RT Journal
A1 Florea, Liliana
A1 Di Francesco, Valentina
A1 Miller, Jason
A1 Turner, Russell
A1 Yao, Alison
A1 Harris, Michael
A1 Walenz, Brian
A1 Mobarry, Clark
A1 Merkulov, Gennady V.
A1 Charlab, Rosane
A1 Dew, Ian
A1 Deng, Zuoming
A1 Istrail, Sorin
A1 Li, Peter
A1 Sutton, Granger
T1 Gene and alternative splicing annotation with AIR
JF Genome Research 
JO Genome Research 
YR 2005 
FD January 01 
VO 15 
IS 1 
SP 54 
OP 66 
DO 10.1101/gr.2889405 
UL http://genome.cshlp.org/content/15/1/54.abstract 
AB Designing effective and accurate tools for identifying the functional and structural elements in a genome remains at the frontier of genome annotation owing to incompleteness and inaccuracy of the data, limitations in the computational models, and shifting paradigms in genomics, such as alternative splicing. We present a methodology for the automated annotation of genes and their alternatively spliced mRNA transcripts based on existing cDNA and protein sequence evidence from the same species or projected from a related species using syntenic mapping information. At the core of the method is the splice graph, a compact representation of a gene, its exons, introns, and alternatively spliced isoforms. The putative transcripts are enumerated from the graph and assigned confidence scores based on the strength of sequence evidence, and a subset of the high-scoring candidates are selected and promoted into the annotation. The method is highly selective, eliminating the unlikely candidates while retaining 98% of the high-quality mRNA evidence in well-formed transcripts, and produces annotation that is measurably more accurate than some evidence-based gene sets. The process is fast, accurate, and fully automated, and combines the traditionally distinct gene annotation and alternative splicing detection processes in a comprehensive and systematic way, thus considerably aiding in the ensuing manual curation efforts.