Tag: logFC

Single-cell RNA-seq workflow

In this tutorial we walk through a typical single-cell RNA-seq analysis using Bioconductor packages. We will try to cover data from different protocols, but some of the EDA/QC steps will be focused on the 10X Genomics Chromium protocol. We start from the output of the Cell Ranger preprocessing software. This…

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what is the best way to build my design model with DESeq2

Hello all, Hope you’re well. I would really appreciate it if you take some time and give me feedback on my experimental design. It is valuable to me. I am doing single nucleus RNA sequencing and using DESeq2 package for my DE analysis. My sample information is as below: Case:…

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A transcriptomic taxonomy of mouse brain-wide spinal projecting neurons

Animals All experimental procedures were performed in compliance with animal protocols approved by the Institutional Animal Care and Use Committee at Boston Children’s Hospital (Protocol no. 20-05-4165 R). Mice were provided with food and water ad libitum, housed on a 12-hour light/dark schedule (7 a.m.–7 p.m. light period) with no more than five mice…

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how to test for differential expression in samples where a global increase in gene expression is expected

As the title suggestions, I’m wondering what the best way to test each gene in a count matrix containing two groups is, where one group is expected to have a global increase in gene expression. I need to use spike-in normalized RPKM data, so from my understanding of DESeq, it…

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Exploration of the role of oxidative stress-related genes in LPS-induced acute lung injury via bioinformatics and experimental studies

Selection of 152 ALI-related genes (ALIRGs) by weighted gene co-expression network analysis (WGCNA) The samples of the GSE16409, GSE18341 and GSE102016 datasets were discretely distributed before merging, and the sample data (ALI = 21 and control = 14) was uniform after batch processing (Supplementary Fig. 1a,b). To identify the ALIRGs, the WGCNA was performed in…

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scRNA data analysis , how to compare pattern in multiple samples

Hello Everyone . I am new to single cell data . in this path G:\RNA\sc\scdata I have 3 files Sample5D_barcodes Sample5D_features Sample5D_matrix.mtx I want to see cell clusters and differentially expressed genes for this single cell sample. I am running this command in R install.packages(c(“Seurat”, “ggplot2”, “Matrix”, “dplyr”)) library(Seurat) library(ggplot2)…

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KCouper/Liverpool K-means RNAseq Analysis November 2020

R3 VAR14 vs RBC no TNF k-means q0.05 1. Genelist Selection groupsName<-“R3_VAR14_kmeans_q0.05” countsTable<-read.delim(“RNAseq2019July_5.txt”, header = TRUE, sep = “\t”,check.names=FALSE,row.names=1) head(countsTable) AllGeneNames<-countsTable$Gene_Symbol #head(AllGeneNames) tempA<-countsTable topDEgenes <- which(tempA$padj_R3noTNF_var14_vs_RBC_0h<0.05&!is.na(tempA$padj_R3noTNF_var14_vs_RBC_0h))####find indexes listA<-tempA[ topDEgenes, ]$Gene_Symbol topDEgenes <- which(tempA$padj_R3noTNF_var14_vs_RBC_2h<0.05&!is.na(tempA$padj_R3noTNF_var14_vs_RBC_2h))####find indexes listB<-tempA[ topDEgenes, ]$Gene_Symbol topDEgenes <- which(tempA$padj_R3noTNF_var14_vs_RBC_6h<0.05&!is.na(tempA$padj_R3noTNF_var14_vs_RBC_6h))####find indexes listC<-tempA[ topDEgenes, ]$Gene_Symbol topDEgenes <- which(tempA$padj_R3noTNF_var14_vs_RBC_20h<0.05&!is.na(tempA$padj_R3noTNF_var14_vs_RBC_20h))####find indexes listD<-tempA[ topDEgenes,…

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Knockdown of GNL3L alleviates the progression of COPD

Introduction Chronic obstructive pulmonary disease (COPD) is a common chronic bronchitis disease characterized by persistent airflow limitation, which can be prevented and treated. COPD is the third leading cause of death in the world reported in 2020.1 With the progression of the disease, COPD will lead to respiratory failure, pulmonary…

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The effects of methylphenidate and atomoxetine on Drosophila brain at single-cell resolution and potential drug repurposing for ADHD treatment

Both MPH and ATX increase the locomotor activity of wild-type Drosophila To investigate the cell type-specific molecular mechanisms of ADHD drugs in the brain at single-cell resolution, we conducted behavioral experiments and scRNASEQ in wild-type (WT) adult male Drosophila melanogaster following exposure to MPH, ATX, and control treatment. Here, we…

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Differential Expression Analysis using Bioconductor (RStudio) and GEO2R (GEO)

Hello everyone, I’ve been having the same question for a while now. I’m also conducting my own analysis of differential expression on a microarray dataset in R. However, the data is different from the results obtained using GEO2R. Here’s my line of code: my_id <- “GSE80178” gse <- getGEO(my_id, GSEMatrix…

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Bioconductor – gg4way

DOI: 10.18129/B9.bioc.gg4way   4way Plots of Differential Expression Bioconductor version: Release (3.18) 4way plots enable a comparison of the logFC values from two contrasts of differential gene expression. The gg4way package creates 4way plots using the ggplot2 framework and supports popular Bioconductor objects. The package also provides information about the…

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GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership | Genome Biology

Models for single-cell ATAC-seq data In single-cell ATAC-seq data, \(x_{ij}\) is the number of unique reads mapping to peak or region j in cell i. Although \(x_{ij}\) can take non-negative integer values, it is common to “binarize” the accessibility data (e.g., [19, 74, 133,134,135]), meaning that \(x_{ij} = 1\) when…

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DE analysis in paired samples with limma

Hello! I am interested in doing DE analysis in 12 samples from 3 different patients (“id”). The samples have been sequenced using bulk RNA-seq in a specific group of isolated cells. I have treated the cells by doing a knock-out experiment to remove a gene (group1 as mutated “MUT” and…

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Signatures of necroptosis-related genes as diagnostic markers of endometriosis and their correlation with immune infiltration | BMC Women’s Health

Technical roadmap Figure 1. Fig. 1 Analysis of endometriosis-related differentially expressed genes Using the limma package, we first normalized the expression profile data of the endometriosis datasets, GSE7305 and GSE11691. The data distribution before and after standardized treatment is revealed in a box plot (Figs. 2A–D). We found that the data after…

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Can’t find a gene in single cell

Can’t find a gene in single cell 0 Hi Biostars, I have single-cell data with wild type and knock-out gene A. When I open the loupe file of both wild type and knock-out, I can find gene A in both samples. However, when I use Findallmarker() on the Seurat object…

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Immunosuppression causes dynamic changes in expression QTLs in psoriatic skin

Mapping eQTLs in patients with psoriasis We obtained longitudinal lesional and non-lesional skin biopsies from participants at baseline, during treatment, and at the time of psoriasis relapse after study medication withdrawal over a course of 22 months. We used genome-wide genotyping and RNA-seq to assay samples. After stringent quality control,…

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DeSeq2 data comparison and extracting outputs

Hi, I have an RNA-seq experiment where there are 2 conditions and 2 genotypes. I am trying to figure out how to output the 2 conditions with 2 genotypes from the dds object. I have read online resources, however, it is still not clear what is extracted. I followed and…

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DESeq2, results(dds, name = ) interpretation results

Hello together, hello Michael, I have an understanding problem using results(dds, …) I have RNAseq data and a grouping of two conditions with interaction of time with the defined reference levels, see code below. And run the code as below. coldata$Cond <- factor(coldata$Cond, levels = c(“A”,”B”)) coldata$Time <- factor(coldata$Time, levels…

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scRNAseq Differential expression analysis

Forum:scRNAseq Differential expression analysis 0 Hello everyone! I am a student that recently started working with transcriptomics data. I am trying to conduct my first single cell data analysis of an organoid model using mainly Seurat. I tried to conduct a differential expression analysis between different clusters using the FindMarkers()…

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High pvalues when using clusterProfiler for seurat

High pvalues when using clusterProfiler for seurat 0 Hi, I am trying to run clusterProfiler::GSEA version 4.8.3 for each cluster of my SeuratObj When ranking the DEG based on logFC I get decent ES/NES scores however my q/p values are usually > 0.05 sometimes even >0.5. However, when I re-run…

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Is it okay to just average the log2FC values across different cell types in pseudobulk scRNA-seq data?

Is it okay to just average the log2FC values across different cell types in pseudobulk scRNA-seq data? 0 Hi! I downloaded a differential gene expression summary data table like this from brainSCOPE. All I need is “gene” and “log2FoldChange” column. However, each gene’s data is split into multiple different cell…

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Why we are using filtering >0 for up and

Why we are using filtering >0 for up and <0 for down after TopTags() to extract de genes ids? 0 How to extract list of DE genes after EdgeR? With summary() I get number of Up and Down expressed genes. And I would like to extract the gene IDs for…

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RNA-sequencing and bioinformatics analysis | COPD

Introduction COPD, a common preventable and treatable disease characterized by persistent airflow limitation and respiratory symptoms, is associated with exposure to harmful environments. COPD is currently the third leading cause of death globally. The high incidence and mortality of COPD, which seriously threaten human health, represent a public health problem…

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Associating between results obtained after running Trinity’s run_DE_analysis.pl and genes

Associating between results obtained after running Trinity’s run_DE_analysis.pl and genes 0 Hi.How can one associate between the generic transcript names and the actual genes of the studied organism? Here are the first few lines of the output file kallisto.gene.counts.matrix.Control_vs_Serum.edgeR.DE_results (which I understood is the relevant one for differential expression analysis):…

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Meta analysis randon effects model and combined p-values

I am performing a meta analysis based on 10 different data sets (derived from different platforms and technologies (RNAseq as well as Microarray)). DGE analysis was pretty much straight forward and mostly performed using limma package. The experimental setup was nothing special, just a treatment (heat) vs. control design. So…

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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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Microarray DGE analysis

Microarray DGE analysis 1 Hi, www.ncbi.nlm.nih.gov/geo/geo2r/?acc=GSE30929 I have performed DGE analysis between WDLPS and DDLPS tumour samples in R and have the following results table. I ended up with the same results as the GEO2R. logFC AveExpr t P.Value adj.P.Val B 207175_at -5.7 8.8 -14 3.1e-25 7.0e-21 47 213706_at -3.5…

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Limma couldn’t find the differential gene

Limma couldn’t find the differential gene 1 Hi, I am using limma for differential gene analysis of RNA seq results. I have encountered the following issues: I cannot find any genes with significant padj values (less than 0.05). Although some genes have extremely high logFC values. (I use TPM values…

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Enricher with Gene Symbols

Enricher with Gene Symbols 0 Hi! I have a list of genes with abs(logfc) >= 0.9 like this: > genes [1] “MDM2” “CDK4” “CCND2” “FLNA” “RBP7” “EDNRB” “EPHA4” “PTPRB” “PPP1R13L” “TPM1” “INSR” [12] “DLC1” “WNT7B” “SFRP1” “IFI16” “ZMAT3” “MEST” “AKT3” “CD36” “SRD5A1” “KIF23” “EPOR” So the list has the gene…

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What are the reasons to find so few Differentially expressed genes (DEGs)?

What are the reasons to find so few Differentially expressed genes (DEGs)? 1 HI, After the differential gene expression analysis, I had got only 15 genes with logFC < 1.5. Is it because of the Transcriptome reference annotation, expression quantification method, and DEG detection methods which are affecting the optimal…

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LogFc vs t_statistic to estimate over/under expressed genes?

LogFc vs t_statistic to estimate over/under expressed genes? 0 Hi! I am doing DGE using limma+voom over two populations, I have a gene X that has significant adjusted p values yet logfc values of 0.6/0.7 which is below the threshold of 1. Additionally I did t test over the Voom$E…

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Make heatmap for RNA-seq with non replicate

Make heatmap for RNA-seq with non replicate 0 Hi all, degs = rownames(subset(DEG, PValue < 0.05 & abs(logFC > 9))) rownames(counts) = DEG[rownames(counts), ‘symbol’] counts_degs = counts[degs,] pheatmap(counts_degs, clustering_method = ‘ward.D’, scale=”row”) Could I use TPM matrix instead of raw count matrix to make heat map using the code above?…

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Similarities in gene expression between post-mortem and living human brains

An important objective of medical research is to identify the underlying molecular mechanisms of human brain health and diseases. This objective has been predominantly achieved through observational studies of gene expression in human brain tissues obtained from post-mortem brain donors for their analysis. Importantly, many of these studies are based…

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ComplexHeatmap with anno_barplot

I’ve been making various heatmaps for different gene sets and I added the log2FoldChange values as an extra column, but I need to leave it as a barplot, but I’ve been lost on how to put those log2FoldChange values to appear as bars. Any help is appreciated, thanks 😉 “`r…

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Direct inference and control of genetic population structure from RNA sequencing data

In this study, we constructed the RGStraP pipeline to calculate RG-PCs from genetic variants called from RNAseq data. RGStraP relies on GATK for its variant calling suite, as well as PLINK and flashPCA to filter the SNPs and calculate genetic principal components from them, respectively (Methods). We make RGStraP available…

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How to analyse a particular pathway after doing DGE?

How to analyse a particular pathway after doing DGE? 0 Let’s say I have a set of RNA-seq of 1500 genes and I did DGE over two groups and got a list os DGE genes. GSEA is out of question due to the 1500 gene set. I have done already…

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microRNA sequencing for biomarker detection in the diagnosis, classification and prognosis of Diffuse Large B Cell Lymphoma

In this study, we identified new signatures of miRNAs of relevance in DLBCL with potential to improve diagnosis, subtype characterization and treatment response through small RNA sequencing. To our knowledge, few reports exist in which miRNA sequencing were used to identify miRNA signatures in cancer, and only one which analyzed…

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Does the gene universe for enrichGo need to be a list of gene names?

Does the gene universe for enrichGo need to be a list of gene names? 1 Hello, When using the enrichGo does the gene universe need to be a gene list or can it be a named list with logfc? Currently I am doing this: genes <- names(gene_list)[abs(gene_list)> 0.9] go_enrich <-…

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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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Organization of the human intestine at single-cell resolution

Tissue collection and processing This study complies with all relevant ethical regulations and was approved by the Washington University Institutional Review Board and the Stanford University Institutional Review Board. Human bowel tissues were procured from deceased organ donors. Written informed consent was obtained from the next-of-kin for all donor participants….

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How to do GSEA over limma + voom DGE ?

I am doing DGE over RNASeq data of two types of cancer. Here is the code: keep <- filterByExpr(RNA_data, design = design) RNA_data <- RNA_data[keep,] RNA_data <- DGEList(counts = RNA_data, genes = rownames(RNA_data)) # Normalize the counts using the TMM method RNA_data <- calcNormFactors(RNA_data, method = “TMM”) # Create the…

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How to tune and use the MetaVolcanoR

I’m having some trouble with the MetaVolcanoR package. I asked about this at the Bioconductor support forum but there were no responses. I’ll try my luck here since I need all the help I can get. I have results of differential expression analysis from 17 datasets, using the LIMMA package….

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Strange clustering of genes with circlize

Hi! I’m trying to learn the circlize package and I get weird sorting. Can anyone please tell me why the most expressed and the least expressed gene is ending up where they are (see marking) and not following the gradient? data looks like this: From highest: … To lowest: This…

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How to extract list of top 10 markers from each cluster?

How to extract list of top 10 markers from each cluster? 0 I have a list (markers.l) of dataframes. Each dataframe denotes to one cluster. I try the following function to get the list of top 10 markers. # Extract top 10 markers per cluster top10 <- markers.l %>% mutate(avg_fc…

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Diagnosis in Ectopic Pregnancy | IJGM

Introduction As the leading cause of maternal mortality in early pregnancy, ectopic pregnancy (EP) is responsible for 4–10% of all pregnancy-related deaths,1 but drugs can only be used to treat early EP. However, significant differences in the effects on fertility between surgical treatment and medical treatment have been reported in…

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Identification of molecular mechanisms causing skin lesions of cutaneous leishmaniasis using weighted gene coexpression network analysis (WGCNA)

Data information We downloaded all the data used in this research from National Center for Biotechnology Information Gene Expression Omnibus (www.ncbi.nlm.nih.gov/geo/). We used the data set GSE1278317 to construct a co-expression network by Differential Gene Expression analysis (DGEs) and Weighted Gene Co-expression Network Analysis (WGCNA). The Data was obtained from…

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Why FindMarkers between conditions shows pct.1 and pct.2 as 1 for most of the genes?

Why FindMarkers between conditions shows pct.1 and pct.2 as 1 for most of the genes? 1 I have a Seurat object data which has identified seurat_clusters. And there are two conditions treatment and notreatment for this dataset. I performed DEA between conditions in a specific cluster 3 using the FindMarkers…

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Limma returned only positive logFC values

Limma returned only positive logFC values 0 I want to obtain the upregulated and downregulated genes using limma. However, all the DEGs returned by my code have positive LogFC and none are downregulated (negative LogFC). This observation is consistent across multiple distinct dataframes. Is there something wrong with my code?…

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Three genes expressed in relation to lipid metabolism considered as potential biomarkers for the diagnosis and treatment of diabetic peripheral neuropathy

Screening for pivotal genes in diabetic peripheral neuropathy In screening the DEGs, a total of 6 DPN samples and 6 control samples were included in the GEO dataset GSE95849, and this dataset was normalised. A principal component analysis (PCA) of GSE95849 was conducted to demonstrate clustering using scatter plots. Each…

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Enrichment Analysis, Clustering and Scoring with pathfindR

In this tutorial, I’ll try to provide a brief overview of the capabilities of our enrichment analysis R package pathfindR. The tool is in CRAN and its introductory vignette can be found here. We also have a detailed wiki. pathfindR is designed to improve enrichment analysis by firstly identifying active…

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IL5RA as an immunogenic cell death-related predictor in progression and therapeutic response of multiple myeloma

Differential expression analysis We downloaded GSE125361 (n = 48) microarray data from the Gene Expression Omnibus (GEO) database, which included 45 myeloma samples and 3 controls, for expression analysis of IL5RA in cancer16. Additionally, we analyzed the expression of IL5RA in smoldering myeloma (SMM) patients who progressed to active MM (n = 10) and…

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Plotting heat map with significance based on multiple columns

Plotting heat map with significance based on multiple columns 1 Hello Everyone, I have a data frame with columns having different sample information. It looks like this: Pathways s1_adjPval s1logFC s2_adjPval s2_logFC s3_adjPval s3_logFC X1 0.001 0.6 0.25 -0.6 0.002 0.34 I want to plot the graph in such a…

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Transcriptomic analysis of benznidazole-resistant and susceptible Trypanosoma cruzi populations | Parasites & Vectors

Overview of sample sequencing We compared the transcriptomes of BZ-resistant (17LER) and wild-type (17WTS) T. cruzi populations. cDNA libraries were constructed, sequenced and analysed for identifying the DE transcripts associated with resistance to BZ. The following parameters were evaluated using the read-quality analysis: (i) quantity of the sequenced reads; (ii)…

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Comparative transcriptomics

Comparative transcriptomics 0 Hi all, How can I compare different transcriptomics of different RNA-Seq data results? Each study is unique and comparing LogFC values directly doesn’t seem quite right to me. Is there a tool for compare them or does anyone recommend me a way to compare them ? rna-seq…

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Obtention of the binomial transformed count table with edgeR

Hello! When performing differential expression analysis with RNA-Seq data using DeSeq2, and after data normalisation, there is the option to extract a count table with the transformed abundance levels using the variance stabilisation transformation (vst) method. Line of code vst counts extraction: vst_dds <- vst(res) The DeSeq2 manual itself indicates…

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manually calculate log2 fold change and compare

Hi everybody, I am struggling trying to calculate log2FC manually with an RNA-seq experiment that has no replicates. I know this question has been posted but hadn’t been able to transfer the answers to my data. So I have 3 conditions, let’s say HpA, SpA and Empty. I would like…

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Comprehensive prediction of immune microenvironment and hot and cold tumor differentiation in cutaneous melanoma based on necroptosis-related lncRNA

Identify necroptosis-related lncRNAs in SKCM There are 386 necroptosis-related lncRNAs identified from the data of TCGA and GTEx, as the standard is the coefficients > 0.4 and P < 0.001. After that, flowing the differential expression analysis, 87 necroptosis-related lncRNAs were found to display significantly differential expression with the screen value as |logFC…

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Transformation of Log2FC to average logFC

Transformation of Log2FC to average logFC 1 Hey, I am actually trying to transform Log2FC to the average_logFC using R does any know to do it ? Thank you avg_logFC transformation log2FC to • 70 views • link updated 37 minutes ago by LChart 2.5k • written 2 hours ago…

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Error in `dplyr::mutate()`

Hey all, I am trying to run this script in R but due to some reason I am getting the following error, I don’t know what I am missing. Any help would be appreciated. library(“tidyverse”) library(“ggrepel”) library(“dplyr”) df |> dplyr::mutate( label=ifelse( avg_log2FC >= nth(avg_log2FC, 10, desc(avg_log2FC)) | avg_logFC <= nth(avg_log2FC,…

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p-fold plot

p-fold plot 1 I want to construct this plot, and I have already performed the DESeq analysis. This is how the data looks: Gene p_val avg_logFC pct.1 pct.2 p_val_adj HLA-B 1.69E-152 0.719935845 0.993 0.988 2.38E-148 VAMP5 2.73E-97 1.137804386 0.87 0.527 3.85E-93 PSME2 6.25E-88 0.820693535 0.965 0.88 8.80E-84 STAT1 1.03E-83 0.890453249…

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argument “colors” is missing, with no default

Error in colorRamp2(c(quantile(mean)[1], quantile(mean)[4], c(“white”, : argument “colors” is missing, with no default 0 col_AveExpr <- colorRamp2(c(quantile(mean)[1], quantile(mean)[4], c(“white”, “black”))) Error in colorRamp2(c(quantile(mean)[1], quantile(mean)[4], c(“white”, : argument “colors” is missing, with no default I am trying to make heatmap from sigs.df using complex heatmap, while making color code for average…

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RNA-seq meta-analysis using metafoR

Hi everyone, Apologies if this has been asked before and for the length of this post, but there seems to be a variety of answers out there for different types of studies, so I wasn’t sure if my approach was correct. I have 3 RNA-seq studies where I have performed…

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Downregulated ESRP1/2 promotes lung metastasis of bladder carcinoma through altering FGFR2 splicing and macrophage polarization

Introduction Among all common noncutaneous malignancies, bladder carcinoma (BC) is the fourth prevalent one in all patients from the United States, and a subset of BC can progress to a severe muscle invasive form, leading to distal metastasis to other organs, including liver, lung, bone and mediastinum (1). BC with…

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Inverted log2foldchange in study?

Hi guys, I’m relatively new to any type of analytics work and Rstudio. However, when inputting my TCGA data and doing all of the basic steps, my volcano plot and log2foldchange values seem to all be the opposite of what was expected. I understand perhaps this could just be the…

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suprisingly high logFC using limma

suprisingly high logFC using limma 1 Dear guys, Do you have any experience when using limma for one batch of proteomics data, the log2FC is surprisingly high (1500-3000), but when checking the expression matrix, the value among the samples are pretty similar. The design is ~0+ treatment, which seems quite…

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Cancers | Free Full-Text | CircRNA RNA hsa_circ_0008234 Promotes Colon Cancer Progression by Regulating the miR-338-3p/ETS1 Axis and PI3K/AKT/mTOR Signaling

Figure 1. Identification and validation of hsa_circ_0008234 in colon cancer Notes: (A): The highest five increased and decreased circRNAs between the normal and colon cancer tissue obtained from the GSE172229. (B): Volcano plot of the differentially expressed circRNAs with the threshold of |logFC| > 1 and p < 0.05. (C):…

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LIMMA calculates identical adj.P.Val for different proteins from proteomics

Hi, I am trying to calculate statistics for my proteomic data using LIMMA package so I can create some volcano plots. I have normalized log2 transformed intensities with imputed NA values for 2 samples each with 3 biological replicates so 6 columns (+1 annotations). When using LIMMA for some reason…

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KM Plot for gene of interest (e.g. TP53) using TCGA-PAAD dataset

Hello, I am new to bioinformatic analyses and I am trying to analyse the TCGA dataset to plot a survival curve based on the expression of a gene of interest (say TP53). I have written the following code to analyse the TCGA data, but I am unable to proceed further…

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Secondary Filtering of DE Results to Eliminate Lowly-Expressed Transcripts

Hello, I’m currently trying to analyze an RNA-seq data set of about 10500 samples (including biological replicates) and initially noticed some strange outputs in my differential expression output file. I am using the CIRIquant pipeline with the built-in differential expression function which uses the edgeR module to calculate DE circular…

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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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ASGARD is A Single-cell Guided Pipeline to Aid Repurposing of Drugs

Summary of a Single-cell Guided Pipeline to Aid Repurposing of Drugs Using scRNA-seq data, ASGARD repurposes drugs for disease by fully accounting for the cellular heterogeneity of patients (Fig. 1, Formula 1 in “Methods” section). In ASGARD, every cell cluster in the diseased sample is paired to that in the normal…

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Error when running Kruskal Wallis test in for loop

log_fc primer ID_1 category Avg_logfc primer_1 42 test_1 1.88444044 primer_2 43 test_1 0.8730141 primer_3 44 test_1 1.10542821 primer_4 45 test_1 0.79234524 primer_1 11 test_2 0.33098178 primer_2 12 test_2 0.66117247 primer_3 13 test_2 0.62520437 primer_4 14 test_2 0.21972443 primer_1 94 test_3 -0.96924447 primer_2 95 test_3 1.4806643 primer_3 96 test_3 1.83216384 primer_4…

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logFC is negative, need help to get it done

logFC is negative, need help to get it done 0 I had normalized count matrix with few negative values or I should say log transformed normalized matrix. I performed the following analysis in limma (the code is below). I got the results , I am getting all logfC value in…

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Third quartile normalized logFC data to find differentially express gene using limma

Third quartile normalized logFC data to find differentially express gene using limma 0 I have normalized count matrix which is normalized using conditional quantile normalization and having negative value, I understand that these are normalized logFC values. When I am directly using into limma with following command. It is showing…

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Identification of an unrecognized circRNA associated with development of renal fibrosis

Front Genet. 2022; 13: 964840. , 1 , 1 , 1 , 2 , 2 , 2 , 2 , 2 , 3 ,* and 4 ,* Yun Zhu 1 Department of Dermatology, The People’s Hospital of Yuxi City, Yuxi, China Weimin Yan 1 Department of Dermatology, The People’s Hospital…

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What are Differentially Expressed Genes ?!!

What are Differentially Expressed Genes ?!! 0 Hi, Believe me, I know what I am going to ask would sound stupid and repetitive. I did read through many of the articles available but still is confused. So, let’s say I am doing an RNA-seq DEG analysis with a dataset of…

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Bioinformatics construction and experimental validation of a cuproptosis-related lncRNA prognostic model in lung adenocarcinoma for immunotherapy response prediction

Data collection and processing The RNA-sequencing data, clinical information and simple nucleotide variation of LUAD patients were retrieved from TCGA database (portal.gdc.cancer.gov/, accessed April 8, 2022). Nineteen cuproptosis-related genes (CRG) were mainly collected from previous study, including LIPT1, GLS, NFE2L2, NLRP3, LIAS, ATP7B, ATP7A, SLC31A1, FDX1, LIPT2, DLD, DLAT, PDHA1,…

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DiffBind analysis report gives me two different outputs depending on when I apply a filtering threshold [eg: P-value=0.05, (abs)FC=1.1]

DiffBind analysis report gives me two different outputs depending on when I apply a filtering threshold [eg: P-value=0.05, (abs)FC=1.1] 1 Why is there a difference between the report outputs I get after dba.report, with a threshold set to P-value = 0.05 and fold=0.13750352375 [to get (abs)logFC=1.1], compared to when I…

Continue Reading DiffBind analysis report gives me two different outputs depending on when I apply a filtering threshold [eg: P-value=0.05, (abs)FC=1.1]

Scientists discover key ‘culprits’ in major lung cancer study

Fibroblast identification through single-cell RNA-sequencing analysis of whole-tissue homogenates derived from human NSCLC tumor samples. a Schematic illustrating sample processing and analysis methodology used to generate the target lung drop-seq (TLDS) dataset, comprised of human control (n = 6) and NSCLC (n = 12) samples. The Figure was partly generated using Servier Medical Art,…

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Recommendations needed for a tool for comparative gene set enrichment analyses via a webserver

Recommendations needed for a tool for comparative gene set enrichment analyses via a webserver 1 dear All, I’d like to compare 6 gene expression datasets (multiple conditions / time-points) in terms of joint patterns in the enrichments of the differentially expressed genes. The DEG lists I have prepared (logFC,padj). GO…

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GOplots::GOChord with heatmaps?

GOplots::GOChord with heatmaps? 0 @adrijakalvisa-22810 Last seen 16 hours ago Denmark Hi all, is there a way to add a gene expression heatmap option to GOplots::GOChord plot? Or multiple heatmaps at once? An example Chord plot: Fig 6 in PMID: 33674625. Here is what I tried: library(GOplot) data(EC) circ <-…

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cluster profiler for pathway analysis in scRNA Seq

Dear Community, I am trying to show pathway expression in 6 clusters that I identified in disease and control and would like to compare the corresponding clusters. I followed this post 438466 and used Pratik ‘s solution. Which gives me a plot only for the disease. However, I would like…

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limma issue (possibly a Galaxy issue)

limma issue (possibly a Galaxy issue) 0 I just wanted to alert the community to an issue I discovered while using limma on the Galaxy webserver. The issue arises when conducting differential expression between contrasts. The process is described on the galaxy server as follows: “Names of two groups to…

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Hugely different results between edgeR and DESeq2

Hugely different results between edgeR and DESeq2 0 I am working on a 18-patients dataset. I am trying to calculate DE genes with both EdgeR and DESeq2 for further analyses. Its a 2-factor design (Status, Fraction). I want to calculate DE genes of different Fractions using the Status as covariate….

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Estimating Fold-Changes of Lowly Expressed Genes

Estimating Fold-Changes of Lowly Expressed Genes 1 @vm-21340 Last seen 6 hours ago Brazil I am doing a DGE analysis using RNAseq data to compare three conditions. I am using a standard pipeline (Create DGEList > Filter very lowly expressed genes > TMM normalize > DGE). Since there is a…

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One-tailed test edgeR possible?

One-tailed test edgeR possible? 2 @2357cabb Last seen 19 hours ago Germany Is it possible to conduct a one-tailed differential expression analysis test using edgeR? I might have missed something in the documentation, but I cannot find anything definite. I mean by this conducting a test where I only look…

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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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Microarray DEG scatterplot

Hi, I have found that my selected gene, probe I.D 201667_at is differentially expressed between WDLPS and DDLPS tumour tissue samples after performing microarray DEG analysis. Instead of just a p value in a table format: Probe I.D “201667_at” logFC 10.8205874181535 AveExpr 10.6925705768407 t 82.8808890739766 P.Value 3.10189446528995e-88 adj.P Val 3.10189446528995e-88…

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Same results in Limma Toptable as in DESEQ2 results

Same results in Limma Toptable as in DESEQ2 results 1 Dear all, I am trying to generate exactly the same results in Limma for my result table as I did in DESEQ2 (Differential Expression Analysis). With the toptable function I am not getting lfcSE and basemean. Can anyone help me…

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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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DESeq2 aggregated single cell data

Hi, Im aiming to use aggregated single cell data to perform a pseudobulk analysis to assess differential expression between those with sarcopenia and those without, termed “status_binary” with the levels “yes” and “no”. # DESeq2 —————————————————————— dds <- DESeqDataSetFromMatrix(y$counts, colData = y$samples, design = ~Sex+age_scaled+status_binary) # Transform counts for data…

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use gene symbol in heatmap instead of ensemble geneID

Hi All I plot the heat map for my logCPM successfully but using Ensemble geneIDs. I need the heatmap to have the gene symbols, I can convert the ensemble gene IDs to gene IDs fine, but don’t know how to reflect this on the heatmap. My code for the heatmap…

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Bioinformatics analysis identifies widely expressed genes

1Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, People’s Republic of China; 2Department of Pediatrics, The Shanxi Medical University, Taiyuan, Shanxi, People’s Republic of China Correspondence: Jun Qian, Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, 230022, Anhui,…

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Cluster Profiler output not the same as Enrichr output

Cluster Profiler output not the same as Enrichr output 0 @angkoo-23537 Last seen 18 hours ago United Kingdom Hi there, I have am getting different outputs after running enrichGO on cluster profiler when I put the same genes into enrichR (by Maayan Lab) website. Example here using Biological Process 2021…

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Is there a way to mark up specific genes in MA-plot?

Is there a way to mark up specific genes in MA-plot? 1 Dear, everyone, I have this table, and created MAplot using the following steps. In this plot, I would like to mark up only the genes that I specify:for example, I would like to display the gene name in…

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Identification of a four-gene signature & PTC.

Introduction Thyroid carcinoma (THCA) is the most common type of endocrine malignancy and its incidence is increasing.1 Based on its histopathological characteristics, thyroid carcinoma can be classified into multiple subtypes, such as papillary thyroid carcinoma (PTC), follicular thyroid carcinoma, and anaplastic thyroid carcinoma.2 PTC is the most common subtype of…

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Large DE LogFC range

Large DE LogFC range 1 @3d20f23f Last seen 1 hour ago Italy I’m working with DESeq2 to make a DE analysis between samples in two different conditions. During the analysis, I identified a batch effect due to the sequencing time modelled as a covariate in the design formula. From the…

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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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sigh of log2FC values in DESeq2

sigh of log2FC values in DESeq2 0 @194b0276 Last seen 10 hours ago United States Can someone explain to me how is the sign of log2FoldChange is set in the results of DEseq2? I was pretty sure that it is calculated as log2(Counts_treatment/Count_reference), where reference is determined alphabetically (unless specified…

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Telling apart control and treatment groups in Seurat Visualizations

Hi, I saw on one of the Seurat data visualization tutorials that if you have a dataset you generated from an experiment, you can split a dataset into the control and the treatment. For example, if you have the following dataset where the metadata is clearly split into groups, you…

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