Description
JETTA is an integrated software tool for gene and exon expression calculation and alternative splicing analyses. It can be applied to the analysis and visualization of both exon-junction array and RNA-Seq data.
See more about JETTA
Updates
05/18/11: version 1.0.0
— Interfaces for RNA-Seq data was added.
10/07/10: version 0.6.0
— GUI was built, plotting asa output was enriched.
05/13/10: version 0.5.0
— some bugs were fixed, asa output was enriched
— we are almost ready to open
TODO List
- Supporting alterantive splicing analysis in a signle condition: see more about this.
- Supporting cross-hybridization model: see more about this.
- Extended GUI for RNA-Seq analysis: see “Calculating Alaternative Splicing Statistics” about this.
Instructions
How to run
How to compile
Expression indices calculation
Alternative splicing detection
R-script examples
JETTA GUI
JETTA for RNA-Seq
Downloads
Source Codes
Sample Parameter File
Command Line Application: WIN32 MAC(i386) MAC(x86_64) Linux(i386)
R packages: Windows MAC/Linux
GUI: JETTA GUI
View downloads stats
Microarray Libraries and Annotations
JETTA supports the GG-H arrays (Xu et al, PNAS, 2011) as well as all Affymetrix exon and exon-junction arrays for any species. Here, the libraries for some selected platforms are downloadable. For other Affymetrix platforms, the required library files for JETTA analyses (chip layout file, probe group file, TC meta probeset file and alternative spcliing structure file) will be available in Affymetrix wesite. For other third party arrays or custom arrays, feel free to contact us for supports.
Affymetrix Human Exon 1.0 Array
Affymetrix Mouse Exon 1.0 Array
Demonstrations
10/06/10: JETTA GUI Tutorial
05/18/11: Alternative splicing detection with human liver and muscle samples on Glue Grant arrays
05/19/11: Alternative splicing detection in RNA-Seq data of human liver and muscle tissue samples
Acknowledgements
The development and maintenance of JETTA is supported by NIH U54-GM062119 (to R.W.D., W.X. and W.W.), P01-HG000205 (to R.W.D.), and R01-HG004634 (to W.W. and Y.X.)
References
Seok J, Xu W, Gao H, Davis RW, Xiao W, JETTA: junction and exon toolkits for transcriptome analysis.Bioinformatics, 2012
Xu W, Seok J, Mindrinos MN, Schweitzer AC, Jiang H, Wilhelmy J, Clark TA, Kapur K, Xing Y, Faham M, Storey JD, Moldawer LL, Maier RV, Tompkins RG, Wong WH, Davis RW, Xiao W; Inflammation and Host Response to Injury Large-Scale Collaborative Research Program, Human transcriptome array for high-throughput clinical studies. PNAS, 2011
Liu S, Lin L, Jiang P, Wang D, Xing Y. A comparison of RNA-Seq and high-density exon array for detecting differential gene expression between closely related species. Nucleic Acids Res, 2011
Lin L, Liu S, Brockway H, Seok J, Jiang P, Wong WH, Xing Y. Using high-density exon arrays to profile gene expression in closely related species.Nucleic Acids Res. 2009
Kapur K, Jiang H, Xing Y, Wong WH. Cross-hybridization modeling on Affymetrix exon arrays. Bioinformatics, 2008
Xing Y, Stoilov P, Kapur K, Han A, Jiang H, Shen S, Black DL, Wong WH. MADS: a new and improved method for analysis of differential alternative splicing by exon-tiling microarrays. RNA, 2008
Kapur K, Xing Y, Ouyang Z, Wong WH. Exon arrays provide accurate assessments of gene expression. Genome Biol., 2007
Xing Y, Kapur K, Wong WH. Probe selection and expression index computation of Affymetrix Exon Arrays. PLoS One, 2006
Links
Glue Grant Data Interpretation Core
dChip
cisGenomeBrowser
Contact
Junhee Seok: jseok at stanford dot edu