Bioconductor Forum

interface affect modeling results, within the context of differential expression analysis with DESeq2. I noticed that when I specified two models that from what I understand should decompose the data variance in equivalent...or maybe I missed something. As a toy example, I'm using the same "pasilla" dataset used in the DESeq2 tutorial. The sample meta data is given below. The `group` variable wa…

DESeq2

updated 22 hours ago • Ken C

Good day, Please help with batch option in Deseq2, I have the error below and can't understand the problem as for me my METADATA_RAT has nessesary columns txi.salmon_rat

BatchQC batchinDeseq2. columnsincolData.

updated 1 day ago • Galina

I have puzzling results from an RNA-Seq experiment. The experimental setup is 4 conditions: two tissues (cortex and striatum), and two treatments (drug and DMSO), each is in triplicate (12 samples total). I have set up my design model at the "group" level with no intercept, so that I could directly specify the desired contrast without releveling. Looking at the effect of the drug in the cortex I …

DESeq2 PCAplot RNA-Seq DesignModel

updated 2 days ago • shaunpeterson

Hi, I'm using the function RUVg in the RUVSeq package to analyse my RNA-seq data and then to DEseq2. I have 50 samples. Im following the steps of Love et al. where as factor k they propose k=1 (https://bioconductor.org/packages...packages/release/workflows/vignettes/rnaseqGene/inst/doc/rnaseqGene.html#using-ruv-with-deseq2) they use k=2. The problem is i dont know whick k to use and what is do…

RUVSeq RUVnormalize

updated 4 days ago • Ειρήνη

Hello everyone :) I have a three treatments (each treatment has 3 samples) gene expression matrix and my advisor wants me to do time course analysis with this data, while 3 treatments represents control, acute and chronic (0, 24h, 72h) respectively. I put the raw counts into R software ImpluseDE2 and get the time course result. Meanwhile, I also used DESeq2 to rlog normalize the same raw count, …

DESeq2 timecoursedata GeneExpression

updated 5 days ago • pangtaihin

Hello everybody, I have analysed my RNAseq dataset with RStudio and DESeq2. Now, I would like to use the output of DESeq2 to perform GO analysis. I am working with Verticillium dahlaie and I have

AnnotationForge

updated 5 days ago • ussarizona

Hi bioconductor community! I have performed a DE analysis using DESeq2, with conditions being carriers vs. non-carriers of a risk allele identifed from a GWAS study. The sample size is 131...Hi bioconductor community! I have performed a DE analysis using DESeq2, with conditions being carriers vs. non-carriers of a risk allele identifed from a GWAS study. The sample size is 131 with

DESeq2 DifferentialExpression

updated 5 days ago • Kasper

sub("\\_.*", "", colnames(counts)) meta <- read.csv("metadata.csv") meta <- meta[order(row.names(meta)),] Group <- factor(paste0("Mod", meta$Mod, "_D", meta$DIV)) head(Group) # [1] ModNone_D2 ModLALBA_D4 ModLALBA_D4 ModLALBA_D4...useMart("ENSEMBL_MART_ENSEMBL") mart <- useDataset("hsapiens_gene_ensembl", mart) ens <- row.names(y) …

DifferentialExpression TimeCourse timeOmics edgeR RNAseq

updated 6 days ago • Ashley

readme][1]. Two data sets are used to demonstrate the package, the first pca created takes a deseq2 object ([DESeq2 data][2]), and the second does not ([GEO data][3]). The eigencorplot() function is introduced on the GEO data, and I...am trying to figure out how to use it on the DESeq2 data. Can anyone explain why I can't get it to work, and offer a solution? It is clear the problem is associ…

DESeq2 eigencorplot PCAtools

updated 6 days ago • BioinfGuru

Hi, I am willing to try to perform a kind of differential analysis using DESeq2 among two groups of different species (same genus). I read what was posted previously in [this link][1] but unfortunately

DESeq2 normalization Normalization acrossspecies

updated 6 days ago • piemmea

specific problem. I'm using topGO on a set of DE genes from an RNA-seq experiment analyzed with DESeq2. I have log2FC values and adjusted p values as my criteria for DE. I want to run both a Fisher's test and a Kolmogorov-Smirnov

topGO

updated 9 days ago • adendekk

backticks as shown below ``` ountData3 <- read.csv("gene_count_matrix_nef.csv", header = T, row.names = 1) colData3 <- read.table("c_e_nef.txt", header = T, sep="\t") xpr_matrix_nef <- as.matrix(countData3) eset_nef <- ExpressionSet

Biobase

updated 9 days ago • NATASHA

i have normalized the data using deseq2 internal normalization method. But it seems that my original input data is same as the normalized output. i don't know...on adjusted p value <0.1 Code should be placed in three backticks as shown below ```r library(DESeq2) library(tidyverse) count_data <- read.csv('rawcount_data2.csv',row.names = 1) head(count_data) colData <- read.c…

DESeq2 rnaseqGene Normalization

updated 11 days ago • sajadahmad41454

I am new to DESeq2 and I'm trying to analyze some RIPSeq data. I have 2 conditions: tagged and untagged I have 2 assays: input and IP I want...I am new to DESeq2 and I'm trying to analyze some RIPSeq data. I have 2 conditions: tagged and untagged I have 2 assays: input and IP I want to

DESeq2 RIPSeq

updated 11 days ago • ck

followed by featurecounts for raw counts matrix. when i am trying to process the raw_counts using deseq2 the results are not satisfactory to me. please suggest me if it is something wrong with my data![input normalized file...1] this is the r-script which i am running ```r library(DESeq2) library(tidyverse) count_data <- read.csv('rawcount_data2.csv',row.names = 1) head(count_data) co…

DESeq2 DifferentialExpression rnaseqGene DifferentialRegulation

updated 12 days ago • sajadahmad41454

attr(,"package") [1] "DEXSeq" > write.table(results, "dexseq.tsv", sep="\t", quote=F, row.names=F) Error in write.table(results, "dexseq.tsv", sep = "\t", quote = F, row.names = F) : unimplemented type 'list' in 'EncodeElement...lt;- as.data.frame(results) > write.table(df_results , "dexseq.tsv", sep="\t", quote=F, row.names=F) Error in write.table(df_results, "dexseq.t…

DEXSeq

updated 14 days ago • Sara

Hi all, I try to make plot as the tutorial using the same code: stats <- with(results, setNames(logFC, row.names(results))) fgseaRes <- fgsea(pathways = c2_list, stats = stats, minSize=15, maxSize=500) topPathwaysUp <- fgseaRes[ES &gt...to make plot as the tutorial using the same code: stats <- with(results, setNames(logFC, row.na…

fgsea

updated 16 days ago • Chris

I have been working on data from the recount3 project to integrate GTEx and TCGA data and perform DEG analysis using `DESeq2`. However, I am encountering an issue where I am getting too many significant genes while using datasets with large sample...on data from the recount3 project to integrate GTEx and TCGA data and perform DEG analysis using `DESeq2`. However, I am encountering an issue where …

RNA-seq DESeq2

updated 16 days ago • Reza

Hi, I have been trying to install DESeq2 v1.35.0 to replicate some data I generated some time ago, but I cannot find this subversion. BioCv15 has the v1.36, whereas

DESeq2

updated 18 days ago • Espresso

total fragments in treatment: 613205 # fragments after filtering in treatment: 544611 # maximum duplicate fragments in treatment = 1 # Redundant rate in treatment: 0.11 # total fragments in control: 565624 # fragments after...filtering in control: 489201 # maximum duplicate fragments in control = 1 # Redundant rate in control: 0.14 # d = 210 chr start end length abs_summit pileup -log10(pvalue

DiffBind macs2 chipseq

updated 18 days ago • yvonneh

that specialised tools for this exist e.g. MAGeCK, but am new to coding/R and am most familiar with DESeq2 for now), and it got me thinking about the ways in which we conduct differential analysis, and the differences between...them. I first modelled the count data as usual using DESeq2, after exporting in the data and study design (3 timepoints, gene of interest expression either high or low, 5…

DESeq2 StatisticalMethod Proteomics DifferentialExpression RNASeq

updated 18 days ago • james.zhang20

Completed Deseq2, still seeing a bimodal distribution in my RNA sequencing data after normalization on a histogram![enter image description...at my histogram beforehand). I completed several filtering and outlier step beforehand....however, deseq2 did let me know I have 30 outliers after DE. My PCA plot doesn't show any crazy batch effects. I did the VST transformation...here][2] I am not sure i…

DESeq2

updated 18 days ago • kcarey

I see that the model is more complicated than that. I read the vignette section "Theory behind DESeq2", even though I cannot claim that I understood the theory completely, I think I got the gist of it, maybe :) However, for instance...great if there was a way to get the count matrix that was used to calculate the log2FoldChanges in DESeq2, so that we could plot the heatmap with those values and s…

DESeq2

updated 19 days ago • HAK

Hello :) I have a RNA-seq dataset and a ChIP-Seq dataset and I have ran a differential binding analysis and differential expression analysis, both using DESEQ2. For the RNA-seq I have just followed a standard and the resulting tsv has the following columns: ......,log2Foldchange,lfcSE,pvalue,padj For the ChIP-Seq I have used diffbind to perform the deseq analysis, and extracted the d…

DiffBind ChIPSeqData DESeq2

updated 20 days ago • marcusn

Dataset of which I did mapping, and filtered out the genes, and then put it as an expression data in DESeq2, these are some problems I would like to address. 1. when I put in the dataset, I am not able to run it for DEG analysis because

DESeq2

updated 20 days ago • Dev

Hi everyone, I have an experiment designed as follows: 5 treatments (control included) at 3 timepoints in 3 cell lines in duplicates. I have a total of 90 samples and I am interested in knowing what happens to each cell line after each treatment over...experiment designed as follows: 5 treatments (control included) at 3 timepoints in 3 cell lines in duplicates. I have a total of 90 samples an…

DESeq2 ImpulseDE2 timecour timecoursedata moanin

updated 20 days ago • Aurora

Dear All, I run DESeq2 of liver transcriptomic. I prefiltered my dataset to contain at least 4 raw count and at least 3 biological replicates...like to analyze for DEG to compare the two group with 8 biological replicates. I run a standard DESeq2 analysis in R and found >6000 "NA" values in the Padj. When I checked the genes with "NA" padj, many of those actually have

DESeq2

updated 20 days ago • Agung

Hi, Below is my samples and conditions info: ```r Sample_ID Conditions 1 A 2 A 3 A 4 B 5 B 6 B 7 C 8 C 9 C ``` For A_vs_C, I followed: ```r res_A_vs_C= lfcShrink(dds…

DESeq2 contrasts

updated 21 days ago • bioinf

which is why we did this decontamination step in the first place. However, I am now trying to run deseq2 to find DEGs for each cell type. When I use the regular count matrices, I get TONS of photoreceptor gene contamination...se, design = design, ignoreRank) : some values in assay are not integers" I know that Deseq2 is supposed to use raw counts, but what if raw counts are biologically probl…

DESeq2 celda

updated 24 days ago • JalapenoCornbread

Hello everyone and sorry in advance for the long post, I need some advices ! We have been fighting with a heavy batch & method effect in a cohort of bulk RNAseq from patients. As you can see below on my PCA (generated using all genes), I have three groups of samples : green and blue for patient samples done at the same place with one technology, purple for patient samples done at an othe…

DESeq2 RUVSeq RUVseq BatchEffect DES

updated 25 days ago • Alexandre

any other statistical tool that can take in my 4 WT studies and 4 Mutant studies? Each study has a DESeq2 output generated. Thank you! [1]: /media/images/ec85505d-9c8d-49a5-b542-17f06d4d

DESeq2 PCAtools

updated 25 days ago • Aaliya

Hello, I am having a hard time interpreting the IHW and Shrinkage method results. I have read the paper, and also vignette and other various other question threads. I understand the purpose of the methods, however, not sure how to interpret their results. I have currently run a code: dds<- DESeqDataSetFromMatrix(countData = counts_DE_subset, …

DESeq2 RNAseq

updated 25 days ago • kcarey

Hello everyone, This is my first time performing DESeq2, and even PCA analysis. I have 8 samples. (4 WT and 4 mutant) I have done PCA Analysis, and this is my output. There is not much...Hello everyone, This is my first time performing DESeq2, and even PCA analysis. I have 8 samples. (4 WT and 4 mutant) I have done PCA Analysis, and this is my output. There is not much variance; what can I co…

DESeq2 RSTUDIO PCAtools

updated 26 days ago • Aaliya

I understand that LFC converges to zero when the variance is large and that the LFC calculation in DESeq2 is not just treatment/control. Although there are some strange count plots the sign of the LFC are wrong. I'll show you

DESeq2

updated 26 days ago • winwater0928

1 + time` corresponds to a exponential curve of the form `counts = a*exp(b*time)`, and that the DESeq2 approach to estimating disperisions should be suitable. Note that we are not trying to find the difference in decay

DESeq2

updated 26 days ago • i.sudbery

Hi, I'm trying to better grasp what is happening under the hood during dispersion estimation, and have a bit of a naive question. When using the makeExampleDESeqDataSet function, I can set the dispersions to zero by just specifying a 'null function', i.e.: ```r dds_pois <- makeExampleDESeqDataSet( n=5000, m=10, dispMeanRel = function(x) 0 ) ``` and indeed the dispersions her…

DESeq2

updated 28 days ago • WardDeb

Hi all, I have a question that don't know why, hope you can help. I use GSVA (Gene Set Variation Analysis) package to calculate pathway scores. Then I compare pathway scores between 3 groups using limma. When I use a few thousand pathways, raw p value of pathway A will different (bigger) with when I use only a few pathways. I think it should be the same because each pathway is independent (adj…

limma

updated 4 weeks ago • Chris

bioconductor version 3.18 BiocManager::version() # Verify version BiocManager::install("DESeq2") # install a bioconductor package ### Switch to the other of the 2 releases for the R version currently running: BiocManager

bioconductor Install

updated 4 weeks ago • BioinfGuru

limma) data <- read.csv("normalized_file_for_mesophyll_&_epidermis.csv", header = TRUE, row.names = 1) # Since the data is already normalized, there is no specific step for normalization # Extract Mf and Mr samples. Mf_samples

subsettingdata edgeR designmatrix

updated 4 weeks ago • prity6459

respectively using Minimap2, this gave me bam files, from this counted reads using R and then did DEseq2 analysis for DE. This worked really well for brain but has not work as well for lung as I get #N/A for many padj (this is a separate

DESeq2 LongRead DEXSeq IsoformSwitchAnalyzeR RNASeq

updated 4 weeks ago • 09191919

I am new to RNAseq and started to analyze my dataset using DESeq2. I first run the `DESeqDataSetFromMatrix` function and found the error message ``` Error in DESeqDataSetFromMatrix...I am new to RNAseq and started to analyze my dataset using DESeq2. I first run the `DESeqDataSetFromMatrix` function and found the error message ``` Error in DESeqDataSetFromMatrix(countData = HitCount, colData =…

DESeq2

updated 4 weeks ago • ussarizona

NULL, score=DBA_SCORE_READS) counts <- dba.peakset(myDBA, bRetrieve=TRUE) ``` Then, I use Deseq2 to analyze the differential peaks using default parameters and I get 124 peaks that is more open in control condition

DiffBind DESeq2 ATACSeq

updated 4 weeks ago • lonn

gave a single control group and a endometriosis group as expected: ![PCA_output_2][3] The DESeq2 output file was also different in these 2 analyses, even though the count data should be the same. Does anyone know what...need to keep the groups together in the input file? Thanks for your help. Code: ```library(DESeq2) library(ggplot2) library(tidyverse) counts_data <- re…

DESeq2

updated 4 weeks ago • quanah.hudson

Hello, I am using DEseq2 to analyze the relationship between gene expression and two continuous phenotypic predictor variables, one of...Hello, I am using DEseq2 to analyze the relationship between gene expression and two continuous phenotypic predictor variables, one of which

DESeq2

updated 4 weeks ago • Brynn

gene_symbol") blast_results <- read.delim("blastout_filtered.temp", header = FALSE, sep = "\t", row.names = NULL, col.names = col_names) # Convert dxr1.sorted to a data frame dxr1.sorted.df <- as.data.frame(dxr1.sorted

DEXSeq

updated 4 weeks ago • Clyde

Hi there! I'm trying to perform gene ontology analysis comparing tumor and normal samples. There are about 250 and 350 differentially enriched peaks in the tumor and normal samples respectively. However, there are `0 enriched terms found` when I performed the `enrichGO()` function on the tumor and normal gene lists containing the respective entrez ID of the differentially enriched genes. …

ChIPseeker

updated 4 weeks ago • Henry

design: `~Time.Point*Cell.line*Drug`. My question is, according with the interactions section of `DESeq2 vignette` & example 3 from `results` function, to get the **comparison between 1 and 10 days in Time Point**, at the **baseline

DESeq2

updated 5 weeks ago • andrebolerbarros

Hi I am currently analyzing RNASeq data, having used HISAT2 for mapping and StringTie for quantification. I've proceeded to use DESeq2 for differential expression analysis, but I've encountered an issue where many of the differentially expressed genes...RNASeq data, having used HISAT2 for mapping and StringTie for quantification. I've proceeded to use DESeq2 for differential expression analys…

DESeq2

updated 5 weeks ago • Rajat

Hello, I have data results of DESeq2, 3 samples per condition (2 conditions) When I make ```r boxplot(assay(rlog(dds)), outline = TRUE, col = "lightblue", xlab = "Samples...Hello, I have data results of DESeq2, 3 samples per condition (2 conditions) When I make ```r boxplot(assay(rlog(dds)), outline = TRUE, col = "lightblue", xlab = "Samples", ylab

DESeq2

updated 5 weeks ago • Sahar

Hi, From a Deseq2 analysis, I have just the final table of results (I guess res(dds)). My first question is if the counts there are normalized

Des DESeq2

updated 5 weeks ago • Sahar

end data from human samples on the whole genome. I ran bismark for alignement, then removed the PCR duplicates using deduplicate_bismark, and finally extracted the methylation (deduplicate_bismark): ``` bismark \ $genome \ --non_directional...lt;- targets$sampleID descriptiondf = data.frame( Condition = factor(targets$condition), row.names = sample.ids, stringsAsFactors = FA…

HDF5Array BiocGenerics BiocParallel Biobase

updated 5 weeks ago • jacques.imbert

Hello, I have three groups: "ETOlow" "ETOhigh" and "UT (untreated samples)". I have successfully compared ETOlow vs UT and ETOhigh vs UT but my PI wants an analysis between UT<ETOlow<ETOhigh in order to remove any possibility of a concentration dependence in my results. How, would I do this? Would I just compare ETOlow to ETOhigh as shown below? Will this automatically take into account UT …

DESeq2 rnaseqGene

updated 5 weeks ago • Walter

Hi, I am using SGSeq and have a problem with the analyzefeatures function. Below, I have provided my code and my problems. Could you please kindly guide me? ```r library(SGSeq) library(TxDb.Hsapiens.UCSC.hg38.knownGene) library(GenomicRanges) # Define the path to your BAM files bam_path <- "the path of my bam files" (ps: I have 41 bam files) # List the BAM files in the directory b…

SGSeq

updated 5 weeks ago • Sara

On running the following DESeq2 code, R crashes with the shown error message. I have tried creating the DESeqDataSet object in multiple ways and it...On running the following DESeq2 code, R crashes with the shown error message. I have tried creating the DESeqDataSet object in multiple ways and it always...that require dispersion estimates lead to R crashing and quitting. ```r library("airway") l…

DESeq2

updated 5 weeks ago • Shefali

Hi there, I understand that DESeq2 uses GLM to regress over the raw gene count matrix. And I just wonder for the inner part of the linear regression, is it...of y = a1X1 + a2X2, I know I can retrieve the fitted coefficients by calling the function 'coef' in DESeq2 package, which corresponds to a1 and a2. But I don't know a. where to get the model design matrix, I mean what is the phenotype

DESeq2

updated 5 weeks ago • Weiqian

and also sometimes have a difficult time extracting the right comparisions using `results` from `DESeq2`, so instead I like to do what was suggested by the [DESeq2 vignette][1] to use a grouping variable (called `type` in my case), which...means my design looks very simple `~ 0+type`. After running DESeq2 (by calling `DESeq()`), I want to answer the following question: Does the condition (A or …

DESeq2 DifferentialExpression

updated 5 weeks ago • nhaus

Hi! How can I use DESeq2 to analyze my RIP-seq data, which includes both INPUT and IgG control samples for each of the three replicates across

DESeq2 RIP-seq

updated 5 weeks ago • Adelaide

Hi! I am not sure if I misunderstand how GSEA works or I have an error in my GSEA analysis. I am using clusterProfiler (gseKEGG function). Input data: - output from DESeq2 ("control vs mutant" and "mutant vs control" --> I just set the contrast in both directions. it was the same input in DESeq2) - ranking of genes based on log2foldchange (sign of log2FC is of course inverse for "control…

clusterProfiler gseKEGG

updated 6 weeks ago • andromeda

Hi as I understand it, in DESeq2 one of the ways to run a DEG analysis on time course data is using a likelihood ration test on two different models. For

DESeq2 timecourse DifferentialExpression

updated 6 weeks ago • joshua.mannheimer

batch effects, it could output negative counts, which is not ideal in my case. I'd like to utilize DESeq2 result as much as possible, and I'm wondering if I am doing it in a correct way. After fitting model as below: ```r dds <- DESeqDataSetFromMatrix

DESeq2

updated 6 weeks ago • kys91240