Cufflinks

Cufflinks assembles aligned RNA-Seq reads into a parsimonious set of transcripts and estimates their relative abundances to quantify transcript-level expression and reveal alternative transcription and splicing.


Key Features:

  • Read input and parsimonious assembly: Accepts aligned RNA-Seq reads and assembles them into a parsimonious set of transcripts while estimating relative abundances based on read support.
  • Transcript discovery and abundance estimation: Performs simultaneous transcript discovery and abundance estimation without requiring prior gene annotations to enable exploration of alternative transcription and splicing events.
  • Reference annotation-based transcript assembly: Assembles novel transcripts in the context of existing annotations to address the reference annotation based transcript assembly problem.
  • Differential expression analysis (Cuffdiff 2): Uses Cuffdiff 2 to perform transcript-level differential analysis, controlling for variability across replicate libraries and identifying differentially expressed transcripts and genes, as well as changes in splicing and promoter preference.
  • Correction of library preparation bias: Applies a likelihood-based approach to account for non-uniform distribution of cDNA fragments within transcripts caused by RNA-Seq library preparation, improving accuracy and replicability across libraries and sequencing technologies.

Scientific Applications:

  • Mouse myoblast transcriptome analysis: Applied to over 430 million RNA-Seq reads from a mouse myoblast cell line to detect known and previously unannotated transcripts and to reveal substantial shifts in transcription start sites and splice isoforms during muscle development.
  • Lung fibroblast regulatory studies: Used to detect differential expression and splicing changes in lung fibroblasts in response to loss of the HOXA1 transcription factor.
  • Transcriptome dynamics and gene regulation: Enables comprehensive characterization of transcriptome dynamics and layers of gene expression regulation from RNA-Seq data.

Methodology:

Accepts aligned RNA-Seq reads, assembles them into a parsimonious transcript set, and estimates transcript abundances from read support; addresses reference annotation-based transcript assembly; performs differential analysis with Cuffdiff 2 controlling for replicate variability; and applies a likelihood-based correction for non-uniform cDNA fragment distribution due to library preparation.

Topics

Collections

Details

License:
BSL-1.0
Maturity:
Mature
Tool Type:
command-line tool, workflow
Operating Systems:
Linux, Mac
Programming Languages:
C++, C
Added:
1/13/2017
Last Updated:
11/24/2024

Operations

Data Inputs & Outputs

RNA-seq time series data analysis

Standardisation and normalisation

Other operations do not define inputs or outputs.

Publications

Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, Salzberg SL, Wold BJ, Pachter L. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nature Biotechnology. 2010;28(5):511-515. doi:10.1038/nbt.1621. PMID:20436464. PMCID:PMC3146043.

Roberts A, Pimentel H, Trapnell C, Pachter L. Identification of novel transcripts in annotated genomes using RNA-Seq. Bioinformatics. 2011;27(17):2325-2329. doi:10.1093/bioinformatics/btr355. PMID:21697122.

Trapnell C, Hendrickson DG, Sauvageau M, Goff L, Rinn JL, Pachter L. Differential analysis of gene regulation at transcript resolution with RNA-seq. Nature Biotechnology. 2012;31(1):46-53. doi:10.1038/nbt.2450. PMID:23222703. PMCID:PMC3869392.

Roberts A, Trapnell C, Donaghey J, Rinn JL, Pachter L. Improving RNA-Seq expression estimates by correcting for fragment bias. Genome Biology. 2011;12(3). doi:10.1186/gb-2011-12-3-r22. PMID:21410973. PMCID:PMC3129672.

Mareuil F, Doppelt-Azeroual O, Ménager H. A public Galaxy platform at Pasteur used as an execution engine for web services. Unknown Journal. 2017. doi:10.7490/f1000research.1114334.1.

Documentation

Links