Tag: DESeq

Differentially expression analysis of orthologous genes between two species

Differentially expression analysis of orthologous genes between two species 1 @4dbfec5b Last seen 10 hours ago Netherlands Hi people, I want to use DESeq2 for differentially expression analysis of orthologous genes between two different species. I am not experienced at all using R and DESeq2, but I think at the…

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why do i get much more significant genes and wierd volcano plot with DESeq2 for my RNAseq dataand LRT not with Walds test

I’m looking into the differentially expressed genes in heat-stressed animals versus normal ones. I have a data matrix of 40 samples of different conditions and using contrast I compare each one to its the control. I want to look at the heat stressed the other 3 are non-stressed old versus…

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Assessing spermatozoal small ribonucleic acids and their relationship to blastocyst development in idiopathic infertile males

Vander, B. M. & Wyns, C. Fertility and infertility: Definition and epidemiology. Clin. Biochem. 62, (2018). Sun, H. et al. Global, regional, and national prevalence and disability-adjusted life-years for infertility in 195 countries and territories, 1990–2017: Results from a global burden of disease study, 2017. Aging 11, 10952 (2019). Article …

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Higher Dimensional RNASeq Clustering Significance

Higher Dimensional RNASeq Clustering Significance 0 @73ef4518 Last seen 29 minutes ago United States Looking at the principal components of our RNASeq data, there is clear separation between the diseased and controlled, however, this separation is in the 5th principal component, which only accounts for 0.45% of variance. There is…

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Error in DESeqDataSetFromHTSeqCount

I am using HTseq pipeline for DESeq2: Directory = “/Users/abhaykanodia/Desktop/smallRNA/” condition = c(“WT1”, “WT2”, “WT3”, “NTC1”, “NTC2”, “NTC3) sampleFiles= c(“AK1a_counts.txt”,”AK2a_counts.txt”,”AK3a_counts.txt”,” AK4a_counts.txt”,”AK5a_counts.txt”,”AK6a_counts.txt”) sampleName = c(“AK1”, “AK2”, “AK3”, “AK4”, “AK5”, “AK6”) sampleTable <- data.frame(sampleName = sampleName, fileName = sampleFiles, condition = condition) sampleTable The output is: sampleName fileName condition 1 AK1 AK1a_counts.txt…

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How to check gene properties (eg GC, repetitiveness, average expression level)?

How to check gene properties (eg GC, repetitiveness, average expression level)? 0 Hello, I am trying to compare the data from 2 sequencing machines. I aligned my data with Kallisto and then I performed DESeq2 like I normally do. I was checking to see if I was getting similar results…

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Extra-hematopoietic immunomodulatory role of the guanine-exchange factor DOCK2

Cell isolation, reprogramming and culture Approval was obtained for human cell and tissue sample collection and genetic reprogramming from the Institutional Review Board (protocols 19–252, 18–243, 21–060, 19–284 and 415-E/1776/4-2014, Ethics Committee of the province of Salzburg). Adult samples were collected in accordance with the Declaration of Helsinki after written…

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normalization of ChIP-seq data by using the spike-ins or by using total library sizes

Dear all, This question may have been asked before, I have searched the mailing list and I can not find an answer. The question is about the correct way of setting the SizeFactors() in DESeq2 in 3 situations. I would like to double check with you. Although the R code…

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Interpreting time-series analysis with DESeq2 output

Interpreting time-series analysis with DESeq2 output 1 Hello all, I read and followed time course experiment mentioned in DESeq2 vignette bioconductor.org/packages/release/workflows/vignettes/rnaseqGene/inst/doc/rnaseqGene.html#time-course-experiments Please see attached figure which was generated with this model: LRT p-value: ‘~ strain + minute + strain:minute’ vs ‘~ strain + minute’ I have also generated a similar…

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Quantifying Peak Height Difference in ATAC-seq

Quantifying Peak Height Difference in ATAC-seq 1 Hi, everyone. How would I go about quantifying the peak height difference of a particular gene between two a wild type and a mutant in ATAC-seq? A colleague mentioned possibly calculating a moving average of read depths for smoothing and then comparing the…

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Nociceptor neurons affect cancer immunosurveillance

Secondary use of biopsies as research specimens The ten melanoma samples used in this study were collected by Sanford Health and classified by a board-certified pathologist. Their secondary use as research specimens (fully de-identified formalin-fixed, paraffin-embedded (FFPE) blocks) was approved under Sanford Health IRB protocol 640 (titled ‘Understanding and improving…

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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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DESeq2 design formula considerations

nhaus – This question has been asked many times both here as well as on other fora, for instance the bioconductor forum. Mike Love (the author of the DESeq2 software) has probably answered this question 50-60 times, if I had to guess, so you can find a lot on this…

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drug sensitivity prediction

drug sensitivity prediction 0 Dear all, I have been working on OncoPredict. I was able to reproduce results of calcPhenotype() using the example data. But i am bit confused with the input data. What are column and rows in each datasets used trainingExprData, trainingPtype and testExprData I have data downloaded…

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r – Cannot install bioconductor DESeq2 package on M1 mac … any advice?

This is where the installation failed. I tried installing DESeq2 on “R Studio Cloud” and it worked. I am assuming this is a mac issue. If anyone knows what to do I would very much appreciate it! Very new to R so anything will help. make: /opt/R/arm64/bin/gfortran: No such file…

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Comprehensive Analysis of NPSR1-AS1 as a Novel Diagnostic and Prognostic Biomarker Involved in Immune Infiltrates in Lung Adenocarcinoma

The incidence of lung adenocarcinoma (LUAD), the most common subtype of lung cancer, continues to make lung cancer the largest cause of cancer-related deaths worldwide. Long noncoding RNAs (lncRNAs) have been shown to have a significant role in both the onset and progression of lung cancer. In this study, we…

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Combine scRNAseq data for bulk analysis using DESeq2

Combine scRNAseq data for bulk analysis using DESeq2 0 @evocanres-17914 Last seen 2 hours ago United States I have scRNAseq data from Fluidigm C1 platform, but I have low number of cells (sample 1 ~30, sample 2 ~ 20). Can I merge the fastq files for each samples and treat…

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Opposing roles of hepatic stellate cell subpopulations in hepatocarcinogenesis

Villanueva, A. Hepatocellular carcinoma. N. Engl. J. Med. 380, 1450–1462 (2019). CAS  PubMed  Article  Google Scholar  Affo, S., Yu, L. X. & Schwabe, R. F. The role of cancer-associated fibroblasts and fibrosis in liver cancer. Annu. Rev. Pathol. 12, 153–186 (2017). CAS  PubMed  Article  Google Scholar  Mederacke, I. et al….

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Deseq2 Output Explained With Code Examples

Deseq2 Output Explained With Code Examples In this session, we are going to try to solve the Deseq2 Output Explained puzzle by using the computer language. The code that follows serves as an illustration of this point. Column Description 1 Gene Identifiers 2 mean normalised counts, averaged over all samples…

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DESeq2. Multi-factor Interactions designs

DESeq2. Multi-factor Interactions designs 0 Dear all, I want to get your feedback, please !! I have gene expression data from two tissue(Tissue_1 and Tissue_2) in three conditions(A, B and C). I want to get genes upregulated in Tissue_2 in condition C vs A+B. I was trying this, but not…

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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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Multiple conditions DESeq2

Multiple conditions DESeq2 1 Hi, I am working on differentially expressed genes analysis of RNA-seq data extracted from multiple but related experiments: experiment DESH21_E DESH40_S DESN21_E DESN21_S DESN40_E DESN40_S ES21_E ES21_S ES40_E ES40_S where, DES and ES are different in vitro cells; 21/40 are concentration (low/high), and H/N are additional…

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deseq2 – Creating multiple phenotype datasets using bootstrap method “Bootstrap-samples-by-column-of-a-data-frame-in-r” for DEG analysis

I am working on a datasets and after some discussion with my group, we doubt that maybe one or more of our controls are different than the other controls. The motivation is to see if one or more controls have been effected differently by the solvent they were kept in….

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Exporting DESeq2 results to CSV files

Exporting DESeq2 results to CSV files 1 Hello there. I need a help with this situation. I’m following this vignette and I’m getting an error on the item “Exporting results to CSV files”: write.csv(as.data.frame(resOrdered), file=”condition_treated_results.csv”) In my case i get this: write.csv(as.data.frame(resOrdered), file = “myres_counts.csv”) error in evaluating the argument…

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Evolution of stickleback spines through independent cis-regulatory changes at HOXDB

Darwin, C. On the Origin of Species by Means of Natural Selection (John Murray, 1859). Owen, R. On the Archetype and Homologies of the Vertebrate Skeleton (Richard and John E. Taylor, 1848). Stern, D. L. & Orgogozo, V. Is genetic evolution predictable? Science 323, 746–751 (2009). CAS  PubMed  PubMed Central …

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Log2FC values slightly higher in some genes after DESeq2 shrinkage

Hi, I have a question about DESeq2 LFCshrinkage: Is it possible that some genes have a slightly higher LFC after shrinkage? It happened during my RNAseq DE analysis, I have very deeply sequenced samples with large base means. I tried visualizing using MAplot check, and it looks fine. I’m mainly…

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NODULIN HOMEOBOX is required for heterochromatin homeostasis in Arabidopsis

NDX is a heterochromatin-associated factor To understand the genome-wide regulatory roles of NDX, we first analyzed its genomic distribution. For this, we performed chromatin immunoprecipitation sequencing (ChIP-seq) in 10-day old Arabidopsis seedlings expressing N-terminally and C-terminally tagged NDX fusion proteins (flag-NDX/ndx1-1(FRI)/flc-2 and NDX-GFP/ndx1-1(FRI)/flc-2, respectively) expressed from their endogenous promoter21,32. The…

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Long non-coding RNA SNHG6 couples cholesterol sensing with mTORC1 activation in hepatocellular carcinoma

Chu, B. B. et al. Cholesterol transport through lysosome-peroxisome membrane contacts. Cell 161, 291–306 (2015). CAS  Article  Google Scholar  Luo, J., Yang, H. & Song, B. L. Mechanisms and regulation of cholesterol homeostasis. Nat. Rev. Mol. Cell Biol. 21, 225–245 (2020). CAS  Article  Google Scholar  Luo, J., Jiang, L., Yang,…

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Time course RNA seq with DESEq2

Hi all, Hope you are well. I am running time course experiment to examine differentially expressed genes from tumour tissues between two conditions, radiotherapy and sham-radiotherpapy groups at 4 time points post radiotherapy. Each time point had size matched untreated controls. I used the following code to run model with…

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TPM normalization starting with read counts

Hello everyone I have multiple bulk RNA-seq datasets that I need to apply the same pipe line on. I want to normalize them from counts data to TPM. In all datasets, I have the genes as rows, and samples as columns. Unfortunately, I don’t have the fastq files, all I…

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between results of RNAseq and absence/presence of Type3 Secretion System

Correlation between two different datasets: between results of RNAseq and absence/presence of Type3 Secretion System 1 Dear All, I have a “How would you solve” kind of question. I have two sets of tables : 1. Log2FoldChange table and 2. Effectors Table. Firstly, the Log2FoldChange table was obtained by performing…

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Feature selection for a binary classifier using mixed cancer type samples

Feature selection for a binary classifier using mixed cancer type samples 0 Hi all, I am not an expert in machine learning (ML) and have a few specific questions regarding the design of a binary classifier. I have bulk RNA-seq data for the samples from 6 different cancer types. These…

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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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I have a query regarding differential gene expression using limma-voom.

I have a query regarding differential gene expression using limma-voom. 1 @28946033 Last seen 1 day ago India I used the following pipeline for RNA Seq Analysis Fastq-Trimmomatic- Hisat2(gtf file was annotated)-featurecounts After featurecounts I tried to do limmavoom, but I get error saying this An error occurred with this…

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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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Batch effect correction in 2 conditions + 2 genotypes + interaction term design

Dear all, I am analyzing RNAseq data with DESeq2 for a dataset that resemble the type “2 conditions, 2 genotypes and interaction term”; specifically I have healthy donors and patients for both male and female population. I am interested in obtaining: 1- genes modulated in male patients as compared to…

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DESeq2 analysis has not been run for this contrast

DESeq2 analysis has not been run for this contrast 1 @e16bdcce Last seen 10 hours ago Hong Kong error :DESeq2 analysis has not been run for this contrast DB.DESeq2 = 0 I think until this step everything is ok here is my file↓ here is my code ↓ # dbObj_contrast…

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lncRNA analysis tutorial

lncRNA analysis tutorial 2 hello, I would like to ask if there is some good tutorial concerning analysis of lncRNA along RNAseq analysis? like practical example. thank you for your help. lncRNA RNA-seq • 458 views Generally speaking, doing differential expression (DE) or transcript discovery on lncRNA is no different…

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Seeking help in multifactor differential gene expression analysis using DESeq2. Can not get significance difference while comparing 3 time factor (0,2 and 4h) with 3 group (1 control, 2 treated)

Dear Experts, I have RNAseq data from 6 different plant samples (2 control, 2 Sensitive, and 2 tolerance), and different location of one species. I am trying to see the effect of the different groups at different time points, but after going through all the posts and vignettes I am…

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Hisat2 – stringtie – deseq2 pipeline for bulk RNA seq

Software official website : Hisat2: Manual | HISAT2 StringTie:StringTie article :Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown | Nature Protocols It is recommended to watch the nanny level tutorial : 1. RNA-seq : Hisat2+Stringtie+DESeq2 – Hengnuo Xinzhi 2. RNA-seq use hisat2、stringtie、DESeq2 analysis – Simple books Basic usage…

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Getting the best of RNA-Seq

Forum:Getting the best of RNA-Seq 0 This is not a banal discussion. I am facing some problems with the analysis of DE genes in mouse. Most methods of analysis of DE genes must face two considerations or challenges. The first needs to take into consideration the existence and the different…

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Difference in number of DEGs from Deseq2 and limma-voom

Difference in number of DEGs from Deseq2 and limma-voom 0 Hello, I have RNA-seq data from two different treatment groups (F and NF ) at 2 different time points (T1 and T2). The mapping was done with STAR aligner and the quantification was done with FeatureCounts. I run differential expression…

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Multiple disease condition vs Normal

DESeq2: Multiple disease condition vs Normal 0 Hello! I have an mRNA dataset with one cell type and 3 different conditions (Metastatic, Primary Tumor, and Solid Tissue Normal). I would like to compare the two diseased conditions with the normal. I am using the following code but getting the understated…

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Multifactor analysis

Multifactor analysis 1 @66dd6104 Last seen 1 day ago United States HI every one I am new to RNA seq analyisis using R. I Am usig DESeq 2 for my analysis. I have four different Samples with three replicates each and I want to compare all of them with control…

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Running DESeq2 from rpy2 – Askdevz

If you open R and type: you will see that the assay function is not actually coming from DESeq2, but from its dependency which is called SummarizedExperiment: > assay standardGeneric for “assay” defined from package “SummarizedExperiment” function (x, i, withDimnames = TRUE, …) standardGeneric(“assay”) <bytecode: 0x5586a354db90> <environment: 0x5586a3535e20> Methods may…

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rna seq – R – [DESeq2] – How use TMM normalized counts (from EdgeR) in inputs for DESeq2?

I have several RNAseq samples, from different experimental conditions. After sequencing, and alignment to reference genome, I merged the raw counts to get a dataframe that looks like this: > df_merge T0 DJ21 DJ24 DJ29 DJ32 Rec2 Rec6 Rec9 G10 421 200 350 288 284 198 314 165 G1000 17208…

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DESeq2 and WGCNA

DESeq2 and WGCNA 0 I am currently performing an RNAseq analysis with a dataset from a GeneAtlas where I’ve identified DEGs from different comparisons. I want to now do a co-expression analysis with these comparisons and was wondering if anybody had suggestions of tutorials I could be directed to. I…

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Deseq2 Multifactor Design – Design Forum

Deseq2 multifactor design – In fact, deseq2 can analyze any possible experimental design that can be expressed with fixed effects terms (multiple factors, designs with interactions, designs with continuous variables, splines, and so on are all possible). We have searched different posts in different forums and i can’t figure out…

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InteractiveComplexHeatmap on DESeq2 object with more than 2 groups

InteractiveComplexHeatmap on DESeq2 object with more than 2 groups 1 Hello all, I’m writing with the hope someone can clarify a doubt I have about the differential heatmap generated by the package InteractiveComplexHeatmap via the simple command interactivate(dds). I read the package documentation at bioconductor.org/packages/release/bioc/html/InteractiveComplexHeatmap.html, but I couldn’t find the…

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tReasure: R-based GUI package analyzing tRNA expression profiles from small RNA sequencing data | BMC Bioinformatics

tReasure (tRNA Expression Analysis Software Utilizing R for Easy use) is a graphical user interface (GUI) tool for the analysis of tRNA expression profiles from deep-sequencing data of small RNAs (small RNA-seq) using R packages. The whole analysis workflow, including the uploading of FASTQ files of small RNA-seq, quantification of…

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DESeq2 how to specify contrast to test difference of differences

I am trying to take the “difference of differences” in contrasts from two factors (sex and group). We have male and female animals (sex factor) that were untrained or trained for 1, 2, 4, or 8 weeks (group factor, i.e., “control”, “1w”, “2w”, “4w”, “8w”). I want to know the…

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Error in SummarizedExperiment

I have installed DESeq2 version 1.36.0 samples <- colnames(txi$counts) group <- as.factor(c(“control”,”control”,”control”,”control”,”control”,”diet”,”diet”,”diet”,”diet”,”diet”, “control”,”control”,”control”,”control”,”control”,”diet”,”diet”,”diet”,”diet”,”diet”,”diet”)) coldata <- data.frame(samples, group, stringsAsFactors = F) coldata <- coldata[,c(“samples”,”group”)] coldata$samples <- factor(coldata$samples) coldata$group <- factor(coldata$group) rownames(coldata) <- sub(“fb”, “”, rownames(coldata)) all(rownames(coldata$samples) %in% colnames(txi)) all(rownames(coldata) == colnames(txi)) TRUE library(DESeq2) ddsTxi <- DESeqDataSetFromTximport(txi, colData = coldata, design =…

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Genes looking differential abundant are not accoring to DESeq2

Genes looking differential abundant are not accoring to DESeq2 0 I have a metagenomic dataset crossing three time points from which I have mined CAZymes and am using DESeq2 to identify differentially abundant CAZymes from using trimmed mean depth generated my CoverM (very similar to Q2Q3 contig coverage). From this…

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Extremely different results for both EdgeR and DESeq2 analysis

Extremely different results for both EdgeR and DESeq2 analysis 1 @373f98d7 Last seen 23 hours ago Singapore Dear all, Upon comparing my results for the analysis between DESeq2 and EdgeR, I have realized that the 2 results obtained after DEG analysis are extremely different from each other. The thresholds I…

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RNA interference triggers that target SARS-CoV-2 genome

Coronavirus disease 2019 (COVID-19) vaccines have played a critical role in reducing transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. However, with emerging reports of waning vaccine efficacy, there remains an urgent need to develop prophylactic measures against COVID-19. In a recent study published on the bioRxiv*…

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Can Differential Isoform expression analysis can be performed using DESeq2 package

Can Differential Isoform expression analysis can be performed using DESeq2 package 0 @03ddb485 Last seen 9 hours ago India Hello, I am want to perform differential isoform expression (DIE) analysis for RNAseq data from human. Can I use DESeq2 for this by inputting the transcript level abundance and getting differential…

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Counts from recount3 for DESeq2 analysis

Hi, As the topic title suggests, I want to use RSE objects from recount3 for differential expression analysis with DESeq2. This is an ongoing project that I took over. Looking at what has already been done, there are two points I wonder about : 1 – I found that the…

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deseq2 problem

deseq2 problem 0 Hi I am trying to draw a PCA plot with DESeq2 but somehow I cannot use DESeq2 functions. It is a really simple code i wil be pasting below. > transform <- DESeq2::rlog(eliminated_data, blind = TRUE) Error in (function (classes, fdef, mtable) : unable to find an…

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scrnaseq – Normalization methods to combine scRNA-seq experiments with different sequencing depths

I don’t think you need to complicate the idea of normalisation by introducing machine learning classifiers as a necessary component. Normalisation is common when comparing different datasets for all differential analysis. If you have single cell data, have a look at integration techniques in the Seurat workflows: satijalab.org/seurat/articles/integration_rpca.html If you’ve…

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Condition shown as ‘Untreated vs. Treated’ in output of results() in DESeq2

Condition shown as ‘Untreated vs. Treated’ in output of results() in DESeq2 1 @bffcbc5f Last seen 16 hours ago United States of America I am trying to find differentially expressed genes using DESeq2 on some RNA-seq data. In the pheno data, there is a column named ‘condition’ with factored values…

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DESeq2 on allelic reads

DESeq2 on allelic reads 1 @ea088d93 Last seen 26 minutes ago Canada Hello, Can I use DESeq2 to perform differential gene expression on allelic reads? I have allelic reads quantified for each parental allele/copy I have 2 treatments (control vs ethanol-exposed) I want to perform differential gene expression to see…

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RNAseq data DEG analysis – DESeq2 normalized data

RNAseq data DEG analysis – DESeq2 normalized data 1 1) You can’t use because those data are already normalized and log-transformed. 3) RSEM expected_count is best to start off with for differential expression. Login before adding your answer. Traffic: 2089 users visited in the last hour Read more here: Source…

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Separate exogenous from endogenous transcripts using Salmon RNAseq DTU

Dear friends, We are trying to use Salmon for DTU analysis. We want to separate exogenous from endogenous transcripts by following this post www.biostars.org/p/443701/ and this paper f1000research.com/articles/7-952 We are focusing on a gene called ASCL1 (endo-ASCL1). We transduced cells with lentiviral vector containing ASCL1 ORF only (Lenti-ASCL1). There should…

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DESeq2 comparisons with multiple experimental variables?

Summary: I’m trying to get a series of pairwise comparisons of specific experimental variables while holding the other variables constant, and can’t figure out how to do it in DESeq2 I am running an circadian experiment with multiple disease states and experimental interventions, let’s say condition: high fat (HFC), normal…

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GDCquery_Maf error

GDCquery_Maf error 0 @76e1237b Last seen 1 day ago Singapore Hi all, I really need some help. I am trying to run GDCquery_Maf which worked fine until yesterday. Now I get the following error: Error in GDCquery(paste0(“TCGA-“, tumor), data.category = “Simple Nucleotide Variation”, : Please set a valid workflow.type argument…

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Subsetting DESEQ2 VST Microbiome Data

Subsetting DESEQ2 VST Microbiome Data 1 @f8d5630d Last seen 16 hours ago Germany Hello there, the question is a bit off topic I am currently using DESEQ2 to normalize 16S microbiome data as advised several times in the recent literature. Currently I am facing the problem that I have 16S…

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A comparison of transcriptome analysis methods with reference genome

Background: The application of RNA-seq technology has become more extensive and the number of analysis procedures available has increased over the past years. Selecting an appropriate workflow has become an important issue for researchers in the field. Methods: In our study, six popular analytical procedures/pipeline were compared using four RNA-seq…

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How to reduce the impact of one varaible in Deseq2 or edgeR for multivariate value analysis?

Hello, everyone, I’m recently meeting this problem with my analysis, which i’ve done a lots of research and asked people around but their answers are quite confusing, so if I can get more opinions, that’d be terrific and thanks at advance. So I’m doing an analysis of DEGs using Deseq2…

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Identification of potentially functional circular RNAs hsa_circ_0070934 and hsa_circ_0004315 as prognostic factors of hepatocellular carcinoma by integrated bioinformatics analysis

Rawla, P., Sunkara, T., Muralidharan, P. & Raj, J. P. Update in global trends and aetiology of hepatocellular carcinoma. Contemp. Oncol. (Poznan, Poland) 22, 141–150 (2018). CAS  Google Scholar  Kong, D. et al. Current statuses of molecular targeted and immune checkpoint therapies in hepatocellular carcinoma. Am. J. Cancer Res. 10,…

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How to pool phyloseq data?

How to pool phyloseq data? 0 @688ee615 Last seen 1 day ago United Kingdom I hope someone can help. I am trying to carry out some differential abundance analysis on some microbiome data that has come from a metabarcoding experiment using 16S illumina sequencing. I have processed my data using…

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Error on Rstudio cloud when installing DESeq2 package : rprogramming

Hi! I am using the free account on R studio cloud. And I am getting this error: * installing *source* package ‘DESeq2’ … ** using staged installation ** libs g++ -std=gnu++14 -I”/opt/R/4.1.2/lib/R/include” -DNDEBUG -I’/cloud/lib/x86_64-pc-linux-gnu-library/4.1/Rcpp/include’ -I’/cloud/lib/x86_64-pc-linux-gnu-library/4.1/RcppArmadillo/include’ -I/usr/local/include -fpic -g -O2 -c DESeq2.cpp -o DESeq2.o g++: fatal error: Killed signal terminated program…

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A genome-scale screen for synthetic drivers of T cell proliferation

Abramson, J. S. et al. Transcend NHL 001: immunotherapy with the CD19-directed CAR T-cell product JCAR017 results in high complete response rates in relapsed or refractory B-cell non-Hodgkin lymphoma. Blood 128, 4192–4192 (2016). Google Scholar  Shifrut, E. et al. Genome-wide CRISPR screens in primary human T cells reveal key regulators…

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r DESeq2 how to add coldata code example

Example: deseq2 output explained Column Description 1 Gene Identifiers 2 mean normalised counts, averaged over all samples from both conditions 3 the logarithm (to basis 2) of the fold change (See the note in inputs section) 4 standard error estimate for the log2 fold change estimate 5 Wald statistic 6…

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Pathway analysis of RNAseq data using goseq package

Hello, I have finished the RNA seq analysis and I am trying to perform some pathway analysis. I have used the gage package and I was looking online about another package called goseq that takes into account length bias. However, when I run the code I get an error. How…

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Loop through columns to generate PCA from DESeq2 data

I’d like to generate a PCA of my bulk RNAseq data, coloured by each of my variables in the DESeq2 object “vsd”. My current code looks like this (to generate a single plot): pcaData <- plotPCA(vsd, intgroup=c(“Age”, “BlastRate”), returnData=TRUE) percentVar <- round(100 * attr(pcaData, “percentVar”)) ggplot(pcaData, aes(PC1, PC2, color=Age, shape=BlastRate))…

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DESeq2 pseudotime series design?

DESeq2 pseudotime series design? 1 @jordiplanells-19865 Last seen 22 hours ago Sweden Hi all. First things first, sorry for posting one more question about experimental design and time series in DESeq2.We have performed RNA-seq with two different treatments (control and protein over-expression) in two different time points (t=0 and t=8h)….

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DESeq2 and high prefiltering cutoff

DESeq2 and high prefiltering cutoff 1 @255004b1 Last seen 3 hours ago United States Hi, I am curious about prefiltering with DESeq2. I understand from this site and reading the DESeq2 vignette that prefiletering is really unnecessary as DESeq2 has a stringent filtering that it does. However, I’m seeing better…

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Interactive Shiny App for Bulk Sequencing Data

calculate_condition_mean_sd_per_gene Calculate statistics for each gene of an expression matrix given a grouping crossPanel Generate the cross plot panel of the shiny app crossPanelServer Generate the cross plot panel of the shiny app crossPanelUI Generate the cross plot panel of the shiny app cross_plot Create a cross plot comparing differential…

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rna seq – How does DESeq2 “collapseReplicates()” function work on read counts data?

Comparing read counts from an RNA-seq experiment for two select genes before and after using DESeq2’s collapseReplicates() and plotCounts() functions yields interesting results: Before collapseReplicates() and plotCounts(): Geneid foo1.1 foo1.2 foo2.1 foo2.2 bar1.1 bar1.2 bar2.1 bar2.2 baz1.1 baz1.2 baz2.1 baz2.2 baz3.1 baz3.2 WASH7P 6 5 0 2 1 1 8…

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No such file or directory)

I have R(version 4.1.2) installed on Fedora35. When I tried to install “DESeq2”, I got the following warning. 1: .inet_warning(msg) : installation of package ‘genefilter’ had non-zero exit status 2: .inet_warning(msg) : installation of package ‘locfit’ had non-zero exit status 3: .inet_warning(msg) : installation of package ‘DESeq2’ had non-zero exit…

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nf-core/circrna

circRNA quantification, differential expression analysis and miRNA target prediction of RNA-Seq data Introduction nf-core/circrna is a best-practice analysis pipeline for the quantification, miRNA target prediction and differential expression analysis of circular RNAs in paired-end RNA sequencing data. The pipeline is built using Nextflow, a workflow tool to run tasks across…

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Butterfly eyespots evolved via cooption of an ancestral gene-regulatory network that also patterns antennae, legs, and wings

Although the hypothesis of gene-regulatory network (GRN) cooption is a plausible model to explain the origin of morphological novelties (1), there has been limited empirical evidence to show that this mechanism led to the origin of any novel trait. Several hypotheses have been proposed for the origin of butterfly eyespots,…

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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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use tcgabiolinks package to download TCGA data

TCGA Data download in terms of ease of use ,RTCGA The bag should be better , And because it’s already downloaded data , The use is relatively stable . But also because of the downloaded data , There is no guarantee that the data is new .TCGAbiolinks The package is…

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RNASeq deseq2

RNASeq deseq2 1 Hi friends I have RNASeq data fromTCGA as HT-seq format. I want to do Deseq2. some patient names are duplicated and deseq2 dose not accept them. How would I deal with the duplicated patients? deseq2 RNASeq • 229 views • link 1 day ago by Rob &utrif;…

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[BioC] DESeq2, plotting residuals vs.fitted values

On the scale of the counts, the fitted values are: assays(dds)[[“mu”]] to get the fitted values on the common scale, you just need to divideeach column by the size factor: fitted.common.scale = t( t( assays(dds)[[“mu”]] ) / sizeFactors(dds) ) So then the residuals are counts(dds, normalized=TRUE) – fitted.common.scale Dear All,I…

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RNA-Seq HTseq galaxy DE analysis

RNA-Seq HTseq galaxy DE analysis 0 Hi friends I have htseq data from TCGA. it contains patients name in first row and genes in first column : 200 columns and 20000 rows. I dont want deseq2 in R. this needs to be done in galaxy. my question is how to…

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Bioconductor – DaMiRseq (development version)

DOI: 10.18129/B9.bioc.DaMiRseq     This is the development version of DaMiRseq; for the stable release version, see DaMiRseq. Data Mining for RNA-seq data: normalization, feature selection and classification Bioconductor version: Development (3.15) The DaMiRseq package offers a tidy pipeline of data mining procedures to identify transcriptional biomarkers and exploit them…

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How to retrieve the batch corrected data frame when using Deseq in R?

How to retrieve the batch corrected data frame when using Deseq in R? 1 I have several different RNAseq dataframes that I have merged together; they are from different studies and are raw counts. I want to correct the merged dataframe for study batch effects without getting negative values (I…

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Profiling and functional characterization of maternal mRNA translation during mouse maternal-to-zygotic transition

INTRODUCTION Mammalian life starts with the fusion of two terminally differentiated gametes, sperm and oocyte, resulting in a totipotent zygote. After going through preimplantation development, the zygote reaches blastocyst before implantation. The two most important events taking place during preimplantation development are zygotic genome activation (ZGA) and the first cell…

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Multi-factor paired RNAseq differential analysis with DEseq2

Hello, I’m working with an RNAseq dataset that looks at plants that are either infected with a fungus or have been left uninfected. I have both male and female genotypes, and those have been cloned, with one clone of each genotype getting inoculated while the other clone serves as the…

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DESeq2 contrast multiple treated conditions versus multiple control conditions

I have 4 treated and 2 control samples each 3 reps. I would like to contrast treated 1,2,3 against 2 controls, and treated 4 against 2 controls. (condition <-factor(c(“treated1″,”treated1″,”treated2″,”treated2″,”treated3″,”treated3″,”treated4″,”treated4″,”control1″,”control1″,”control2″,”control2”))) (coldata <- data.frame(row.names=colnames(txi.g), condition)) dds <- DESeqDataSetFromTximport(txi.g, colData=coldata, design=~condition) dds <- DESeq(dds) res <- DESeq2::results(dds, contrast = list(c(“treated1″,”treated2″,”treated3”),c(“control1″,”control2”)), listValues = c(3,-3/5)…

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Bioinformatics Scientist Job Opening in Seattle, WA at Alpine Immune Sciences

Job Posting for Bioinformatics Scientist at Alpine Immune Sciences Alpine Immune Sciences is applying our platform discovery technology to bring innovative new therapies to people living with serious or life-threatening illnesses or conditions, such as cancer and autoimmune/inflammatory diseases. Exciting challenges lie ahead—guided by our core values, we’ll…

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Test if a gene is NOT differentially expressed in DESeq2?

Test if a gene is NOT differentially expressed in DESeq2? 1 @pennylane-21859 Last seen 1 day ago United States First, my apologies if this has been covered already. I thought for sure it would have been, but I can’t find the relevant info with my searches. It’s pretty obvious from…

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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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Which method works best for analysing ONE sample of scRNA-seq data?

Which method works best for analysing ONE sample of scRNA-seq data? 1 Hello, I currently have a single-cell RNA-seq (scRNA-seq) data of a single person (sample) and i want to perform DE analysis. However, when I run the DESeq() in the DESeq2 package, it shows an error about only one…

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DE analysis model matrix for paired samples

DE analysis model matrix for paired samples 1 @tkapell-14647 Last seen 2 hours ago Helmholtz Center Munich, Germany Hi, I am analyzing a NanoString dataset where the metadata look as below: The factor of interest is the “group” and both groups are found in each mouse (“mouseID”) (paired samples). I…

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normalization for unsupervised analysis by DESeq2

normalization for unsupervised analysis by DESeq2 1 Hi friends I want to use DESeq2 to normalize the raw count data to do PCA. I dont have colData. What code should I use? because in the DESeq2 workflow we need colData and design. thanks RNA-Seq • 216 views • link updated…

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rna seq – How does DESeq2 “collapseReplicates” work on read counts data?

Comparing read counts from an RNA-seq experiment for a couple select genes before and after using DESeq2’s collapseReplicates function yields interesting results: Before: Geneid foo1.1 foo1.2 foo2.1 foo2.2 foo3.1 foo3.2 bar1.1 bar1.2 bar2.1 bar2.2 bar3.1 bar3.2 baz1.1 baz1.2 baz2.1 baz2.2 baz3.1 baz3.2 WASH7P 6 5 0 2 7 3 1…

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DESeq2 input from GDAC firehose

Hi guys, I hope you are fine. I’m not good in English so if you couldn’t understand my question, please feel free to reply. I’m a beginner of bioinformatics. I want to practice differential expressed gene (DEG) analysis in R. The RNA seq data I used was downloaded from broad…

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