Bioconductor Forum

Essentially, due to low input RNA (issue with sequencer), there's a high number of 0s in the gene count matrix with featurecounts, and this gives a poor dispersion estimate (shown below, with ~60,000 genes) ![enter image description here][1] Then to deal with this, I filtered out the lowly expressed genes (with idx <- rowSums( counts(dds, normalized=TRUE) >= 5 ) >= 3)…

dispersionestimates dispersion DESeq2 estimates deseq2

updated 21 months ago • Julia

was done by sequencing facility using STAR) and **1) Generated read counts with RSubread featureCounts** ``` counts<-featureCounts(files=c("WGTR_0001_Le_n_WT_OT1DTAM1.merged.sorted.bam", "WGTR_0001_Le_n_WT_OT1DTAM2.merged.sorted.bam

edger

updated 4.9 years ago • melanie.girard

I am using Rsubread to analyze human FASTQ files from the ENA. I downloaded a GRCh38 FASTA from ENCODE to create and index. I used the featureCounts(bam.files, annot.inbuilt = "hg38") function to count mapped reads for genomic features. Everything seems to work...FASTQ files from the ENA. I downloaded a GRCh38 FASTA from ENCODE to create and index. I used the featureCounts(bam.files, annot.i…

Ensembl Rsubread

updated 2.1 years ago • agustin.gonvi

analysis. What files should I use as the input file? is it just gene count files in tabular form by featurecount? Thank you

RNASeq

updated 2.4 years ago • cam

Hi, I did my RNA-Seq analysis using the Galaxy platform with the following pipeline: HISAT2 --> featureCounts --> DESeq2. Now I want to recreate the PCA plot in RStudio. In the DESeq2 manual, the command line for this is: plotPCA

DESeq2

updated 2.6 years ago • jac

after aligning using the subjunc function. Is it acceptable (to save processing time) to apply featureCounts() to the subjunc BAM files? Will this produce different feature counts than I would get if I used the align function

rsubread subjunc

updated 8.8 years ago • Stephen Piccolo

View(bam.files) # Ver lista de archivos del directorio (.BAM) bam.files[12] head(bam.files, n = 12L) #### FeatureCount: Programa que cuenta las lecturas de los bam mycount = list() for (i in 1:12) { mycount[[i]] <- featureCounts(files = bam.files...splitOnly = FALSE) } > for (i in 1:12) { + + + mycount[[i]] <- featureCounts(files = bam.files[i], + …

Rsubread

updated 2.6 years ago • v.merino.nicolas

forward-stranded or rev-stranded and PE or SE)? Like it possible to do, for instance, using featureCounts from Rsubread... Unfortunately, I didn't find that information in the reference manual. Thanks in advance, Best

ribosomeProfilingQC countReads

updated 3.2 years ago • alexandr.gopanenko

Hi, I was doing repeat analysis from RNA seq data and learn that featureCounts() function ("Rsubread" package) can provide fraction counts for multi-mapping reads. However, DEseq2 doesn't take

deseq2

updated 8.4 years ago • tg369

down). Below are the codes of how I obtained length info and plots, as well as the plots 1) Using featureCounts results: featCountsData <- read.table("charolais\_145A\_TGACCA.featCounts.txt", header=TRUE, comment.char...nullp(DEgenes = genes, bias.data = testLenData, plot.fit = TRUE) PLOT 1: Length info obtained from featureCounts: https://drive.google.com/file/d/0B6Ho35U9KAepTGxuR0Fx…

goseq

updated 8.1 years ago • mrodrigues.fernanda

Hi, I am trying to use the Bioconductor package in R 3.6.3 on Windows 64-bit platform to analyse my RNA-seq data with Apis mellifera. I am facing difficulty from an error described below. I have checked the available GTF file, using readGFF, the gene_id comes in the 10th column. But that is how I have downloaded the file from: https://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/003/254/395/GCF…

featureCounts

updated 4.1 years ago • chatterjee.arumoy

Enter the body of text here I did RNAseq of a Drosophila cell line. By using RNASTAR in Galaxy I am getting high number of reads mapped to too many loci. (uniquely mapped 60 %, mapped to multiple loci 10 %, mapped to too many loci 24 %). Later when I am doing FeatureCounts there is only 40 % assigned, unasigned : unmapped 20 %, unassigned : mapping quality 35 %. Should I consider this as …

RNASeqData

updated 2.2 years ago • vasa.broz

package. I routinely deal with mixed paired end and single end data. The Rsubread function featureCounts had a isPairedEnd argument that used to accept a logical vector containing information of which files are

software error Rsubread

updated 3.9 years ago • barrel0luck

Hi , For the following : > fCountsList = featureCounts(props, annot.ext="/patho/to/gtf/GRCh38.gtf", isGTFA nnotationFile=TRUE, nthreads=16, isPairedEnd=TRUE, allowMultiOverlap

normalization

updated 5.2 years ago • memoly101

Hi, I want to remove X and Y chromosome genes from my bulk seq data. I don't know how to proceed with that. Do I need to remove the genes from the counts after featurecounts or using the Deseq2? I also tried using the code from the previous post (https://support.bioconductor.org/p/67237...seq data. I don't know how to proceed with that. Do I need to remove the genes from the counts after featurec…

DESeq2 RNASeq

updated 3.4 years ago • Archit

nbsp;and in Genome Browser that some exons do not belong (or are not included in the analysis of featureCounts from rsubread package) to the gene that is specified by those packages.</span>   <pre> mm9 = TxDb.Mmusculus.UCSC.mm9.knownGene...3 are Xkr4.  I do not know why but only one transcript is included in the in-built version of FeatureCounts of Rsubread p…

rsubread featurecounts

updated 8.7 years ago • tonja.r

Hello, I have a question relative to the featureCounts function, from the Rsubread package: from the documentation: "minOverlap: integer giving the minimum

Rsubread minOverlap featureCounts

updated 8.1 years ago • c.merce

rejecting overlapping reads if I assign them to all isoforms in which they are falling i.e. by using featurecounts and then find differential expression using DESeq. Do you think the results which I got after it will be significant

DESeq ASSIGN DESeq ASSIGN

updated 9.8 years ago • Gourja Bansal

case. Another approach I have used to get the normalized TMM value for upstream regions is to use featureCounts program and then normalize the reads using DESeq TMM normalization. But in that case the value of total counts...here or any parameter values I need to change because for the same dataset with default parameter featureCounts gives me counts that I can further normalize using DESeq (Kind…

chip-seq TSS TMM csaw

updated 8.0 years ago • saadmurtazakhan

Hi Everyone,   I'm trying to analyze some RNAseq results, but one of my samples is a pretty bad outlier by PCA and by clustering over the entire transcriptome. I have 4 groups with 3 biological replicates.  These samples were run in 2 batches. When I try to summarize my reads using RSubread's featureCounts, the outlier has a very low assignment %, with a high % of multiple a…

rnaseq outlier statistics batch effect

updated 7.9 years ago • grastalt27

RNA-Seq data for 8 different treatment conditions, with 3 biological replicates for each. I used the featureCounts command on Rsubread and have the raw counts matrix for all 24 samples at the meta-feature(gene) level. I was wondering

differential gene expression biologicalreplicates raw_counts

updated 5.7 years ago • tasnif.rahman

Hi I essentially have a counts data frame from featurecounts (Rsubread) and its giving me the error seen above..... Does anyone know how I can check input counts file "test4", find

deseq rna-seq

updated 9.2 years ago • rodriguez.varenka

infection consisting of 3 time points and a virus free control with 3 replicates each produced with featureCounts. Normalization after running template_script_DESeq2.r: ![enter image description here][1] It does not look

DESeq2 viral controls

updated 19 months ago • f99942

transcripts into a single feature, just like what `bedtools merge` does. 2. When I use the `featureCounts` of `Subread` package (v2.0.3, command-line version), will `-g gene_id -t transcript` and `-g gene_id -t gene` give me same

Rsubread ensembldb

updated 9 months ago • Ya

Hi, I am new to Deseq analysis. Recently i conducted metatranscriptomics analysis of bacterial community in two different conditions. My aim to explore the overall significent transcript expression and also some selective transcripts (related to specific function). I used raw featurecounts output to run Deseq and created heatmap on VSD transformed data on to 20 features. But, due to vast …

DESeq2

updated 2.8 years ago • Shail

nbsp;org.Mm.eg.db (org.Mm.egENSEMBL) to annotate the differential expressed genes (tophat(mm9)-featureCounts-RUVseq-edgeR). Although the results are nice some genes could not well being annotated and I guess it is is because

edgeR ruvseq rnaseq isoforms

updated 9.0 years ago • sergio.espeso-gil

to a genome using the Gencode M17 comprehensive annotation .gtf file. Then I did read-counting using featureCounts, but I supplied a subset of the annotation, containing only lncRNA annotations. This leads to  only 1-2% of

edger rnaseq

updated 6.1 years ago • martin.weihrauch

res$ensembl, mart = ensembl ) fc$counts are gene IDs and counts from featureCounts function

biomaRt getBM

updated 5.1 years ago • angelica.lindlof

35096 34391 24142 38428 30607 28948 45369 35688 36033 25738 20554 44144 `` The parameters used in featureCounts function are: <pre> countPrimaryAlignmentsOnly=TRUE, isPairedEnd=TRUE, annot.ext='gencode.v24.chr_patch_hapl_scaff.annotation.gtf

rsubread

updated 8.2 years ago • Likai Mao

I am using DESeq2 to run a multifactor paired analysis to determine the change in gene expression between men and women due to a treatment on 70 males and 45 females. Because I have a differing number of samples for each condition, I'm using the following steps to create a custom design matrix: https://support.bioconductor.org/p/63134/\#63146 Everything is fine until estimateDispersionsGeneEst(d…

deseq2 differential gene expression model matrix

updated 7.3 years ago • gregory.l.stone

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

RNASeq DESeq2 vst rlog Normalization

updated 2.4 years ago • mohammedtoufiq91

site led me to this [discussion](https://support.bioconductor.org/p/65604) on the performance of featureCounts for that purpose but it has no details about how the annotations are input to the software. i'm familiar with

GenomicFeatures repeatmasker GenomicAlignments

updated 6.5 years ago • Robert Castelo

I want to plot trends between genes across different conditions from my normalized count matrix (featurecount-EdgeR). I was using "csCluster" in cummerbund. Now I switched to this pipeline and I am wondering, if similar pacakage

edger clustering visualization

updated 5.6 years ago • thindmarsmission

nbsp; I'm wondering whether I should be using the raw counts output from read summarisation (eg featureCounts output) or say the "E" matrix of normalised log2 counts from the EList object after voom transformation, or if

limma rnaseq geneexpression voom counts

updated 9.5 years ago • Peter Crisp

all reads are reversed with respect to the genomic sequence of the transcript and annotation. With featureCounts I would have to use -s 2 option, for example, to get a 70+% rate of assignments to transcripts. But now I am very concerned

easyrnaseq rnaseq strand

updated 6.9 years ago • Michael Dondrup

Hi all - Hoping I can get some guidance on an issue I'm having with the _featureCounts_ function in the _RSubread_ package. I've successfully aligned 150bp paired-end reads to the mouse genome and am trying to summarize the reads to features. My problem is that if I summarize with strandSpecific=1, I get the following output showing less than 3% of fragments assigned to features: …

rsubread featurecounts rnaseq

updated 9.1 years ago • beiting

More perplexingly, they have 100% sequence identity with a single gene. My question, then, is why featureCounts is failing to map these sequences? I've thought to change the stringency settings, but I doubt that will make

featurecounts rnaseq subread

updated 5.7 years ago • rogangrant

sample represent one cell. I have used `STAR` to map the samples against my indexed genome and `featureCounts` to quantify the reads onto the genes. If I do a pre-filtering before running the DESeq function only very little

DESeq2 SMART-seq

updated 14 months ago • Assa Yeroslaviz

pulled down the protein and sequenced both IP and input. I got the reads assigned to each gene using featurecount and use that as input to Deseq2, and I have two replicates for IP and input. After differential expression analysis...Log2FC from Deseq2, however, the log2FC is not consistent with the RPM I calculated (RPM calculation: featurecount assigned reads/total reads *1000000). Here is an e…

RNASeqData DifferentialExpression SmallRNAData DESeq2

updated 7 months ago • Shihui

packages/release/bioc/html/Rsubread.html) aligner and were then summarized to genes using the [featureCounts](http://bioconductor.org/packages/release/bioc/html/Rsubread.html) program. This package includes the gene

seqc rsubread featurecounts subjunc ercc News

updated 9.5 years ago • Wei Shi

RNA Seq data from human biopsies (2 groups, 50 samples each). My pipeline is trimmomatic-star-featureCounts-edgeR-voom/limma (big fan of limma, being a veteran from array days..). <span style="line-height:1.6">I am looking into

limma edger sequencing

updated 7.8 years ago • blofeld

genes across species. I was planning to filter the table of raw counts (previously obtained with featureCounts) to obtain the raw counts of these ~2500 orthologs across species replicates in condition B, normalize them

DESeq2

updated 7 weeks ago • Laura

Before using this pipeline I used to get started from the raw gene counts from `featureCounts` then use in EdgeR. ```salmon.merged.gene_counts_length_scaled.rds salmon.merged.gene_counts_length_scaled.tsv

salmon edgeR tximport nf-core gene_counts

updated 15 months ago • mohammedtoufiq91

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 23 months 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 5.1 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 7.3 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 5.2 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 5.2 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 7.5 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 3 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 6.0 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 5.5 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 6.7 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 5.6 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 12.0 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 5.3 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 6.5 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 8.3 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 6.9 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 5.6 years ago • Beginner