easyRNASeq protocols

View easyRNASeq computational protocol

easyRNASeq statistics

To access cutting-edge analytics on consensus tools, life science contexts and associated fields, you will need to subscribe to our premium service.


Citations per year

Citations chart

Popular tool citations

chevron_left Differential expression Known transcript quantification Transcriptome annotation Demultiplexing Normalization Bioinformatics workflows chevron_right
Popular tools chart

Tool usage distribution map

Tool usage distribution map

Associated diseases

Associated diseases

easyRNASeq specifications


Unique identifier OMICS_01938
Name easyRNASeq
Software type Pipeline/Workflow
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License Artistic License version 2.0
Computer skills Advanced
Version 1.4.2
Stability Stable
methods, parallel, graphics, utils, genomeIntervals(>=1.14.0), Biobase(>=2.18.0), BiocGenerics(>=0.4.0), biomaRt(>=2.14.0), edgeR(>=3.0.0), Biostrings(>=2.26.0), BSgenome(>=1.26.0), DESeq(>=1.10.0), GenomicRanges(>=1.10.0), IRanges(>=1.16.0), Rsamtools(>=1.10.0), ShortRead(>=1.16.0), BSgenome.Dmelanogaster.UCSC.dm3(>=1.3.17), GenomicFeatures(>=1.10.0), RnaSeqTutorial(>=0.0.10)
Maintained Yes


Add your version



  • person_outline Nicolas Delhomme <>

Publication for easyRNASeq

easyRNASeq in pipelines

PMCID: 5928323
PMID: 29740591
DOI: 10.3389/fcvm.2018.00030

[…] the left end of the r2 reads). sequence alignment was performed using tophat v2.1.0 to the mm10 genome. bam files were merged on a per sample. exon and gene level counting were performed using the easyrnaseq version 2.4.7 package. a binary annotation file, built using the annotation file generation function of easyrnaseq, was used for this analysis; the ensembl release 83 gtf file was used […]

PMCID: 4972487
PMID: 27333023
DOI: 10.1016/j.ebiom.2016.05.011

[…] casava software version 1.83 was used to produce de-multiplexed fastq sequence files from raw .bcl files. sequences were aligned to the human genome version hg19 (uc santa cruz) using tophat v1.4.1. easyrnaseq v1.6.0 running on the r version 3.0 platform was used for determination of raw reads and reads per kilobase per million reads (rpkm) for each gene and exon. using a custom r script, […]

PMCID: 4626857
PMID: 26507234
DOI: 10.1128/mBio.01520-15

[…] bases were removed using trimmomatic (leading:27 trailing:27 slidingwindow:4:20 minlen:35) (), mapped using bowtie (), and sorted with samtools (). the number of reads per locus was calculated with easyrnaseq (). the .gff file was generated using the rast annotations (, ). reads were normalized by number and compared to the water control. rna-seq results can be found in in the supplemental […]

PMCID: 4077804
PMID: 24983472
DOI: 10.1371/journal.pone.0101425

[…] (illumina, san diego, ca, usa). tophat 1.4.1 software was used to align the library reads to the ucsc mouse (mm9) reference genome (>75% efficiency), and annotated using samtools v0.1.18. easyrnaseq version 1.6 was used to count reads mapping within ensembl version 66 exons, and calculate normalized counts for each gene. raw count files were annotated using data from ensembl mouse […]

PMCID: 3881016
PMID: 24330725
DOI: 10.1186/1471-2229-13-213

[…] in order to correct for differences in both library sizes and gene length. furthermore, sorted and indexed bam files were processed with the statistical software r v.2.15.1[] and the r package easyrnaseq by providing an annotation object created by the r packages easyrnaseq, biomart, genomicranges and genomicfeatures[]. correspondingly, calling the easyrnaseq() function of the r package […]

To access a full list of citations, you will need to upgrade to our premium service.

easyRNASeq in publications

PMCID: 5399671
PMID: 28264836
DOI: 10.1242/dev.148494

[…] from ucsc table browser as a guide. all assemblies were merged to obtain a merged annotation file, which was passed to cuffdiff (v2.1.1) to obtain normalized rpkm value for each gene, and to easyrnaseq (v2.1.0) to retrieve the count table for all genes (). all sequencing data were deposited in gene expression omnibus (geo) under accession number gse69185., deseq (v1.16.0) was used […]

PMCID: 5356301
PMID: 28302071
DOI: 10.1186/s12864-017-3608-7

[…] sorted and indexed) with samtools [] and only reads that mapped to a single gene were used for further analysis. uniquely mapped reads were used to generate counts for each annotated gene using easyrnaseq []. a count table was generated for all samples containing the number of reads for each of the 37,315 annotated genes from the mouse genome. for differential expression analyses, rna-seq […]

PMCID: 5337622
PMID: 28194033
DOI: 10.1038/oncsis.2017.1

[…] under accession number srp064894., expression profiles of 15 paired escc and non-tumor samples were extracted by using tophat (v2.0.6, tophat, washington, md, usa) and easyrnaseq version 1.6.0 (heidelberg, germany), in which the lncrnas and pcgs were included. then, we used deseq version 1.14.0 (heidelberg, germany) to identify the differentially expressed lncrnas […]

PMCID: 5187580
PMID: 28000665
DOI: 10.1038/ncomms13856

[…] modifications adapted from (2s rrna block oligo added before 5′ ligation step to decrease rrna reads in final library)., reads were mapped to the dm3 genome using tophat. the bioconductor r package easyrnaseq was used to count reads (using ‘genemodels' summarization parameter) and calculate normalized reads per kilobase per million (rpkm) values. error bars presented represent s.e.m. with three […]

PMCID: 5431353
PMID: 28442708
DOI: 10.1038/s41598-016-0025-0

[…] convert the sam file generated by bowtie2 to the bam format, which was then sorted and indexed. samtools was also used to perform alignment quality check. the sorted bam file was used as input for easyrnaseq version 2.2.0, along with a gtf file containing gene annotation, to obtain count tables. the count tables (file ) were fed to deseq2 version 1.6.2 in order to perform differential gene […]

To access a full list of publications, you will need to upgrade to our premium service.

easyRNASeq institution(s)
Genome Biology Computational Support; Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
easyRNASeq funding source(s)
Supported by the European Molecular Biology Laboratory, an ERASysBio grant ModHeart and a NIH grant (NIH: R01 GM068717).

easyRNASeq reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review easyRNASeq