Bioconductor Forum

of genes in this cell line. Fastq files for all these 8 experiments were processed using Hisat2 and featureCounts to get gene counts. Replicates from each exp vary from 1 to 3. To complicate matters, half the exp were performed

RNASeq BatchEffect DESeq2

updated 3.6 years ago • Alexandre

input_format = "FASTQ", output_format="BAM", nthreads=8, output_file = all.BAM) featuresC <- featureCounts(all.BAM, annot.inbuilt="mm10") ``` <pre> //================================= Running ==================================\\ || || || Load annotation file mm10_RefSeq_exon.txt ... …

rsubread featureCounts

updated 6.7 years ago • diego.carvalhoalvarez

each paired (so ~200 sets of count files). I aligned my fastq files with STAR, counted genes with featureCounts, and am using DESeq2 for differential expression analysis. My design is ~sex + sex:nested + sex:condition, where

deseq2 outliers differential gene expression

updated 9.0 years ago • gregory.l.stone

50 human samples. The gencode gtf file was used to map the reads. STAR was used to map and featureCounts was used to generate count data. So, the rownames in my files are ensenbl gene_ids which looks like: `"ENSG00000231251.1

edgeR ENEMBL RefSeq

updated 6.8 years ago • mzillur

Hi everybody, I have just started using featuercounts and am new to this. Would you please help me with the folowing: >fls <- dir("/path/to/bam/files/", "bam$") > fls [1] "X_A.bam" > props <- propmapped(files=fls) Error in normalizePath(files, mustWork = T) : path[1]="ENCFF064QSN.bam": No such file or directory I can see that bam files are…

path Rsubread

updated 6.9 years ago • memoly101

I am interested in counting the number of reads that span splice junctions. Therefore, I set the options GTF.featureType = "transcript", useMetaFeatures = FALSE, and juncCounts = TRUE. However, the resulting counts matrix has row names like ENSG00000223972.5\_1 and many of them are duplicated. What combination of parameters should be used to make the row names be transcript identifiers? Also, the…

rsubread featureCounts

updated 9.2 years ago • Dario Strbenac

bam_file <- "path/aligned_reads.bam" gtf_file <- "path/to/annotation.gtf" counts <- featureCounts(files = bam_file, annot.ext = gtf_file, isPairedEnd = TRUE)" what could be wrong???? GTF file is absolutely fine i did

Rsubread BAMfiles GTFfile

updated 24 months ago • mirjanakessler

paired-end data that we mapped to respective genomes with STAR, and then obtained read counts with featureCounts, using the most recent GTF gene annotations for the 3 species. I then obtained the lists of orthologue genes

deseq2 normalization

updated 7.7 years ago • akozlenkov

cell types. This modification is very broad and not amenable to peak analysis. Therefore I have used featurecounts to count up reads falling in gene-bodies for each gene and sample, and now have a counts matrix of K9me2 enrichment

deseq2 Cut&Run

updated 7.1 years ago • MPerch

this https://f1000research.com/articles/5-1438/v2 they combined all BAM files and then ran \`fc <- featureCounts(all.bam, annot.inbuilt="mm10")\` Is it possible to combine all the counts from each BAM file and create an compatible

edger htseqcounts

updated 8.4 years ago • mictadlo

Hi,  I was wondering which counts are appropriate to use for plotting the expression of the differential transcripts? `` plotDEXSeq `` is giving me this error, even when using the pre-constructed matrix of counts from the workflow "__Swimming downstream: statistical analysis of differential transcript usage following Salmon quantification__": plotDEXSeq( dxr2, "ENSG0…

DEXSeq StageR rnaseqDTU

updated 7.2 years ago • rbenel

count against exon/gene/feature models: alignedToRPKM <- function(readcounts) { # the output of featureCounts() millionsMapped <- colSums(readcounts$counts)/1000000 if('ExonLength' %in% names(readcounts$annotation)) { geneLengthsInKB...with Bowtie/TopHat/CuffLinks I got about the same results but slower, so I stuck with Rsubread. And featureCounts() is really handy.) So, …

Normalization GO graph Rsubread Normalization GO graph Rsubread

updated 13.7 years ago • Tim Triche

Dear List, Our sequencing core recently switched from STAR to Kallisto. The genewise output was given as both TPM values and counts. Gordon Smyth has written that TPMs should not be used as input to EdgeR. In a recent paper (F1000 Research 2016,4:1521) Soneson, Love, and Robinson have presented evidence that the method they call simplesum_avextl for deriving reads-per-gene, from numbers-of-tr…

RNASeq-quantification edgeR TPM

updated 6.9 years ago • raf4

Call peaks using MACS2 2) Count the number of reads for each peak in each sample separately using featureCounts (Rsubread package). The output matrix is as follow.            sample1 peak\_1    100

deseq2 atac-seq

updated 8.2 years ago • zhongjixx

each gene. I am trying to do this using summarizeOverlaps (as I'm using R and I don't have a mac for featurecounts) and I have looked at the example on bioconductor as follows: (ebg <- exonsBy(txdb, by="gene")) se <- summarizeOverlaps

summarizeoverlaps bacteria e coli unique reads

updated 9.9 years ago • as9309

All,  I processed and analyzed RNAseq data before. It was pretty straight forward with Star, featureCounts and edgeR. I received a new dataset of  36 samples with SE sequence file. I expected 36 files with ~30 million

rnaseq edger technical replicates

updated 8.6 years ago • alakatos

nbsp; I have raw counts data from featureCounts. I actually wanted to do survival analysis. For a specific gene I want to classify the samples into Low and High

deseq2 r fpkm() geneexpression

updated 7.3 years ago • Beginner

Hello, I have counts from Salmon that I have imported using Tximport for WT and KO samples. I want to use ERCC spike-in data for normalizing these counts. To do this, my strategy involves estimating size factors using ***only*** the **spike-in data** (function: Deseq2::estimateSizefactors) and using those normalize my counts (*Mus musculus* transcripts). What I have done so far: step1: I …

deseq2 Tximport Sizefactors normalizationfactors spike-in

updated 5.6 years ago • hina.abbas.bandukwala

specific expression events with mouse RNA-Seq dataset. I use featurecount to count the reads mapped to maternal/paternal allele and also those which map equally to both (i.e. Reads that

edger

updated 10.7 years ago • Vivek.b

Dear all, I'm recalculating the RPKM value of a RNASeq data on Rsubread through featureCounts function, and I'd like to know if should I use just the "assigned" reads or the total reads, including "unassigned

rnaseq R rsubread rpkm

updated 11.2 years ago • gustavoborin01

obtained my list of DE transcripts. The functions I used to align .BAM files to features are featureCounts and summarizeOverlaps respectively, the latter resulting in higher expression levels for different transcripts...and with the following parameters: For edgeR fc <- featureCounts(all.bam, annot.ext="pathofmygff3", isGTFAnnotationFile=TRUE, nthreads=16, GTF.featureType="tra…

edger deseq2 rnaseq de

updated 5.8 years ago • Raito92

Hi, I have paired rnaseq data from multiple samples, counted with `` featureCounts ``, now planning to use DESeq2 and trying to design it. I have gone through https://support.bioconductor.org

deseq2 rnaseq featurecounts DESeqDataSetFromMatrix

updated 8.1 years ago • bioinf

of mapping reads to a preliminary genome sequence of the symbiont, summarizing the reads with featureCounts, and doing DE with DEseq2. I've followed the basic protocol that I've seen outline in various vignettes. I've found

deseq2 differential expression normalization

updated 8.4 years ago • RMRG

d liek to compare, my differential expression list will look quite a lot different. e.g. I only use featureCounts on those .bam files that correspond to WT/A for region 1 and 2, so I can easily contrast WT/A/1 vs. WT/A/2. Just the result

deseq2 rna-seq

updated 8.5 years ago • martin.weihrauch

Hello   I am trying to understand how to run a differential expression using R and for that I am referring to Smyth and other's \["limma: linear models for microarray and RNA-seq data user guide"\]\[1\] (2016). This vignette refers to data sets provided by \[WEHI bioinfo\]\[2\]. The latter provides the link to a dataset made of four libraries (A\_1, A\_2, B\_1 and B\_2), a chromosome r…

limma rnaseq edger

updated 8.3 years ago • marongiu.luigi

I am analyzing an experiment on the mouse olfactory epithelium. We have 3 treatment conditions and 1 control condition. Each condition contains 4 biological replicates. Our 3 treatment conditions each express a different isoform of transgenically up-regulated Adar protein. Adar is hypothesized as a negative regulator of circular RNAs (circRNAs). It's hypothesized mechanism of negative regulation …

deseq2 circRNA rna-editing

updated 6.2 years ago • maxhenryhills

and have been following the Galaxy pipleine for my RNA seq data. At this stage, I have featureCounts count tables. In one one of the DEG experiments, I have to compare WT baseline data (2 males + 2 females) vs WT at 1h

DESeq2 RNASeq Galaxy

updated 3.9 years ago • István

5, indels=5, nthreads=6) Here is the command used to generate count tables: featureCounts(inputfiles, annot.ext=gtf, isGTFAnnotationFile=T, useMetaFeatures=T, isPairedEnd=ispaired, allowMultiOverlap

rsubread alignment reproducibility

updated 9.3 years ago • Isaac Virshup

RNAseq analysis. Briefly, I mapped the RNA-seq reads to the reference genome using STAR and I used featureCounts to quantify the reads mapped to the reference genes and found the gene counts. I removed rows that have no counts

deseq2 baseMean differential gene expression rnaseqgene

updated 7.0 years ago • melkile26

Here is my process: 1) Feed raw count data of all the predicted genes within the sample (use **featurecounts** table). 2) Tranform the data to deseq2 compatible format and provide metadata 3) i have two samples (control vs

DESeq2

updated 4.4 years ago • Shail

get a direction about the correct design for my experiment I have counts tables (generated with FeatureCounts) my samples where sorted for 2 markers and I have samples from 2 different tissues (with triplicates). meaning

deseq2 differential gene expression multiple factor design

updated 7.2 years ago • galozs

Not sure if I need to tweak something in the DESeq2 parameters or I should use something like featureCounts for the counting step. Cheers for any insight, ```r # include your problematic code here with any corresponding

ATAC-seq DESeq2 Oddresults

updated 15 months ago • Ricardo Iván

<div class="preformatted"> Dear list, I have a question about the arguments of the align function in the Rsubread package. I have mapped my RNA-seq SOLiD data (single-end, 16 samples, 50bp long reads, human) with Rsubread using the align() function in 3 versions: -default parameters (1) -unique=TRUE and tieBreakQS=TRUE (2) -unique=TRUE (3) For my surprise, the percentage of mapped reads i…

Alignment Rsubread Alignment Rsubread

updated 13.6 years ago • Guest User

Starting from featureCounts generated raw counts file, I used edgeR to estimate the DE analysis and it went well. Now I use CPM normalized

Normalization edgeR RPKM

updated 5.2 years ago • anikng

Hello I'm doing an rna seq differential expression analysis using DESeq2 I did the read counting using **FeatureCount** but didn't normalize the read counts after. I just wanted to confirm if I have interpreted the DESeq2 manual statement...I'm doing an rna seq differential expression analysis using DESeq2 I did the read counting using **FeatureCount** but didn't normalize the read counts …

deseq2 rnaseq

updated 6.4 years ago • adeler001

a few samples with high counts of rRNA genes in the third replicate. My pipeline was HISAT2 --> featureCounts --> DESeq2. When clustering replicates 1 and 2, the replicates of each condition clustered closely together

DESeq2

updated 4.3 years ago • jac

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 data I've used is unnormalized raw counts from FeatureCounts. I would…

DESeq2

updated 2.5 years ago • bio2249

tool on a local instance of Galaxy (I find the GUI really easy to use, plus I can upload batches of featureCounts files rather than combining them manually). Today, I went to check my results by running it in R. Both were fresh

DESeq2

updated 2.7 years ago • murphytho1401

find genes that associate with changes in triglyceride levels (TG) in the liver samples. I used featureCounts to summarize the gene level. ``` > dge <- DGEList(counts=expr) > keep <- filterByExpr(dge) > dge <- dge[keep, , keep.lib.sizes

limma edger

updated 6.7 years ago • anna.cot.anna.cot

The main players, as we understand it, are: easyRNASeq, summarizeOverlaps() in GenomicRanges and featureCounts() in Rsubread. Outside of Bioconductor, we have used htseq-count from Simon Anders and treat this as the standard...divergence in read counts: http://imlspenticton.uzh.ch/pe.png ... at present, easyRNASeq and featureCounts()/Rsubread "overcount" reads and summarizeOverlap() "undercounts…

GO Infrastructure Rsubread easyRNASeq GO Infrastructure Rsubread easyRNASeq

updated 13.4 years ago • Mark Robinson

a bulk-RNA experiment, and I have mapped the sequencing to the human genome using ***STAR*** and ***featureCounts***, producing a count-matrix of **ENSGs** (rows) and **samples** (columns) of size [**E**xS]. I'm interested in running an ***edgeR&gt

limma edgeR biomaRt

updated 12 months ago • Jonathan

white-space:pre-wrap">ensembl\_gene\_id is the column of the count table that I obtained by using featureCounts to the latest gencode annotations. Why is this error occurring<span

biomart

updated 9.7 years ago • Darya Vanichkina

If not, what approach could I follow? Please note that so far, I have fragment counts from featureCounts for all my libraries; nevertheless, there are big differences between technical replicates sometimes (e.g

edgeR

updated 4.8 years ago • mo17

Hi everyone, I used DESeq2 for DE analysis of featureCounts data from RNAseq of 2 treatments (A & B) with 2 replicates each. I have the same error as in this thread: https...Hi everyone, I used DESeq2 for DE analysis of featureCounts data from RNAseq of 2 treatments (A & B) with 2 replicates each. I have the same error as in this thread: https://support.bioconductor.org...vari…

deseq2 featurecounts error message

updated 7.4 years ago • Yuqia

AT5G27710.2, AT5G45240.2 ``` And it can make the Txdb lose 6 genes compared with my featureCounts result ``` > genes(Tx_At) GRanges object with 37330 ranges and 1 metadata column: seqnames ranges strand | gene_id...ATMG09980 ------- seqinfo: 7 sequences from an unspecified genome ``` ``` # My featureCounts result > head(data) …

genomicranges genomicfeatures

updated 5.7 years ago • shangguandong1996

associated cirrhosis in patient derived hepatocytes" and i align them using hisat2, followed by featurecounts for raw counts matrix. when i am trying to process the raw_counts using deseq2 the results are not satisfactory

DESeq2 DifferentialExpression rnaseqGene DifferentialRegulation

updated 20 months ago • sajadahmad41454

No such file or directory</pre> But Rsubread is installed: <pre> library(Rsubread) featureCounts() NCBI RefSeq annotation for mm10 (build 38.1) is used. Error in paste(files, collapse = ";") : argument "files" is missing

dupradar rsubread

updated 7.5 years ago • b.nota

Hi, I was trying to investigate the changes of H3K27ac upon conditional KO of gene X. After mapping and counting the data using "featurecount" from "Rsubread" packages, I used the DEseq2 to perform differential analysis.  Below is the scatter plot (WT...the changes of H3K27ac upon conditional KO of gene X. After mapping and counting the data using "featurecount" from "Rsubread" packag…

deseq2 diffbind

updated 8.6 years ago • JunLVI

but only when using some RNA-seq analysis pipelines. Our RNA-seq pipeline uses Rsubread and featureCounts to get genewise counts, then either voom or edgeR to the differential expression analysis. Voom is attractive

Sequencing RNASeq edgeR Rsubread Sequencing RNASeq edgeR Rsubread

updated 12.7 years ago • Gordon Smyth

Hi! I did the code for exactTest and for glmQLFTest for my 153 samples. I used raw counts (DGE) for the DE analysis. Resuts from the exactTest: 10 genes with FDR<0.05 and 1651 genes with p-value< 0.05. With glmQLFTest results, all the p-values are >= 0.99 and all the FDR values are =1. Why are the results so different? glm approach ```r library(edgeR) library(tidyverse) l…

edgeR

updated 22 months ago • fr8712ca-s

and two time points for uninfected samples. I have a count matrix that was generated using featureCounts after alignment of reads using bowtie2, and the matrix includes reads mapping to the bacteria as well as the

RNASeq DESeq2

updated 2.2 years ago • Sean

very-sensitive-local` or others such as miRDeep2. When aligned to the genome, one can use e.g. `featureCounts` with mature miRNA coordinates from miRBase to assign features and when aligned to miRase sequences directly

tximport DESeq2 edgeR swish miRNA

updated 3.6 years ago • BG

I have mapped the data with the ensembl genome build WBcel215. I have ran tophat2 to map and featureCounts to counts the reads (both with the defaults parameters). I have two conditions, control and a knock-out with each

RNASeq DESeq DESeq2 RNASeq DESeq DESeq2

updated 11.6 years ago • Assa Yeroslaviz

1 = mutated). For the RNA-Seq I aligned with STAR and counted the number of reads per gene with featurecounts. Then I merged everything into a big read count matrix (column = sample ; rows=gene). Now I want to detect genes which

limma rnaseq mutations

updated 9.4 years ago • Nicolas Rosewick

Dear Team, I want to perform differential expression on counts generated from featureCounts. Each family has different disease. Can we perfrom differential expression across all samples? or since disease

deseq2 multiple factor design

updated 7.3 years ago • vrehaman

To preface this, I have used DiffBind and csaw for most of my experimental work and love these programs, this is just a general question I had and I have seen versions of these questions asked before on this forum - but would like to ask additional questions namely regarding the normalization procedures. (see: [https://support.bioconductor.org/p/116282/][1] and [https://support.bioconductor…

csaw ChIPseq DESeq2 DiffBind

updated 10 months ago • Luca

lib_spec][1] This structure follows to 27_sample. The df is a dataframe output from featureCounts. Columns of samples follow the same order that lib_spec. Although the obvious comparison would be according

design model.matrix edgeR complexdesign

updated 17 months ago • Karla

data from 8 time-points with 3 replicates per sample. These data were aligned with STAR, I get the featureCount output. With these file, I wan't to use MasigPro package to evaluate which genes are moving during this process

R masigpro edgr rnaseq negative binomial model

updated 8.0 years ago • nicolas.hipp

serif,arial,verdana,trebuchet ms; line-height:1.6">dds <- DESeq(DESeqDataSetFromMatrix(countData=featureCounts[,paste(1:24,"D",sep="")],colData=design,design=~Diagnosis:Age))</pre> First comparison is this, and is where I get the

deseq2

updated 7.0 years ago • hmgeiger

samples into a single BAM, called peaks (Genrich), and counted reads per peak region for each sample (featureCounts). I then ran limma following common guidance (example code below), and the resulting MA plot shows many more significantly

limma edger atac atac-seq

updated 5.9 years ago • pgugger