Tag: ReactomePA

Bioconductor – clusterProfiler

DOI: 10.18129/B9.bioc.clusterProfiler     This package is for version 3.12 of Bioconductor; for the stable, up-to-date release version, see clusterProfiler. statistical analysis and visualization of functional profiles for genes and gene clusters Bioconductor version: 3.12 This package implements methods to analyze and visualize functional profiles (GO and KEGG) of gene…

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removeBatchEffect with non-linear model fit

removeBatchEffect with non-linear model fit 0 @2289c15f Last seen 6 hours ago Germany Hello, I am attempting to use limma’s removeBatchEffect for visualization purposes (heatmat & PCA) while fitting non-linear models (splines) to my expression data in DESeq2. Given that my design is balanced, would this approach work within the…

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Predicting missing values splines DESeq2

Hello, I am fitting splines in DESeq2 like so: dds <- DESeqDataSetFromMatrix(countData = counts, colData = coldata, design = ~ ns(age_scaled, df = 3)) Plotting later using the code Mike Love posted elsewhere: dat <- plotCounts(dds, gene, intgroup = c(“age”, “sex”, “genotype”), returnData = TRUE) %>% mutate(logmu = design_mat %*%…

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Bioconductor – ReactomePA

    This package is for version 2.12 of Bioconductor; for the stable, up-to-date release version, see ReactomePA. Reactome Pathway Analysis Bioconductor version: 2.12 This package provides functions for pathway analysis based on REACTOME pathway database. It will implement enrichment analysis, gene set enrichment analysis and functional modules detection. Author:…

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Errors in Functional Enrichment Analysis with Clusterprofiler

Errors in Functional Enrichment Analysis with Clusterprofiler 0 library(clusterProfiler)library(org.Hs.eg.db) library(tidyverse) library(DOSE) library(ReactomePA) library(enrichplot) library(fgsea) library(data.table) library(ggplot2) keytypes(org.Hs.eg.db) res = read.csv(“coex.Csv”) head(res) original_gene_list = res$correlation names(original_gene_list) <- res$gene gene_list<-na.omit(original_gene_list) gene_list = sort(gene_list, decreasing = TRUE) gse <- gseGO(geneList=gene_list, ont =”ALL”, keyType = “ENSEMBL”, minGSSize = 3, maxGSSize = 800, pvalueCutoff =…

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Whole exome sequencing and transcriptome analysis in two unrelated patients with novel SET mutations

Moeschler JB, Shevell M, Committee on G. Comprehensive evaluation of the child with intellectual disability or global developmental delays. Pediatrics. 2014;134:e903–18. PubMed  Google Scholar  Patel DR, Cabral MD, Ho A, Merrick J. A clinical primer on intellectual disability. Transl Pediatr. 2020;9:S23–35. PubMed  PubMed Central  Google Scholar  Baker K, Devine RT,…

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Handling NA’s in Deseq2

Hi everyone First of all thank you for making rna-seq data much more accessible to an average clinical doctor through the DEseq2 packages and vignettes. I am though running into some trouble: I have a dataset of Nanostring mRNA-data from clinical study, which later was followed up. I therefore have…

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Bioconductor – multiSight

DOI: 10.18129/B9.bioc.multiSight   Multi-omics Classification, Functional Enrichment and Network Inference analysis Bioconductor version: Release (3.17) multiSight is an R package providing functions to analyze your omic datasets in a multi-omics manner based on Stouffer’s p-value pooling and multi-block statistical methods. For each omic dataset you furnish, multiSight provides classification models…

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Bioconductor – reactome.db

    This package is for version 2.14 of Bioconductor; for the stable, up-to-date release version, see reactome.db. A set of annotation maps for reactome Bioconductor version: 2.14 A set of annotation maps for reactome assembled using data from reactome Author: Willem Ligtenberg Maintainer: Willem Ligtenberg <willem.ligtenberg at openanalytics.eu> Citation…

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