- RNA software
- Gene Prediction Tools :
- DNA Structure Prediction Tools :
The Flux Capacitor predicts abundances for transcript molecules and alternative splicing events from RNAseq experiments. Additionally, there is a simulation pipeline that is capable to simulate whole transcriptome sequencing experiments.
- Visualization Tools :
- Gene Regulation Tools :
The Flux CapacitorAStalavista, the Alternative Splicing Trascriptional Landscape Visualization Tool and more, retrieves all alternative splicing events from generic transcript annotations.
sgp2 is a program to predict genes by comparing anonymous genomic sequences from different species. It combines tblastx, a sequence similarity search program, with geneid, an ab initio gene prediction program.
You will also find whole genome annotations for different species obtained with sgp2 in our "Gene Predictions" web pages.
geneid is a program to predict genes along a DNA sequence in a large set of organisms. While its accuracy compares favorably to that of other existing tools, geneid is more efficient in terms of speed and memory usage and it offers some rudimentary support to integrate predictions from multiple source.
You will also find whole genome annotations for different species obtained with geneid in our "Gene Predictions" web pages.
AcE is a program to aid gene prediction accuracy evaluation. It uses GFF format to make it easy to convert gene prediction results into an analyzable format. Novel features include isoform accuracy evaluation from either the annotated gene or gene prediction perspective or both at the same time. Masking of genomic sequence which has unknown features allows gene predictions in annotated regions to be analyzed in a genomic context. Test sets, such as an artificial sequence test set or genomic context test set, can be generated by selecting specified annotated sequences from a master set.
Obtaining plots to compare genomic sequences and/or sources from GFF files.
Last available version is 0.98. Get the PostScript version of "gff2ps Users Manual" (v0.96). A Web Server is also available at Institut Pasteur thanks to Catherine Letondal.
A new section has been created: HTML HOWTOs for gff2ps. The first two HOWTOs were also added: "Comparing sources with gff2ps" and "Visualizing PostScript output from gff2ps". We hope you will find them useful.
gff2ps was used to obtain the six chromosome arm plots (X, 2L, 2R, 3L, 3R and 4) appearing in the "Coding content of the fly genome" genome map (figure 4), included as a poster in "The Genome Sequence of Drosophila melanogaster" [Adams et al. Science 287(5461):2185-2195(2000)].
We have produced the map of the Human Genome with gff2ps. 22 autosomic, X and Y chromosomes were displayed in a big poster appearing as the figure 1 of "The Sequence of the Human Genome" [Venter et al. Science 291(5507):1304-1351 (2001)]. The single chromosome pictures can be accessed from here to visualize the web version of the "Annotation of the Celera Human Genome Assembly" poster.
gff2ps has achieved another genome landmark. The mosquito genome annotation for five chromosome arms (2L, 2R, 3L, 3R and X) has been summarized into a two-sided five-pages foldout included as the figure 1 of "The Genome Sequence of the Malaria Mosquito Anopheles gambiae" [Holt et al. Science 298(5591):129-149 (2002)], available from the "Annotation of the Anopheles gambiae genome sequence" web page.
Visualizing pair-wise alignments with annotated axes from GFF files.
We are proud to announce the new version of gff2aplot, that has been re-implemented in perl. Visit the program's web page downloading section to obtain v2.0. You can obtain the full distribution tarball from there.
Although the "gff2aplot User's Manual" is not finished yet, you can start using it as we have written several HTML tutorials that will introduce you in how to use this program. We hope you will enjoy them.
A snapshots web page is also available, listing few examples of what can be done with gff2aplot.
meta is a program to produce and to align the TF-maps of two gene promoter regions. meta is very useful to characterize promoter regions from orthologous genes, or from co-regulated genes in microarrays, as it reduces the signal/noise ratio in a very significant manner, still detecting the real functional sites.
mmeta is a program to produce and to align the TF-maps of multiple promoter regions. mmeta is very powerful to characterize promoter regions from multiple orthologous genes, or from co-regulated genes in microarrays, as it reduces the signal/noise ratio in a very significant manner, still detecting the real functional sites.