related Signature as a Biomarker in Liver Cancer

Introduction As one of the most frequent causes of cancer deaths across the globe, liver cancer, characterized by high mortality, recurrence, metastasis and poor prognosis, is the only one of the top five deadliest cancers to have an annual percentage increase in occurrence.1 Surgery, local destructive therapies, and liver transplantation…

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ssGSEA scores correlate with the number of gene counts, should I be worried?

ssGSEA scores correlate with the number of gene counts, should I be worried? 0 I performed a Pearson correlation between the ssGSEA scores for all the 50 Hallmark pathways and the number of gene counts in my data. I noticed that most hallmark ssGSEA scores correlate with the number of…

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Gene Set Enrichment Analysis, KEGG and over representative analysis

Dear Seniors, I am looking to perform GSEA, KEGG and Over Representative Analysis. I found ClusterProfiler interesting and had ago with “GO classification” including groupGo (gene classification based on GO distribution at a specific level) , enrichGO (Over Representative analysis), gseGO (GO Gene Set Enrichment Analysis). ClusterProfiler needs EntrezID. Unfortunately,…

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RNA-seq z-score normalization

RNA-seq z-score normalization 1 Hi! I have RNA-seq data that I have put into DeSeq2 (R) for analysis and I would like to create heatmaps. I have also run my data using the gsea software from the broad institute and I would like to replicate the heatmaps that come out…

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Differential gene abundance analysis with 16s seq data

Differential gene abundance analysis with 16s seq data 0 Hello, Is it possible to do differential gene „abundance“ (I don’t want to say expression because it was not sequenced) analysis from two conditions of 16s RNA seq data (Microbiome analysis)? So basically, by 16s seq we can assign sequences to…

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Convert HTSeq-count, raw count to TPM : bioinformatics

Hi Everyone, I am working with a publicly available RNA-Seq dataset for which only the HTSeq-count data is accessible. I have done differential gene expression already (i.e. between sample analysis) however I am also hoping to obtain TPM count for within-sample analysis such as single-sample GSEA and for this I…

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deseq2 tutorial microbiome

phyloseq Handling and analysis of high-throughput microbiome census data. Detecting the periodontal pathogens at the subgingival plaque requires skilled professionals to collect samples. Import mothur list and group files and return an otu_table. In a randomized, double-blind, placebo-controlled trial, we assessed the effect of Lactobacillus reuteri supplementation, from birth to…

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Exclude pseudogenes and lncRNA’s from DE-analysis?

Hi all, Let’s start off to thank the ones that helped me lately. I almost feel bad for how many questions I have asked in the last weeks, but the answers were always of great help, so thanks for that! And yet I have another question. As described in my…

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Functional succinate dehydrogenase deficiency is a common adverse feature of clear cell renal cancer

Clear cell renal cell carcinoma (ccRCC) is by far the most common type of kidney cancer, accounting for ∼80% of all kidney cancers (1). Despite recent advances, metastatic ccRCC is a generally incurable malignancy, with a 5-y survival rate <20%, highlighting the need for further biologic and therapeutic insights in…

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Proper way(s) to perform enrichment analysis in R

I am not sure what is the proper way to carry out over-representation analysis (and also gene set enrichment analysis) for RNAseq data. Ideally, the analysis can be performed in R, otherwise, if the software/ platform can export the output file (also include all the non-statistical-significant term) will also be…

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clusterProfiler won’t read gene list

clusterProfiler won’t read gene list 0 So I have a list of DE genes that I would like to analyse for enriched GO and KEGG terms. I was going to use clusterProfiler for this, but I can’t seem to get past constructing the gene list. I have followed the vignette…

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Identification of Prognosis-Associated Biomarkers in Thyroid Carcinoma

Introduction Thyroid cancer (TC) is a common endocrine malignancy with a rapidly increasing incidence worldwide, and the estimated new cases and deaths are notably higher in women than in men.1 Papillary thyroid carcinoma (PTC) is identified as the most common pathological type of TC, and accounts for approximately 80–85% of…

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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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Visualization of GO results using enrichplot

Visualization of GO results using enrichplot 0 Hello I am doing gene set analysis on DNA methylation microarray data (Illumina 450k and EPIC), and use the missMethyl package to do the analysis, and want to keep using that package because it accounts for some biases that occur when extracting the…

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Bioconductor – ttgsea (development version)

DOI: 10.18129/B9.bioc.ttgsea     This is the development version of ttgsea; for the stable release version, see ttgsea. Tokenizing Text of Gene Set Enrichment Analysis Bioconductor version: Development (3.14) Functional enrichment analysis methods such as gene set enrichment analysis (GSEA) have been widely used for analyzing gene expression data. GSEA…

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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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gct output in DESeq2

gct output in DESeq2 2 Hi everyone, I’m trying to analyze my counts data with DESeq2 and based on the tutorial of GSEA, DESeq2 has an output format that can be used directly in the GSEA (here). However, I’m reading their workflow and I don’t find how to make this…

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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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Sum of rows for GSEA analysis

Sum of rows for GSEA analysis 0 Hi, I have an issue which looks like easy to solve, but I’m stuck. I have a dataframe composed of columns (significant pathways retrieved from GSEA) and rows (entrez gene ids). In this data frame there are 1 if a gene is present…

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Predicting and characterizing a cancer dependency map of tumors with deep learning

INTRODUCTION The development of novel cancer therapies requires knowledge of specific biological pathways to target individual tumors and eradicate cancer cells. Toward this goal, the landscape of genetic vulnerabilities of cancer, or the cancer dependency map, is being systematically profiled. Using RNA interference (RNAi) loss-of-function screens, Marcotte et al. (1),…

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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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how to use ESTIMATE to infer tumor purity and stromal score from RNA-seq data?

how to use ESTIMATE to infer tumor purity and stromal score from RNA-seq data? 1 Dear all: Did anyone use ESTIMATE (bioinformatics.mdanderson.org/main/ESTIMATE:Overview) to infer tumor purity and stromal score from RNA-seq before? I am not clear how to use this tool and what is the input file format for this…

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GSEA and over-representation analysis of many genes

GSEA and over-representation analysis of many genes 0 Hello everyone! I’ve been doing some Differential Expression analysis on specific samples. It happens that I found a lot of genes that are DE. In total, of 24000 features, 11000 were up or down regulated in control vs group. Even tough the…

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