Bioconductor Forum

I am reanalyzing some CRISPR-Cas9 screening data to look for sgRNAs effective across cell lines. countData: ![enter image description here][1] colData: ![enter image description here][2] Condition here corresponds to time (initial vs. final). I can set up the DESeqData like this, where the fold-change result is from the effect of time: `DESeq2::DESeqDataSetFromMatrix(countData = counts…

DESeq2

updated 4.8 years ago • P1000

tring to use the TCGA HTseq\_counts data to do some annlysis. I plan to follow the process below. First. Use the RNA\_seq dataset which containing tumor and normal tissue to find differently expressed genes by DESeq2::DESeq...Second, because i only want to normalize the tumor data, so i use DESeq2::rolg to transform the data only containing tumor data. Third, I will use the rolg transformed tu…

deseq2 rna-seq

updated 7.5 years ago • 137737756

Is it possible to run DESeq2 with gene-dependent binary variable such as membership in a pathway or transcription factor association? If not, in

deseq2

updated 8.1 years ago • yuri.pritykin

the treatment: control vs CL. Following the manual, there are two ways to do this.   The first method would be to perform an analysis where you contrast both treatments with the results function: <pre> # First perform...genotype:time) dds_withTHREEWAYint_forgroupanalysis <- dds_withTHREEWAYint # Combine the factors of interest into a single factor with all combinatio…

deseq2

updated 7.9 years ago • Jonas B.

we've been using DESeq for some of the analysis that we usually perform and now we'd like to jump to DESeq2. We've been checking the DESeq2 manual but it is not clear to us how to switch from one version to the other. Could you please...sep = "\\t",eol = "\\n")   Our main questions are: 1. How could we use as input file for DESeq2 a full table that contains row counts for the differ…

Deseq2 Deseq

updated 10.6 years ago • Osvaldo

The documentation of estimateDispersions in DESeq2 says > estimateDispersions checks for the case of an analysis with as many samples as the number of coefficients...it appears that the results of estimateDispersions are different depending on the design of the DESeq2 object it receives as input. As an example for that, the mean of the dispersions resulting from different designs is…

deseq2

updated 6.2 years ago • Sam

Hi,    My DESeq2 running was stucked for one night, it is normal?  My dataset contains 635 human samples, this is abnormally large...Hi,    My DESeq2 running was stucked for one night, it is normal?  My dataset contains 635 human samples, this is abnormally large: `` head(ddsTxi) `` class: DESeqDataSet dim: 6 635 metadata(1): versi…

deseq2 rnaseq

updated 7.2 years ago • Raymond

I am trying to use the DESeq2 package to analyze RNASeq dataset in a very complex design and am having trouble wrapping my head around. I have a 4...factor experiment generated from phosphoTRAP protocol: - age (with 4 levels): 1, 2, 3, 4 - sex (with 2 levels): F, M - stimulus (with 2 levels...Ctrl, Exp - fraction (with 2 levels): total, IP We expect each factor and their interactions to …

DESeq2 RNA-Seq Multifactorial Design GLM Contrasts

updated 6.1 years ago • ananda2

file you used in your guide "Analyzing RNA-seq Data with the DESeq Package" from 2012. At first I had two tables: one per replicate containing FPKMs for the three conditions analyzed. I then merged the FPKMs of both...FPKM FPKM FPKM ... I understand that DESeq must first normalize the expression values of each treatment by dividing each column with it's own size …

DESeq DESeq

updated 13.3 years ago • Andres Eduardo Rodriguez Cubillos

We are using DESeq2 to analysis some Ribo-seq data pointwise and try to replicate the dispersion estimation procedure. That is, we focus...count in gene. Thus there is a large proportion of small counts. We have problem to replicate the Deseq2 methods in our data. Could you help us with them? First, following Anders and Huber (2010), we had lots of negative raw dispersions...at small relative…

DESeq2 Ribo-Seq

updated 6.2 years ago • li.keren.cn

Is there a way to obtain the relative importance of a variable in the design formula of the DESeq2 model? For example, if I have a variable for age in my design formula and I want to know the percentage of variance accounted...by age. I know you can run a likelihood ratio test with a reduced model that does not include the factor to see if it is significant or not. But is there something similar …

DESeq2 RNASeq

updated 4.6 years ago • AT

Hello, I want to perform differential expression analysis with DESEQ2 of my miRNA seq data. I want to include age, sex, height, gender, and the batch in the design matrix as a covariate. In our data...and must be removed. Please read the vignette section 'Model matrix not full rank': vignette('DESeq2')***** 1. My data has a total of 365 samples and 645 miRNA 2. I am adding each covar…

deseq2 miRNASeq designmatrix Batch

updated 5.8 years ago • anshulmbi

very strange. I have no idea what my bug might be. My R script is launched/submitted using ``` docker exec -d -u studio R CMD $RSCRIPT ``` This is a partial snipit from the script ```r library("DESeq2") # version 1.32.0 library("BiocParallel") countMatrixDF <- read.table(countMatrixFile, sep=delimator, header=TRUE) # convert...exec -d -u studio R CMD $RSCRIPT ``` …

DESeq2 dese

updated 3.9 years ago • aedavids

The reference for DESeq2's estimateDispersions() says that it uses Cox-Reid likelihood that was originally implemented in edgeR in 2010. I take...an offset, whereas CR can't. For that reason, counts have to be normalized prior to applying CR. In DESeq2 normalized counts are obtained by dividing the raw counts by the corresponding normalization factors: <span style...Small sample estimation o…

deseq deseq2 edgeR normalization

updated 10.1 years ago • Nik Tuzov

The DESeq2 vignette states that both the variance stabilizing transformation and regularized log transformation "produce...on the log2 scale which has been normalized with respect to library size *or other normalization factors*". If I am not providing any normalization factors (like in my code below), the gene counts are normalized with respect...I'm sure that's the case, but wanted to double ch…

DESeq2

updated 4.5 years ago • Nikolay Ivanov

I have gene expression data from some symbiont critters in response to temperature stress, where we replicated temperature treatments across two types of experiments (specifically, in culture and in symbiosis). These separate experiments were both sequenced using TagSeq, but were sequenced at different facilities at different times. The result of both the distinct experiments and using different …

DESeq2

updated 4.4 years ago • Hannah

I am doing differential expression using DESeq2. I have 2 conditions (Veh_0h, treatment_56h) and 5 samples each. After generating the gene count matrix from StringTie...I am doing differential expression using DESeq2. I have 2 conditions (Veh_0h, treatment_56h) and 5 samples each. After generating the gene count matrix from StringTie output files and loading into R as `countData`, I used the fo…

deseq2

updated 5.5 years ago • nattzy94

the negative control -- treated. Which is a better approach: - calculating the normalization factors using all 9 libraries, or - calculating the normalization factors using only the 2×3 libraries that are compared at...a time (and load in three count tables, entirely separately)? Example for first option: <pre> groups <- factor(c("A", "A", "B", "C", "C", "A", "B", "B", "C")…

edgeR calcNormFactors RNA-seq

updated 11.1 years ago • Peter

Hi, I've two factors in my experiment design : `group` (Normal, Low, Middle, High) and `localization` (in, out). We would like to perform DE analysis...to extract DE genes based on localization (in or out). My first idea was to use `~ group + localization` as model and then `results(dds,contrast=c("localization","out","in"))` to extract the DE genes

deseq2

updated 5.8 years ago • Nicolas Rosewick

In the documentation or the rlog() function we can find that _rlog(K\_ij) = log2(q\_ij) = beta\_i0 + beta\_ij_, Which means the function would return the log2 transformed data after normalization by a size factor, estimating dispersion, shrinking dispersion and then the the beta parameters. Following the description of the paper..._ij_, Which means the function would return the log2 transform…

deseq2 rlog rlog transformation

updated 9.8 years ago • lanhuong

Hello all, [My first post to this forum, as requested.] I cannot perform data.table revdep checks because DESeq2 was unavailable in Bioc-devel...bioconductor.org/checkResults/devel/bioc-LATEST/lpsymphony/malbec2-buildsrc.html In the meantime, DESeq2 has removed the IHW Suggests dependency so that DESeq2 will propagate. Michael Love asked me to post this here and tag

lpsymphony IHW

updated 6.1 years ago • mattjdowle

Hi, I am using `DESeq2` for analyzing Illumina `RNASeq` datasets. I follow the below steps; 1. Derived raw counts (from featureCounts) > Imported...counts to DESeq2 2. Normalised the counts via an estimation of size factors `(counts(dds, normalized = TRUE))` 3. Transformed the data for downstream

RNASeq DESeq2 vst rlog Normalization

updated 4.0 years ago • mohammedtoufiq91

I'm trying some first-pass exploratory analyses of a DESeq2 dataset using vidger. Naturally, I get an error with my very first graph. I created...type = "deseq") ``` This is just as described in the vidger vignette. It works with the DESeq2 pasilla dataset example, but not for my own data, which gives an error: ``` Error in names(ls.mean) <- sapply(nam, paste) : 'names

vidger

updated 5.5 years ago • bbj23

Ind_4 (I had to add numbers in front of the treatments because otherwise deseq would only test the first two groups against After_infection, but I was also interested in the results from Peak vs Uninfected.) dds <- DESeqDataSetFromMatrix...output from the test with the exact same groups is different. I.e. if I change the name of the first two conditions to: "2_Uninfected" and "1_Peak_inf…

DESeq DESeq

updated 12.6 years ago • Elin Videvall

I am using DESeq2 with single-cell data. Previously, I used the "Wald" test with default settings but I wanted to check how my previous analysis...I am using DESeq2 with single-cell data. Previously, I used the "Wald" test with default settings but I wanted to check how my previous analysis would look using the recommend single-cell settings from the vignette (basically using the "LRT" tes…

deseq2

updated 6.9 years ago • casikecola

Hi all, I got a problem running DESeq2. I was running scripts from http://www.bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.html...Hi all, I got a problem running DESeq2. I was running scripts from http://www.bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#differential-expression-analysis (by Michael I. Love, Simon Anders, and Wolfgang Huber)…

DESeq2 Errors

updated 6.8 years ago • joy@wh

to see the DE genes between treated and untreated considering the gender. There might be other factors that add noise to data such as the time of collection, age etc.  So far what I have done is the following. Is it the correct

deseq2 edgeR rna-seq

updated 10.5 years ago • gthm

Hi, I'm using DESeq2 to identify differentially affected histone modifications in cells from control and treated human populations...two ways, the only difference being how the data were initially mapped to the genome.   In the first instance there was no threshold for sequences mapping to multiple sites; anything that could be mapped was kept (and...but the background is a little highe…

deseq2

updated 11.0 years ago • David Auble

I am posting in regards to an error I've experience when running Deseq2's estimateSizeFactors. The specific error is posted below:  <pre> > dds = DESeqDataSetFromMatrix(countData=filteredDGE...every gene contains at least one zero, cannot compute log geometric means</pre> I've run Deseq2 several times in the past but have never experienced this error. I have trie…

deseq2 estimatesizefactors

updated 10.0 years ago • ssabri

I used DESeq2 with the default settings, and of the roughly 30,000 genes, 16 of them yielded NA values for both the p-values and adjusted...p-values. I assume this occurred as a result of DESeq2 detecting an outlier in these genes - is that correct? However, I am using 44 samples in the case group and 59 in the control...groups, so my understanding is DESeq2 should have automatically replaced the…

Bioconductor

updated 12 weeks ago • Gabriel

Syed" <mosvey@gmail.com> wrote: > Thanks Michael, > I have more questions regarding my Deseq2 analysis. If I have three > conditions, ( Transcriptome at three different stages during development), > Which > way...genes at three > developmental time points?. > And further if I am interested in transcription factors only: > 1. Is it bet…

Transcription DESeq DESeq2 Transcription DESeq DESeq2

updated 11.7 years ago • Michael Love

levels for the samples and differentially expressed genes between tissues. For both I intend to use DESeq2. From my reading and testing, I believe that the samples have two undesirable characteristics:   o  the replicates...dispersion calculations.   o  the sample data have a wide range of coverage: when I run DESeq2 on all   &nb…

deseq2

updated 8.1 years ago • bge

<div class="preformatted"> I want to know how to deal with data without replicates using DESeq2,can you tell me how to deal with it.You can see my codes below,but it have errors when deal with sample without replicates. -- output of sessionInfo(): library('DESeq2') readcount<-read.delim("readcount.xls",row.names=1) readcount<-round(readcount) readcount&a…

updated 12.1 years ago • Guest User

div class="preformatted">Hi, I am trying to run DESeq2 analysis on sample design like this: sample replicate treatment A 1 no A 2 no A 1 yes A 2 yes B 1 no B 2 no B 1 yes B 2 yes (repeated...DESeqDataSetFromMatrix(readcount, sampleinfo, ~treatment+sample:replicat…

DESeq2 DESeq2

updated 11.4 years ago • BJ Chen

are: 1) Is it appropriate to use the DESeq function on raw agglomerated counts? 2) Should size factors be estimated only at the OTU level, and then should these same size factors be applied to the agglomerated datasets...Or should size factors be estimated at each level separately? 3) Another question unrelated to agglomeration: I have a very sparse OTU table...248, 248, 248)"> <…

phyloseq deseq2 estimatesizefactors

updated 10.1 years ago • brandilyn.peters

have a counts matrix of K9me2 enrichment at each gene. I would like to use this counts matrix in DESeq2 for differential enrichment analysis, as if treating it as RNA-seq in essence. However one issue I have is that for Cut...amp;Run and for analysis of global changes in enrichment, I first normalize the data to the number of mapped reads generated from S.cerevisiae spike-in, within each sample.…

deseq2 Cut&Run

updated 7.1 years ago • MPerch

I'm running a deferential expression pipeline that first calculates DE with DEseq2 and then looks for enticement in the DE genes. This pipeline seems somewhat common in...I'm running a deferential expression pipeline that first calculates DE with DEseq2 and then looks for enticement in the DE genes. This pipeline seems somewhat common in the literature, so I'm sure it's fine. W…

deseq2 goseq gene ontology differential gene expression

updated 8.4 years ago • david.rinker

pre> ctrl1 trtB1 trtA1 ctrl2 trtB2 trtA2 ctrl3 trtB3 trtA3</pre> Treatment factors: <pre> Treat <- factor(substring(colnames(data.set),1,4)) Treat <- relevel(Treat, ref="ctrl") Batch <- factor(substring(colnames...ctrl, since ctrl was set as ref with relevel()? The reason I am a bit unsure is because this is the first time that I am using …

edger limma design matrix

updated 9.9 years ago • Ekarl2

to make sense of RNA Seq and the stats behind it. I am looking to use the transformed counts from DESeq2 as input to WGCNA. Since we are using a design when we create the DESeqDataSetFromMatrix before we get the counts (and...depending on the factor/ combination of factors we use the counts slightly change), I was wondering if this would affect how WGCNA will correlate

WGCNA DESeq2

updated 5.0 years ago • Peny

higher (additional variation in the counts) in some persons as compared to the other. I have used DEseq2 package: first without using batch factor and then with batch factor, I have more differentially expressed genes including...batch factor. So, do you think I should build my model including the batch factor (different donors) to the design to increase the sensitivity

deseq2

updated 5.4 years ago • laurent.manchon

appears when reviewing the results of the contrast. DESEq2 returns 1113 sequences as significant DE (padj < 0.05). But in some cases, when I go to the counts tables (both the one from...DESeq2 and the ones I get originally) and check the normalized counts of X sequence of interest, I don't see the fold change that...DESeq2 tells me. For example: **Result:** seq baseMean log2FoldChange l…

SmallRNA DESeq2

updated 3.4 years ago • jucosie

Hello, Crossposted https://www.biostars.org/p/9492478/ I am trying to do a differential ATACseq analysis with DiffBind3, and need to build a design that DESeq2 will accept. I have tried several relevant models, but I have been unsuccessful in achieving the contrasts I desire, without DESeq2 throwing a "Model matrix not full rank" error. Any help with generating a correct linear model wou…

timecourse DiffBind DESeq2

updated 4.2 years ago • Kavi

Hi, I'm looking for help with a complex experiment in DESeq2. I've already read the vignette and help functions, but I'm still not sure if these data can actually be analyzed properly...sample types, plus variation in library size within each sequencing type (table below). I know that DESeq2 can handle random variation in library sizes, but does this apply when there's an experiment-wide conf…

deseq2

updated 4.8 years ago • cja

Dear Prof Smyth, in design <- model.matrix(~ a + b + a:b , data=targets) my interest is in factor a (coef=2). ""Do you expect the effect of experimental factor b to be same for each level of a? If yes, then maybe you don't need...sure, but I guess the answer is no. The experiment consists of embryos collected at two time points (factor a), normal or cloned embryos (factor b). And on …

edgeR edgeR

updated 14.6 years ago • Biase, Fernando

and columns "Subtypes" and  "Type". Column "Type" is with Disease and Normal. <pre> library(DESeq2) dds <- DESeqDataSetFromMatrix(countData = U2, colData = coldata, design = ~ Type) dds class: DESeqDataSet dim: 15754 44 metadata...lt;- rowSums(counts(dds)) >= 10 dds <- dds[keep,] nrow(dds) [1] 11755 dds$Type <- factor(dds$Type, levels …

deseq2 rnaseq differential gene expression edger

updated 7.6 years ago • Biologist

Hello.  Is it possible to analyze a continuous phenotype with DESeq2, without grouping into factors?  I receive this note when I run the default DESeq function: <pre> -- note: fitType='parametric

DESeq2 continuous

updated 9.5 years ago • pjgalli2

on a number of samples. I would like to compare to some of these in separate analyses using DESeq2, and the following design of the colData works fine for me: <pre> > sample <- factor(c("pos", "neg", "pos", "neg", NA, NA, NA, NA),   &nbsp...analysis. However, if I perform the same analysis with the following colData <pre> > sample <- fac…

deseq2 coldata NA

updated 7.4 years ago • t.kuilman

I'm using Deseq2 for differential gene expression analysis and then for downstream analysis i'm going to classify healthy vs disease...I'm using Deseq2 for differential gene expression analysis and then for downstream analysis i'm going to classify healthy vs disease states using support vector machine. The data comprises of healthy and disease states which sequenced in 13 batches. I hav…

deseq2 batch effect classification

updated 7.2 years ago • Maryam

C, D) and 3 conditions: treated, control, and untreated. Each sample is in triplicate. I performed DESeq2 analysis using two different methods: Method1 Day 3 analysis ```r design = ~ -1 + Condition) Method 2 design = ~ -1 + Condition + Cellline...Day3$group <- factor(paste0(Day3$Cellline, Day3$Condition)) design(Day3) <- ~-1 + group These two methods yield different nu…

DESeq2

updated 16 months ago • rajan

the same, I have quantified my samples using **salmon** and am using tximport as an offset before DESeq2. I wanted to know whether passing **scaledTPM** values is recommended to **DESeqDataSetFromTximport**? I am attaching my...salmon", txOut=TRUE, countsFromAbundance="scaledTPM") sampleTable <- data.frame(condition = factor(samples$condition)) rownames(sampleTable) <- colname…

DESeq2 tximport

updated 2.6 years ago • prangannathofficial

Hello everyone, From the vignette of DESeq2, I can either set the factor level by doing this code dds= relevel(dds$condition, ref=“untreated”) Or I can use the contrast

deseq2 RNAseq

updated 6.4 years ago • Merlin

mean mu\_ij is specified as _mu\_ij = s\_ij \* q\_ij_  with _s\_ij _=_ s\_j_ = a normalization factor and _q\_ij_ = a quantity that is proportional to the concentration of the cDNA fragments of gene i in the sample j.&nbsp...what point do I account for different library sizes? 3) Some lines above the paper states that the DESeq2 design matrix does not have full rank, but that a uni…

deseq2 design matrix

updated 7.0 years ago • nikosbosse

Hi, I'm currently exploring the functions in DESeq2 and try to replicate some findings of DOI: 10.1126/science.aan3456. In this paper, they test several models to identify...of species: human, chimpanzee, macaque) To identify clusters of genes where H > C > M, they first test Model H vs reduced model 0. This also works fine in my code, as I can easily drop the complete factor …

deseq2 LRT

updated 5.8 years ago • bio_inc

as explained in the workflow [RNASeqEdgeRQL][1]). However, I'd like to perform my anaylsis with DESEQ2 as well . Basically, edgeR seems to perform pairwise analysis between couples of samples, for example, given the following...y group <- paste(targets$Variable1, targets$Variable2, sep=".") group <- factor(group) design <- model.matrix(~0+group) …

edgeR DEG RNASeq DESEQ2

updated 3.9 years ago • Raito92

MOGSP", "MOGSP", "MOGSP", "MOGSP"), row.names = colnames(countData) ) colData #DESeq2 dds <- DESeqDataSetFromMatrix(countData=countData, colData=colData, design= ~ treatment + cell) rld <- rlog(dds, blind...low counts keepCounts <- rowSu…

deseq2 design

updated 5.3 years ago • mhnidhi2-c

Dear all,   In my experimental design, I have 20 libraries, coming from 20 F2 interspecific hybrids, meaning every genotype is different. 10 individuals are tolerant and the other 10 are sensitive to a specific type of stress. I’m interested in what genes are differentially expressed in these two group of plants (tolerant vs sensitive). Because of the unique genotype in each individu…

deseq2 estimatedispersions

updated 8.6 years ago • nicky.driedonks

Dear DESeq2 support: I wish to use lfcShrink after doing a contrast with a 2X2 factor experiment. I grouped the variables based on...to know the effect of "fertilizer": ``` dds <- makeExampleDESeqDataSet() dds$fertilizer <- factor(rep(c("fertilized", "unfertilized"),each=1)) colData(dds)$group <- factor(paste0(colData(dds)$condition, "_", colData(dds)$fertilizer

deseq2

updated 7.0 years ago • gcagle1

I am a new learner of DESEQ2 and have seen similar posts on this forum but could not find clear answers. What would be the best way to create heatmaps...specifically with 2 log fold change(base 2) in DESEQ2 or R in general? In DESEQ2, heatmaps are created based on VST (Variance Stabilizing Transformation) values. The count...FeatureCounts. I would like to create heatmap specifically using …

DESeq2

updated 2.4 years ago • bio2249

Hi, I'm running differential transcript and exon usage analyses using DEXSeq and have a quick question about when I should subset the data. For the purposes of my experiment, we have multiple nested groups of contrasts that we are interested in. Unlike DESeq2 we can't just fit a more complex model, do multiple group comparisons and pull out individual contrasts and have to **subset...of my exp…

DEXSeq

updated 2.8 years ago • Ben J

tests I have to run. So I deleted 2290 features and plugged the resulting 784 x 12 matrix into DESeq2. The result was that no features had significantly different sequence counts in the two sample groups. Out of curiosity...a second matrix from which I only deleted 1990 features leaving an 1084 x 12 matrix. In this matrix, DESeq2 identified a couple of features with significantly different sequen…

deseq2

updated 9.5 years ago • szoboszlay.m