Cufflinks statistics

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Cufflinks specifications


Unique identifier OMICS_01304
Name Cufflinks
Software type Application/Script
Interface Command line interface
Restrictions to use None
Input format GTF, GFF, SAM, BAM, FASTA, TSV, CXB, FPKM_tracking
Output format GTF, GFF, SAM, BAM, FASTA, TSV, CXB, FPKM_tracking, DIFF
Operating system Unix/Linux
Programming languages C++
Computer skills Advanced
Version 2.2.1
Stability Stable
Maintained Yes


  • Cuffcompare
  • Cuffdiff
  • Cuffmerge
  • Cuffnorm
  • Cuffquant




No version available



  • person_outline Lior Pachter
  • person_outline Cole Trapnell

Publications for Cufflinks

Cufflinks citations


Distinct epigenetic landscapes underlie the pathobiology of pancreatic cancer subtypes

Nat Commun
PMCID: 5958058
PMID: 29773832
DOI: 10.1038/s41467-018-04383-6

[…] the human hg19 genome build and gene counts with the HTSeq software 0.5.3p9 ( using gene annotation files obtained from Illumina ( RNA-seq reads were also mapped using STAR with the proposed ENCODE parameters and XENOME on the human hg19 and mouse mm10 genomes and transcript annotation (Ense […]


Computational identification and validation of alternative splicing in ZSF1 rat RNA seq data, a preclinical model for type 2 diabetic nephropathy

Sci Rep
PMCID: 5955895
PMID: 29769602
DOI: 10.1038/s41598-018-26035-x

[…] tools have been developed to analyse alternative spliced transcripts in RNA-seq data. These tools can be divided into two categories based on their functionality. Tools in the first category include Cufflinks, RSEM, Kallisto, and Salmon, which can be applied to analyse known or annotated transcript isoforms. In this study, we chose Salmon, one of the top performers in speed and accuracy based on […]


Systematic pan cancer analysis of somatic allele frequency

Sci Rep
PMCID: 5956099
PMID: 29769535
DOI: 10.1038/s41598-018-25462-0
call_split See protocol

[…] d autosomal genes, were excluded from the analyses. For the NMD-analysis, short-living (<1 h half-life) transcripts were identified based on Tani et al.,. The gene expression was quantified using the Cufflinks package from the Tuxedo suite, as we have previously described. […]


Assessment of established techniques to determine developmental and malignant potential of human pluripotent stem cells

Nat Commun
PMCID: 5954055
PMID: 29765017
DOI: 10.1038/s41467-018-04011-3

[…] Samples were multiplexed (7–8 samples per lane) resulting in an average depth of 58 million reads per sample. Reads were aligned (human reference genome hg19) and transcripts counted using Tophat and Cufflinks. Data for analysis was expressed as FPKM values (Supplementary data , ) […]


DOT1L inhibition attenuates graft versus host disease by allogeneic T cells in adoptive immunotherapy models

Nat Commun
PMCID: 5954061
PMID: 29765028
DOI: 10.1038/s41467-018-04262-0
call_split See protocol

[…] , and the trimmed reads were mapped to the GRCh37 human reference genome using TopHat (version 2.0.14) and Bowtie2 (version 2.2.9). The read counts and FPKM values for each gene were calculated using Cufflinks (v2.1.1). The log2-transformed (FPKM+1) values were compared between SGC0946- and DMSO-treated T cells using the paired t-test, and FDR was calculated by the Benjamini–Hochberg method. Diffe […]


Direct measurement of pervasive weak repression by microRNAs and their role at the network level

BMC Genomics
PMCID: 5952853
PMID: 29764374
DOI: 10.1186/s12864-018-4757-z

[…] re mapped to D. melanogaster Reference Genome (BDGP6.83) using tophat [] and transcripts’ expression value was quantified as “Fragments Per Kilobase of exon per Million fragments mapped” (FPKM) using Cufflinks []. […]


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Cufflinks institution(s)
Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA; Department of Computer Science, University of California, Berkeley, CA, USA; Computer Science and Artificial Intelligence Lab, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Medicine, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA; Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA; Department of Mathematics, University of California, Berkeley, CA, USA; Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
Cufflinks funding source(s)
Supported by US National Institutes of Health grants R01-HG006102 and R01-HG006129-01, Damon Runyon Cancer Foundation Fellow, National Science Foundation Postdoctoral Fellow, National Science Foundation Graduate Research Fellow, Damon Runyon-Rachleff, Searle, and Smith Family Scholar, and is supported by Director's New Innovator Awards (1DP2OD00667-01) and the Center of Excellence in Genome Science from the US National Human Genome Research Institute.

Cufflinks reviews

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Sangram keshari sahu

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When it comes to post-mapping, Cufflinks-tools along with its sub modules (Cuffmerge, Cuffdiff) is good for transcriptome assembly and differential expression analysis (DEG) with RNA-Seq datasets. Because it handles the normalization internally, without additional steps. Being one of the oldest pipelines, there are several supporting tools developed for publication ready visualizations (Ex: CummeRbund). Although a similar tool "StringTie (faster to Cufflinks Assembler)" available, they still use some modules like CuffDiff to do DEG analysis.

Arup Ghosh

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Cufflinks is one of the earliest tools for differential gene expression analysis tools with FPKM/RPKM normalization. This tool is also capable of carrying out isoform abundance quantification and differential expression.