Schema for SGP Genes - SGP Gene Predictions Using Mouse/Human Homology
  Database: hg38    Primary Table: sgpGene    Row Count: 36,030
Format description: A gene prediction with some additional info.
fieldexampleSQL type info description
bin 585smallint(5) unsigned range Indexing field to speed chromosome range queries.
name chr1_1.1varchar(255) values Name of gene (usually transcript_id from GTF)
chrom chr1varchar(255) values Reference sequence chromosome or scaffold
strand -char(1) values + or - for strand
txStart 14969int(10) unsigned range Transcription start position (or end position for minus strand item)
txEnd 15009int(10) unsigned range Transcription end position (or start position for minus strand item)
cdsStart 14969int(10) unsigned range Coding region start (or end position for minus strand item)
cdsEnd 15009int(10) unsigned range Coding region end (or start position for minus strand item)
exonCount 1int(10) unsigned range Number of exons
exonStarts 14969,longblob   Exon start positions (or end positions for minus strand item)
exonEnds 15009,longblob   Exon end positions (or start positions for minus strand item)
score 0int(11) range score
name2 chr1_1varchar(255) values Alternate name (e.g. gene_id from GTF)
cdsStartStat incmplenum('none', 'unk', 'incmpl', 'cmpl') values enum('none','unk','incmpl','cmpl')
cdsEndStat cmplenum('none', 'unk', 'incmpl', 'cmpl') values enum('none','unk','incmpl','cmpl')
exonFrames 0,longblob   Exon frame {0,1,2}, or -1 if no frame for exon

Sample Rows

Note: all start coordinates in our database are 0-based, not 1-based. See explanation here.

SGP Genes (sgpGene) Track Description


This track shows gene predictions from the SGP2 homology-based gene prediction program developed by Roderic Guigó's "Computational Biology of RNA Processing" group, which is part of the Centre de Regulació Genòmica (CRG) in Barcelona, Catalunya, Spain. To predict genes in a genomic query, SGP2 combines geneid predictions with tblastx comparisons of the genome of the target species against genomic sequences of other species (reference genomes) deemed to be at an appropriate evolutionary distance from the target.


Thanks to the "Computational Biology of RNA Processing" group for providing these data.