Schema for Geneid Genes - Geneid Gene Predictions
  Database: mm10    Primary Table: geneid    Row Count: 36,771   Data last updated: 2015-06-26
Format description: A gene prediction with some additional info.
On download server: MariaDB table dump directory
fieldexampleSQL type info description
bin 609smallint(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 3216021int(10) unsigned range Transcription start position (or end position for minus strand item)
txEnd 3226700int(10) unsigned range Transcription end position (or start position for minus strand item)
cdsStart 3216021int(10) unsigned range Coding region start (or end position for minus strand item)
cdsEnd 3226700int(10) unsigned range Coding region end (or start position for minus strand item)
exonCount 2int(10) unsigned range Number of exons
exonStarts 3216021,3226633,longblob   Exon start positions (or end positions for minus strand item)
exonEnds 3216968,3226700,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 cmplenum('none', 'unk', 'incmpl', 'cmpl') values Status of CDS start annotation (none, unknown, incomplete, or complete)
cdsEndStat cmplenum('none', 'unk', 'incmpl', 'cmpl') values Status of CDS end annotation (none, unknown, incomplete, or complete)
exonFrames 1,0,longblob   Reading frame of the start of the CDS region of the exon, in the direction of transcription (0,1,2), or -1 if there is no CDS region.

Sample Rows
 
binnamechromstrandtxStarttxEndcdsStartcdsEndexonCountexonStartsexonEndsscorename2cdsStartStatcdsEndStatexonFrames
609chr1_1.1chr1-321602132267003216021322670023216021,3226633,3216968,3226700,0chr1_1cmplcmpl1,0,
76chr1_2.1chr1-336631534316483366315343164843366315,3401410,3421701,3431490,3366478,3401438,3421901,3431648,0chr1_2cmplcmpl2,1,2,0,
76chr1_3.1chr1+353179435822273531794358222753531794,3531922,3532304,3553600,3582101,3531902,3532277,3532716,3553745,3582227,0chr1_3cmplcmpl0,0,1,2,0,
76chr1_4.1chr1-363751737298793637517372987953637517,3670551,3674518,3706173,3729866,3637764,3671049,3674537,3706200,3729879,0chr1_4cmplcmpl2,2,1,1,0,
9chr1_5.1chr1-3999556428488339995564284883223999556,4007655,4019069,4024735,4041887,4056161,4092616,4120014,4142611,4143170,4147811,4148653,4170204,4197533,4206659,4226610, ...3999617,4007737,4019148,4024890,4042107,4056278,4092780,4120073,4142905,4143238,4147963,4148744,4170404,4197641,4206837,4226934, ...0chr1_5cmplcmpl2,1,0,1,0,0,1,2,2,0,1,0,1,1,0,0,0,1,0,0,1,0,
618chr1_6.1chr1-434459943779984344599437799844344599,4351909,4352201,4377860,4350013,4352081,4352837,4377998,0chr1_6cmplcmpl1,0,0,0,
619chr1_7.1chr1-449171544934064491715449340624491715,4493099,4492668,4493406,0chr1_7cmplcmpl1,0,
619chr1_8.1chr1+449711945362114497119453621154497119,4522787,4524677,4525859,4536077,4497206,4523132,4525329,4526024,4536211,0chr1_8cmplcmpl0,0,0,1,1,
620chr1_9.1chr1+460338346108304603383461083024603383,4610506,4603464,4610830,0chr1_9cmplcmpl0,0,
620chr1_10.1chr1-468797546894044687975468940434687975,4688473,4689296,4688283,4689026,4689404,0chr1_10cmplcmpl1,0,0,

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

Geneid Genes (geneid) Track Description
 

Description

This track shows gene predictions from the geneid 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.

Methods

Geneid is a program to predict genes in anonymous genomic sequences designed with a hierarchical structure. In the first step, splice sites, start and stop codons are predicted and scored along the sequence using Position Weight Arrays (PWAs). Next, exons are built from the sites. Exons are scored as the sum of the scores of the defining sites, plus the the log-likelihood ratio of a Markov Model for coding DNA. Finally, from the set of predicted exons, the gene structure is assembled, maximizing the sum of the scores of the assembled exons.

Credits

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

References

Blanco E, Parra G, Guigó R. Using geneid to identify genes. Curr Protoc Bioinformatics. 2007 Jun;Chapter 4:Unit 4.3. PMID: 18428791

Parra G, Blanco E, Guigó R. GeneID in Drosophila. Genome Res. 2000 Apr;10(4):511-5. PMID: 10779490; PMC: PMC310871