Bioconductor Forum

to normalize some RNASeq data. My data was aligned to `` hg38 `` and I used `` featureCounts `` to aggregate by Ensembl gene ID (GRCh38 v. 87). I used the following call: <pre> > hsa.len.gc <- getGeneLengthAndGCContent

edaseq normalization hg38 biomart org.db

updated 8.1 years ago • mark.ebbert

I have RNA-Seq data with raw counts extracted from bam files using `featureCounts`. I wanted to convert counts to tpm, because I need TPM for some analysis. Initially, I got the coding length for

rnaseq counts tpm GenomicFeatures kallisto

updated 5.2 years ago • m93

of? I could also just use the 10,000bp bins to count the reads from the BAM files using Rsubread's featureCounts, but I wondered since I already have the information if I could get my result faster

granges genomicranges featurecounts

updated 9.0 years ago • s1437643

GTF file ) ``` This causes an issue in generating the counts list in the following chunk: ```r ## featurecounts capture.output({counts_list <- summarize_reads( SummarizedCounts = sc, saf_list = saf_list, gtf = gtf, threads

CleanUpRNAseq

updated 14 months ago • rcreed

Hi all, I am running WGCNA on a set of 129 samples from three timepoints with three diseases and various physiological traits. Unfortunately, due to project logistics, they were not able to be sequenced at the same time, and looking at the module-trait relationship, it looks like there is quite a strong batch effect resulting from various aspects of sequencing. Embarrassing facts: Timepoint…

WGCNA batch effect continuous

updated 6.9 years ago • cats_dogs

the reads back to genes found in the assembly and counting up the reads mapped per gene using featureCounts, I then divided the total reads by gene length, and now would like to sum up these coverages by KO to get a sense

DESeq2 medianofratiostransformation StatisticalMethod Normalization dispersion

updated 2.0 years ago • Linton

R user.  I ran the edgeR for the TCGA RNAseq  data using raw count from the Rsubread featureCounts  and the TCGA miRNAseq data using raw count from TCGA level3 data to identify differential expressed

CPM edgeR

updated 10.6 years ago • ycding

modeling-step already at the counting level, and this is kind of keeping me in the "old and safe" featureCounts-based approach. Do you have a suggestion on how to sell at best the advantages of the new method, well, apart from

deseq2

updated 9.2 years ago • Federico Marini

I generated a count list using featureCounts of my ATAC-seq data and fed it into R. I got the GC bias and lenght for each peak queried, and made a list for the sequencing

cqn normalization conditionalquantilenormalization atac-seq

updated 6.5 years ago • Eric.Martin

pre-processing tools for alignment, counting, or sequence analysis (e.g., Cell Ranger, STAR, HTSeq, featureCounts, salmon, GATK, etc.) and R packages designed for the above-mentioned methods (e.g., DESeq2, limma, Seurat, etc.). A solid

JobPosting

updated 4.6 years ago • hannah.baskir

from Rsubread-align are all NA (see code below). counts\_TH14\_uniqtrue\_annotMirBmature.out <- featureCounts(files=mapped.flist,      annot.inbuilt="hg38", chrAliases=NULL,     \# use mirBase GTF

rsubread miRNA

updated 9.3 years ago • Ina Hoeschele

nbsp;and 13 control samples. The reads were aligned with TopHat2 and read were summarized using featureCounts. When estimating the dispersion, I get a value of 3.29, and the following BCV plot: <img alt="" src="http://i.imgur.com

edger

updated 9.1 years ago • dsperley

I try to read counts using featurecounts and I have a warning says: could somebody help me to figureout the problem?   Warning: failed to find the gene

featurecounts

updated 7.3 years ago • roghaiyeh.safari

gt; library(Rsubread) > fls <- paste0("../data/", dir("../data/", "sam$")) > dat <- featureCounts(fls, annot.inbuilt = "mm10") Mouse annotation NCBI Build 38.1 is used. ========== _____ _ _ ____ _____ ______ _____ ===== / ____| | | | _ \| __...__| | ========== |_____/ \____/|____/|_| \_\______/_/ \_\_____/ R…

Annotation PROcess Rsubread Annotation PROcess Rsubread

updated 12.2 years ago • James W. MacDonald

Hi, I am a master student in biomedicine at Lund University in Sweden. I am using edgeR for differential expression of genes. I am a beginner in the use of edgeR. ``` setwd("C:/Users/Analysis") library("edgeR") library(tidyr) data <- read.csv("C:/Users/Analysis/Data/Case_Control_Phenotype_Features.csv") group <- as.factor(data$T2D) #group include individuals with T2D (YES) and n…

RBioinf

updated 23 months ago • fr8712ca-s

the alternative splicing events by R. Here is the Syntax I used. ``` library(edgeR) fc <- featureCounts(files=c("file control1.bam", "file control2.bam", "file control3.bam", "file treated1.bam", "file treated2.bam", "file

diffSpliceDGE RNASeq DifferentialSplicingWorkflow AlternativeSplicing edgeR

updated 3.8 years ago • zhaoqiao1027

gtfFeature 'exon' --gtfAttr 'gene_id' ``` 2. quantify the reads based on the exons ``` featureCounts -a $gtf -t exon -g exon_id -p -T 12 -o featureCounts.exonLevel.txt subjunc/*.bam ``` 3. upload the data into R, create a `DGEList

diffSpliceDGE edgeR DifferentialSplicing

updated 4.0 years ago • Assa Yeroslaviz

time points (T1 and T2). The mapping was done with STAR aligner and the quantification was done with FeatureCounts. When I perform the paired analysis in F: T2 vs T1 and NF: T2 vs T1. I create a design matrix including the variables

limma lmfit R DifferentialExpression

updated 3.7 years ago • Dimitris

Hi, I am trying to find DE genes using two groups (4 biological samples with two different types of tissues) using RNAseq. I obtained a raw gene count table from FeatureCount. I am using both  glmLRT and glmQF. glmLRT identified ~600 DE genes, while glmQF identified only 3. What was also...samples with two different types of tissues) using RNAseq. I obtained a raw gene count table from…

edgeR

updated 9.4 years ago • miyakokodama

gt;0.7) >= 3 where y is my DGElist__/__?__ What I'm doing: 1. Using the command-line version of featureCounts to count reads to collapsed transcripts (i.e. genes), importing the resulting table into R and getting a clean

goseq

updated 9.5 years ago • Darya Vanichkina

nbsp;   Indels : 0      Running time : 259.9 minutes \#I then used the featureCounts method to produce read count values <pre> fc_SE <- featureCounts("alignResults55296.BAM",annot.inbuilt="hg19

rsubread mapping featurecounts align

updated 10.1 years ago • Jo

doing it: within DEXSeqResults the first line is: LRTresults <- results(object, filter=rowMeans( featureCounts(object) ) ) while the estimatelog2Foldchanges function is using: testablegenes <- as.character( unique( groupIDs...I go with the DESeq2 default than it should be LRTresults <- results(object, filter=rowMeans(featureCounts(object, normalized=TRUE)))   …

DEXSeq

updated 10.9 years ago • n.kreim

Hello, I am analyzing RNA-seq data of arabidopsis samples in response to three treatments (let's call them WT, RT and DT). These treatments have some components in common, so I want to find genes that respond specifically to the unique components in each treatment. In summary, I have performed the Differential Expression analysis of the three treatments versus the non-treated sample (NT), a…

edger complexheatmap R clustering

updated 5.7 years ago • eggrandio

converting counts to integer mode Warning message: 0 aggregate geneIDs were found truncated in featureCounts output Error in `$<-.data.frame`(`*tmp*`, "dispersion", value = NA) : replacement has 1 row, data has 0 Calls: estimateDispersions

DEXSeq

updated 3.0 years ago • Ben J

list=ls()) setwd('H:/qde-2.20191220/DEG/') library("edgeR") Counts data generated by featureCounts program countData <- read.table('qde2_featurecounts',header = TRUE,sep = '\t',row.names = 1) countData <- countData

edgeR no replication glmLRT(fit coef=2)

updated 6.1 years ago • hong1ang

nthreads=8) bamlist_splicing=list.files(pattern=".subjunc.sorted.BAM$") counts_splicing <- featureCounts(bamlist_splicing, annot.ext="dmel-all-r6.38.gtf", isGTFAnnotationFile=TRUE, GTF.featureType="exon", useMetaFeatures

edgeR Rsubread

updated 4.8 years ago • jbono

I am using RUVSeq + edgeR to perform differential expression of these repeats after counting using FeatureCounts. There are approximately 750k repeats, however not all of them show expression. Because I do not have a set of

RUVSeq

updated 8.9 years ago • cguzman.roma

files with czid-dedup - Used HISAT2 for allignment with GRCm38 as the reference genome and used FeatureCounts to summarize counts for genes - Used Bayesian method based on mRNA counts provided by DESeq2 for differential

DESeq2

updated 3.1 years ago • Yongqing

I have an experiment with 30 samples that I aligned using STAR and created a counts file using featureCounts. I'm struggling to properly set up the design matrix as cursory analysis shows a clear donor effect in the MDS

rna-seq edger

updated 9.2 years ago • es874

alteration between conditions of **mice** samples. I made a workflow with Rsubread to align and featureCounts to count. For splicing I switched to the subjunc() function. It worked well. Then I discovered the "reportAllJunctions

Rsubjunc Rsubread

updated 22 months ago • thomas.heigl.ibk

Dear Bioconductor, I am currently performing an RNAseq analysis on rat samples using edgeR. Data was aligned using STAR against the rat genome (Rnor v6.0) and the genes were counted using featureCounts against the Ensembl Rnor gtf file. The experimental design comprises two factors: DSS and stimulation. > phenosheet...Data was aligned using STAR against the rat genome (Rnor v6…

edger glmqlftest()

updated 8.0 years ago • Andy91

Hi all,  I have recently posted an Rsubread featurecounts related question, but I have another one, based on a quality control analysis I would like to do:  I am attempting

rsubread alignment align

updated 7.1 years ago • A

AZM", and "TOB". I have provided the output of the first 10 rows of the raw counts obtained using featurecounts below. I have also provided the metadata table I used for the analyses below: ``` head(DESeq2_data, 10) Geneid BHI_1

DESeq2

updated 4.6 years ago • Naphtap92

<div class="preformatted">On Wed, May 30, 2012 at 7:11 PM, Tim Triche, Jr. <tim.triche at="" gmail.com=""> wrote: > Hi Dr. Smyth, > > ?Thank you for the helpful clarifications. ?It seems like RPM/CPM is > useful for tasks such as plotting expression on a reasonably similar scale; > taking logs and adjusting for mean-variance relationships can better …

Normalization graph limma convert edgeR DESeq Rsubread Normalization graph limma convert

updated 13.6 years ago • Kasper Daniel Hansen

the same data. I used the same code mentioned in edgeR tutorial for differential expression with featurecounts data. library(edgeR) group <- factor(paste0(df$Status)) y <- DGEList(U, group=group) keep <- rowSums(cpm(y) > 0.5) &gt

limma edgeR differential gene expression r

updated 8.4 years ago • Biologist

of tools that produce genewise read counts from RNA-seq > data. My lab routinely uses subread and featureCounts: > > http://www.ncbi.nlm.nih.gov/pubmed/24227677 > > which are available from the Bioconductor package

RNASeq edgeR Rsubread RNASeq edgeR Rsubread

updated 12.0 years ago • Gordon Smyth

t need all the above counting steps. The above steps have given me odd results. That is why I used featurecounts program from Subread package and made my counts file. \#\# Set Working Directory setwd("/media/A2C7-ACFD/") getwd() \# load

deseq2

updated 10.9 years ago • gokhulkrishnakilaru

First timer here and very new to this.   Question is on resultsNames(dds) nor results(dds)  give the comparisons I am looking for.  I know it's been asked but I'm still confused on how results function works.  Below is the console session, boldfaced the code to make it easier to see.  I did do  out.16w <- DESeq2::results(dds,&nbsp…

deseq2 DESeq2 resultsNames

updated 8.5 years ago • davichen

Greetings to those familiar with Feature Counts, We have one RNA sequencing, paired-end, 150bp file for which we estimate gene and junction counts using Feature Counts. We run Feature Counts in Linux. Feature Counts version: 2.0.8 Feature Counts code: $FCOUNTS -a GCF_000001405.40_GRCh38.p14_genomic.gtf -G GCF_000001405.40_GRCh38.p14_genomic.fna -T 8 -J -M -s 0 -p --countReadPairs -…

featurecounts Rsubread

updated 13 months ago • chris2.a.white

Hi, I am running my bulk RNA-seq analysis, I use feature counts from subread package to generate my raw counts from bam files using paired-end option. Do I still need to give library type when I use DESeq() function to get my DEGs? I appreciate your help!

DESeq2 featurecounts

updated 3.0 years ago • Bo

Hi All, I want to extract the counts that are arising form pre-mRNA (i.e non-split reads). For the sigle-end library kind of easy but for the paired end the situation is bit different. Because FWD reads in the exon and reverse reads are in the introns so i don't know how to extract this information. I have searched quiet a lot but not able to find the information. My read size is 60 nt and …

rsubread featurecounts Bioconductor countsextraction

updated 2.8 years ago • barrypraveen

When doing differential gene analysis, why measuring genes based on exons? Can we measure genes based on CDS?

rnaseq featurecounts edger deseq2

updated 8.2 years ago • Jack

Hello Everyone, I got counts data for some samples using "STAR". I need to convert the counts into rpkm values and then normalize them for further analysis. I'm not aware how to do this. Can anyone help me in this? Thank you Example counts data: V1 V2 V3 V4 V5 V6 V7 V8 ENSG00000000003 0 0 0 0 1 0 0 0 ENSG00000000005 0 0 0 0 0 0 0 0 EN…

r featurecounts rpkm tpm edger

updated 8.4 years ago • Biologist

I got a list of paired end bam files, and want to do DESeq2 analysis. The first thing is to count the reads at gene level. I tried feature counts. However, it requires reorder of the bam files if I specified paired end is True, which takes infinite time for my huge dataset. I also tried summarizeOverlaps, which also takes very long time. Is there any tools could quickly count th…

deseq featurecounts paired

updated 9.7 years ago • tszn1984

Hi, I have generated my own annotation file for feature count, However I do not get any error in running but I get zero number which means none of the reads are aligned to my selected regions (created in annotation file). In IGV, I can see that reads are aligned to the selected regions. The annotation file is like this: GeneID Chr Start End Strand &…

annotation featurecounts

updated 8.3 years ago • fatemeh.kaveh

Bioconductors: We are pleased to announce Bioconductor 2.14, consisting of 824 software packages, 200 experiment data packages, and more than 860 up-to-date annotation packages. There are 77 new software packages, and many updates and improvements to existing packages; Bioconductor 2.14 is compatible with R 3.1.0, and is supported on Linux, 32- and 64-bit Windows, and Mac OS X. This release in…

BiocViews aCGH SNP Sequencing RNASeq ChIPSeq miRNA Microarray qPCR Metabolomics Coverage

updated 11.8 years ago • Dan Tenenbaum

Bioconductors: We are pleased to announce Bioconductor 2.13, consisting of 749 software packages, 179 experiment data packages, and more than 690 up-to-date annotation packages. There are 84 new software packages, and many updates and improvements to existing packages; Bioconductor 2.13 is compatible with R 3.0.2, and is supported on Linux, 32- and 64-bit Windows, and Mac OS X. This release in…

BiocViews aCGH SNP Transcription Sequencing miRNA Microarray Genetics Proteomics Coverage

updated 12.3 years ago • Dan Tenenbaum

Bioconductors: We are pleased to announce Bioconductor 2.12, consisting of 671 software packages and more than 675 up-to-date annotation packages. There are 65 new software packages, and many updates and improvements to existing packages; Bioconductor 2.12 is compatible with R 3.0, and is supported on Linux, 32- and 64-bit Windows, and Mac OS X. This release includes an updated Bioconductor Ama…

BiocViews aCGH SNP Transcription Sequencing Microarray Coverage Alignment Annotation GO

updated 10.5 years ago • Dan Tenenbaum