Tag: gsva

Deep learning-enabled breast cancer endocrine response determination from H&E staining based on ESR1 signaling activity

Burstein, H. J. Systemic therapy for estrogen receptor-positive, HER2-negative breast cancer. N. Engl. J. Med. 383, 2557–2570. doi.org/10.1056/NEJMra1307118 (2020). Article  CAS  PubMed  Google Scholar  Jeselsohn, R. M. The evolving use of SERDs in estrogen receptor-positive, HER2-negative metastatic breast cancer. Clin. Adv. Hematol. Oncol. 19, 428–431 (2021). PubMed  Google Scholar  McAndrew,…

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Bioconductor – octad (development version)

DOI: 10.18129/B9.bioc.octad   This is the development version of octad; for the stable release version, see octad. Open Cancer TherApeutic Discovery (OCTAD) Bioconductor version: Development (3.19) OCTAD provides a platform for virtually screening compounds targeting precise cancer patient groups. The essential idea is to identify drugs that reverse the gene…

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Music compensates for altered gene expression in age-related cognitive disorders

Global impact of music on the human transcriptome We first aimed at quantifying the global effect of music on the transcriptomes of the two groups of donors separately. ACD patients exposed to music showed 2.3 times more DEGs (n = 2605) than controls (n = 1148); Table 2. Moreover, while the proportion up-regulated/down-regulated DEGs…

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Comprehensive analysis of necroptotic patterns and associated immune landscapes in individualized treatment of skin cutaneous melanoma

Identification of the SKCM necroptosis cluster The comprehensive analysis encompassed a total of 803 patients drawn from five distinct melanoma cohorts, namely, TCGA-SKCM, GSE65094, GSE53118, GSE54467, and GSE19234. Employing an unsupervised clustering algorithm, we stratified melanoma patients based on their NRG expression profiles. This facilitated a deeper exploration of the…

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Pan-Cancer Analysis and Validation of Opioid-Related Receptors Reveals

Introduction The potential role of opioids used in oncology patients has been controversial. Epidemiological and retrospective studies have demonstrated that lower opioid doses and regional anesthesia (epidural, intrathecal, or paravertebral) for breast,1 colon,2 or melanoma3 are linked to lower rates of cancer recurrence, while general anesthesia with high opioid doses…

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Analysis of nucleoporin 107 overexpression

Introduction Lung cancer is one of the most common types of cancer worldwide and the leading cause of cancer death.1 The main category of lung cancer is non-small cell lung cancer, accounting for about 85%, and lung adenocarcinoma, as a kind of non-small cell lung cancer, is the most frequently…

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Bioinformatics analysis of immune cell infiltration patterns and potential diagnostic markers in atherosclerosis

A database in the Gene Set Enrichment Analysis (GSEA; www.gsea-msigdb.org/gsea/msigdb/index.jsp) platform10,11 was used to identify 134 GLN metabolism-associated genes. Weighted gene co-expression network analysis (WGCNA) and module screening GLN-associated gene sets were investigated using WGCNA. The results demonstrated that when the weighted value was 24 (Fig. 1A), scale independence was greater…

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TNRC18 engages H3K9me3 to mediate silencing of endogenous retrotransposons

Padeken, J., Methot, S. P. & Gasser, S. M. Establishment of H3K9-methylated heterochromatin and its functions in tissue differentiation and maintenance. Nat. Rev. Mol. Cell Biol. 23, 623–640 (2022). Article  CAS  PubMed  PubMed Central  Google Scholar  Tchasovnikarova, I. A. et al. Epigenetic silencing by the HUSH complex mediates position-effect variegation…

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Insights into expression patterns and immunotherapy response prediction

[1] D. Schadendorf, D. E. Fisher, C. Garbe, J. E. Gershenwald, J. Grob, A. Halpern, et al., Melanoma, Nat. Rev. Dis. Primers, 1 (2015), 15003. doi.org/10.1038/nrdp.2015.3 doi: 10.1038/nrdp.2015.3 [2] A. M. M. Eggermont, A. Spatz, C….

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GSVA Analysis

Hi All I am attempting to perform GSVA analysis in R. This is my code- library(GSVA) gene_expression <- as.matrix(read.csv(“C:/Users/Documents/expression data.csv”)) gene_expression_matrix <- gene_expression[, -1] # Exclude the first column with gene identifiers rownames(gene_expression_matrix) <- gene_expression[, 1] # Create a named list with a single gene set my_gene_set <- list( Angio…

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Molecular classification of hormone receptor-positive HER2-negative breast cancer

Siegel, R. L., Miller, K. D. & Jemal, A. Cancer statistics, 2020. CA Cancer J. Clin. 70, 7–30 (2020). Article  PubMed  Google Scholar  Huppert, L. A., Gumusay, O., Idossa, D. & Rugo, H. S. Systemic therapy for hormone receptor-positive/human epidermal growth factor receptor 2-negative early stage and metastatic breast cancer….

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Single-cell transcriptomes reveal a molecular link between diabetic kidney and retinal lesions

Animals The animal experiments were approved by the Institutional Animal Care and Use Committee of Jinling Hospital (Nanjing, China), in accordance with the approved guidelines of the Institutional Animal Care and Use Committee of Jinling Hospital. 7 weeks old male wild-type (wt) and leptin receptor-deficient (db/db) mice on the C57BLKS/J…

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Identification and Analysis of NET- related genes in OA

Introduction OA is a degenerative joint disease that primarily affects the elderly population. It is a multifactorial disorder with a complex pathogenesis, involving a variety of joint tissues. In addition to the well-established degradation of articular cartilage, OA encompasses a comprehensive joint pathology, encompassing the synovial membrane, subchondral bone, menisci,…

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Metabolic programs of T cell tissue residency empower tumour immunity

Masopust, D. & Soerens, A. G. Tissue-resident T cells and other resident leukocytes. Annu. Rev. Immunol. doi.org/10.1146/annurev-immunol-042617-053214 (2019). Park, S. L., Gebhardt, T. & Mackay, L. K. Tissue-resident memory T cells in cancer immunosurveillance. Trends Immunol. 40, 735–747 (2019). Article  CAS  PubMed  Google Scholar  Byrne, A. et al. Tissue-resident memory…

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Bioconductor – GSEABase

DOI: 10.18129/B9.bioc.GSEABase   This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see GSEABase. Gene set enrichment data structures and methods Bioconductor version: 3.16 This package provides classes and methods to support Gene Set Enrichment Analysis (GSEA). Author: Martin Morgan, Seth Falcon, Robert Gentleman Maintainer:…

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Comprehensive analysis of m6A regulators associated with immune infiltration in Hepatitis B virus-related hepatocellular carcinoma | BMC Gastroenterology

M6A regulators are likely to have a significant effect on HBV-related HCC Twenty m6A regulators, including 12 readers, 7 writers, and 1 eraser, were identified in the TCGA and GEO cohorts. The correlation network provided interactive information among the m6A regulators. The ratio of somatic mutations and CNV for the…

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Enrichment methods to differentiate ORA pathways state

Enrichment methods to differentiate ORA pathways state 0 It is know that some enrichment methods (Over representation analysis) methods do not take into account that downregulated genes in a pathway could result in the pathway being more active (see this answer for example). I’m curious if there is a better…

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Immune Cell Infiltration and Novel Biomarkers of CAD

Introduction Coronary artery disease (CAD) is a major cause of death and disability worldwide,1 and has been proved to be triggered by the interaction of environmental and genetic risk factors. It is considered to be a systemic, progressive inflammatory disease. The atherosclerotic plaque formed in CAD accumulates chronically in the…

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Decreased left heart flow in fetal lambs causes left heart hypoplasia and pro-fibrotic tissue remodeling

Coil implantation in fetal lambs We have complied with all relevant ethical regulations for animal testing. All procedures followed the Canadian Council on Animal Care guidelines and were approved by the University of Western Ontario Council on Animal Care (protocol 2010-257). Time-dated pregnant Dorset × Rideau Arcott ewes (gestational age 76 days,…

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Bioconductor – oppar

DOI: 10.18129/B9.bioc.oppar     Outlier profile and pathway analysis in R Bioconductor version: Release (3.5) The R implementation of mCOPA package published by Wang et al. (2012). Oppar provides methods for Cancer Outlier profile Analysis. Although initially developed to detect outlier genes in cancer studies, methods presented in oppar can…

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Identification and immunological characterization of cuproptosis-related molecular clusters in ulcerative colitis | BMC Gastroenterology

Patients with UC have dysregulated cuproptosis regulators and activated immune responses To clarify the biological functions of cuproptosis regulators in the occurrence and progression of UC. A detailed flow chart of the study process was shown in Fig. 1. We identified 12 CRGs as differentially expressed cuproptosis genes in the evaluation prediction…

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Integration of bulk RNA sequencing data and single-cell RNA sequencing analysis on the heterogeneity in patients with colorectal cancer

Bao X, Shi R, Zhao T, Wang Y, Anastasov N, Rosemann M et al (2021) Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels tumour heterogeneity plus M2-like tumour-associated macrophage infiltration and aggressiveness in TNBC. Cancer Immunol Immunother 70(1):189–202 Article  CAS  PubMed  Google Scholar  Becht E, McInnes L, Healy J,…

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Y chromosome loss in cancer drives growth by evasion of adaptive immunity

Caceres, A., Jene, A., Esko, T., Perez-Jurado, L. A. & Gonzalez, J. R. Extreme downregulation of chromosome Y and cancer risk in men. J. Natl Cancer Inst. 112, 913–920 (2020). Article  PubMed  PubMed Central  Google Scholar  Kido, T. & Lau, Y. F. Roles of the Y chromosome genes in human…

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Identification of macrophage-related genes in sepsis-induced ARDS using bioinformatics and machine learning

Screening of differentially expressed genes in GSE32707 According to the screening criteria of differentially expressed genes, there were 489 differentially expressed genes between the control and sepsis groups, of which 152 genes were downregulated in sepsis patients and 337 genes were upregulated in sepsis patients (Fig. 1A). In contrast, there were…

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Establishment of risk model, analysis of immunoinfiltration

Introduction Atrial fibrillation (AF) is a tachyarrhythmia whose incidence and prevalence are steadily increasing with better chronic disease management in the aging global population. As of 2020, 37.5 million patients worldwide were affected by AF, accounting for 0.51% of the global population.1 As a common arrhythmia, AF greatly increases the…

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Visualization App for RNASeq Differential Expression and Enrichment Analysis

Visualization App for RNASeq Differential Expression and Enrichment Analysis 0 Hello, I am looking to see what the latest and greatest is in terms of an app to visualize the results of a differential expression analysis of an RNASeq dataset, including any subsequent enrichment analyses. Ideally this app would take…

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Screening and verification of key ubiquitination genes

Introduction Liver cancer is the third most common cause of cancer death globally with hepatocellular carcinoma (HCC) accounting for the majority of liver cancer.1,2 Early HCC (stage I/II) treatment mainly includes radical surgical resection, radiofrequency ablation and liver transplantation.3,4 However, there is a lack of typical clinical symptoms with early-stage…

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Bioconductor – scFeatures (development version)

DOI: 10.18129/B9.bioc.scFeatures   This is the development version of scFeatures; for the stable release version, see scFeatures. scFeatures: Multi-view representations of single-cell and spatial data for disease outcome prediction Bioconductor version: Development (3.18) scFeatures constructs multi-view representations of single-cell and spatial data. scFeatures is a tool that generates multi-view representations…

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Bioconductor – sparseMatrixStats

DOI: 10.18129/B9.bioc.sparseMatrixStats     This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see sparseMatrixStats. Summary Statistics for Rows and Columns of Sparse Matrices Bioconductor version: 3.15 High performance functions for row and column operations on sparse matrices. For example: col / rowMeans2, col /…

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Job Opening – Bioinformatics Analyst – Cambridge, MA

job summary: We are seeking a Bioinformatics Analyst to assist in multi-omics data analysis and setup network biology pipelines for supporting target discovery programs and indication prioritization efforts. The role involves analyzing large collections of bulk and single cell transcriptomic data, performing differential expression analysis and meta-analysis and interpret results…

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Applications of single-cell RNA sequencing in drug discovery and development

DiMasi, J. A., Grabowski, H. G. & Hansen, R. W. Innovation in the pharmaceutical industry: new estimates of R&D costs. J. Health Econ. 47, 20–33 (2016). Article  PubMed  Google Scholar  Wouters, O. J., McKee, M. & Luyten, J. Estimated research and development investment needed to bring a new medicine to…

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How to aggregate pseudobulks: Normalization & Log-Transformation

How to aggregate pseudobulks: Normalization & Log-Transformation 1 I am currently working on a single-cell data analysis project, and I am facing a challenge regarding the aggregation of single-cell data into pseudobulks for input into the GSVA software. GSVA only accepts a gene X subject matrix, which means that pseudobulks…

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Molecular pathways identified from single nucleotide polymorphisms demonstrate mechanistic differences in systemic lupus erythematosus patients of Asian and European ancestry

Identification of ancestry-dependent and independent non-HLA SLE-associated variants and downstream target genes Despite the success achieved by GWAS in mapping polygenic disease risk loci in SLE, the biological implications of the majority of identified variants has remained unknown. To gain a broader view of how inherited genetic variation impacts disease…

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Differences between GSVA and GSEA?

Differences between GSVA and GSEA? 0 What are the differences between GSVA and GSEA? I got some idea from a toward data science post (link): “GSVA builds on top of GSEA where a set of genes is characterized between two condition groups defined in the sample. GSEA works on how…

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How to perform a gsva assessing for the directonality of the genes.

I have a signature composed of several genes, but not all the genes work in the same direction. In order to predict the outcome with my signature, some of them should be highly expressed while others should be lowly expressed. Generating a gsva as a summary of the expression seems…

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Comprehensive analysis of exosomal circRNA-miRNA-mRNA network in breast cancer

Background: Exosomal circRNAs played critical roles in tumor development and progression and might be novel biomarkers in the diagnosis and treatment of various cancers. However, the biological functions and clinical implications of exosomal circRNAs in breast cancer are unclear. Methods: Expression profiles of exosomal circRNAs in exoRBase 2.0 database were…

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Differential (pathways) expression testing using linear model packages in R (Limma & GSVA)

I’m a novice in this field, and I would be glad if anyone could provide some guidance on analysis of differential expression testing using linear model packages in R. I am running a test for differential expression at the pathway level using the lmfit function in limma on pathway activity…

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GSVA scores – positive and negative values

GSVA scores – positive and negative values – normalization prior to running PCA 1 I have a data frame with GSVA scores (positive and negative values) for gene modules that are important for my analyses. I want to normalize my data (GSVA scores) prior to calculating PCA, correlations, and also…

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Nidogen-2 (NID2) is a Key Factor in Collagen Causing Poor Response to

Yan Sha,1,&ast; An-qi Mao,1,&ast; Yuan-jie Liu,2 Jie-pin Li,2 Ya-ting Gong,3 Dong Xiao,1 Jun Huang,1 Yan-wei Gao,1 Mu-yao Wu,3 Hui Shen1 1Departments of Dermatology, Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Zhangjiagang, People’s Republic of China; 2Department of Oncology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu…

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Relationship between pan-cancer CLEC2B expression& melanoma

Introduction Melanoma is the deadliest type of skin cancer, with a rising yearly incidence.1,2 Despite the rapid development of checkpoint immunotherapy and targeted therapies, the main melanoma treatment methods include surgical resection and chemotherapy.3,4 Recent immunosuppressive agents increase the one-year survival rate of melanoma patients to more than 50%. However,…

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What are the differences between GSVA and ssGSEA (in layman’s term)?

What are the differences between GSVA and ssGSEA (in layman’s term)? 0 I know the Bioconductor vignettes for GSVA has a decent description of the methodological differences between the algorithms. However, I am still confused with the technical terms. May I know if there are any further references that explain…

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Combined scRNAseq and Bulk RNAseq Analysis to Reveal the Dual Roles of Oxidative Stress-Related Genes in Acute Myeloid Leukemia

Background. Oxidative stress (OS) can either lead to leukemogenesis or induce tumor cell death by inflammation and immune response accompanying the process of OS through chemotherapy. However, previous studies mainly focus on the level of OS state and the salient factors leading to tumorigenesis and progression of acute myeloid leukemia…

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Enolase-1 & prognosis & immune infiltration in breast cancer

Introduction Breast cancer is the most prevalent malignancy and the leading cause of cancer death in women worldwide.1 After its diagnosis, the most immediate challenge is to tailor treatment strategies and predict the prognosis; traditional clinicopathologic features, including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2…

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Single sample GSEA analysis

Single sample GSEA analysis 1 Hi, I sorted specific type of cells by FACS and subjected it to RNA-seq. I want to test the enrichment of target cell type. I want to perform analysis just like GSEA to show the enrichment and get the plot which is common for GSEA…

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Predicting severity in COVID-19 disease using sepsis blood gene expression signatures

Mechanisms of sepsis severity and mortality in COVID-19 patients To identify COVID-19 specific severity mechanisms, we initially compared the whole blood gene expression profiles associated with defined severity groups from a cohort of 124 patients recruited at various times relative to hospital admission. Patient severity was assessed using two measures,…

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Multi-level cellular and functional annotation of single-cell transcriptomes using scPipeline

Software Figure preparation: CorelDRAW x8 (Corel); Bioinformatic analyses: R v 4.0.3 (R Foundation for Statistical Computing). Computational resources Analyses were run on a desktop computer with an Intel Core i9-10900L CPU (3.70 GHz, 10 cores, 20 threads) with 120 GB RAM running Windows 10 Pro (v21H2). Data preprocessing scRNA-seq data sets…

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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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Immune Infiltration and N(6)-Methyladenosine ncRNA Isoform Detection in Acute Lung Injury

Acute lung injury (ALI) is a severe form of sepsis that is associated with a high rate of morbidity and death in critically ill individuals. The emergence of ALI is the result of several factors at work. Case mortality rates might range from 40% to 70%. Researchers have discovered that…

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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 – TBSignatureProfiler (development version)

DOI: 10.18129/B9.bioc.TBSignatureProfiler     This is the development version of TBSignatureProfiler; for the stable release version, see TBSignatureProfiler. Profile RNA-Seq Data Using TB Pathway Signatures Bioconductor version: Development (3.15) Gene signatures of TB progression, TB disease, and other TB disease states have been validated and published previously. This package aggregates…

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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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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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Bioconductor – TBSignatureProfiler

DOI: 10.18129/B9.bioc.TBSignatureProfiler     This package is for version 3.12 of Bioconductor; for the stable, up-to-date release version, see TBSignatureProfiler. Profile RA-Seq Data Using TB Pathway Signatures Bioconductor version: 3.12 Signatures of TB progression, TB disease, and other TB disease states have been created. This package makes it easy to…

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pughlab/inspire-genomics: Pan-cancer analysis of genomic and immune landscape profiles of metastatic solid tumors treated with pembrolizumab

Contents Serial circulating tumor DNA (ctDNA) monitoring is emerging as a non-invasive strategy to predict and monitor immune checkpoint blockade (ICB) therapeutic efficacy across cancer types. Yet, limited data exist to show the relationship between ctDNA dynamics and tumor genome and immune microenvironment in patients receiving ICB. Here, we present…

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Can I remove the control in differential expression analysis?

Hi there, Essentially, my experimental design is control vs treatment. Cells were sorted based on fluorescence, so there are 4 different “colors” of treated cells, i.e. red, green, green+red, and blue+green+red. I am interested in how the colors differ from one another. And, I have duplicates for all colors and…

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Bioconductor Forum

James W. MacDonald 57k 1 week, 5 days ago United States Answer: Biomart’s getBM returns no genes for an existing GO-term in grch38, and less the Michael Love 33k 1 week, 6 days ago United States Answer: Normalizing 5′ Nascent RNA-seq data to identify differentially expressed transcr Kevin Blighe 3.3k 2 weeks, 2 days ago Republic…

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Advice on organizing large GSVA heatmap

Advice on organizing large GSVA heatmap 1 Hi there, I wanted to get some advice on how you might make your heatmap easier to read. In my case, I generated a heatmap from GSVA data which I filtered to only include significant pathways, here. I wanted to see how each…

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GSVA R packages

GSVA R packages 1 Hello everyone, I’m trying to do a gene set varian analysis using R to detect a specific gene set signature of a specific pathway from 20 samples of RNA-seq. I have this files in BAM format but I don’t know what to do in order to…

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