--------------------------------------------------------------- thaSir1.trackDb.html : Differences exist between hgwbeta and hgw2 (RR fields taken from public MySql server, not individual machine) 1926,1929d1925 < ncbiRefSeqGenomicDiff | html < ncbiRefSeqGenomicDiff | < ncbiRefSeqOther | html < ncbiRefSeqOther | 3072,3851d3067 < transMapEnsemblV5 | html < transMapEnsemblV5 |

Description

< transMapEnsemblV5 | < transMapEnsemblV5 |

< transMapEnsemblV5 | This track contains GENCODE or Ensembl alignments produced by < transMapEnsemblV5 | the TransMap cross-species alignment algorithm from other vertebrate < transMapEnsemblV5 | species in the UCSC Genome Browser. GENCODE is Ensembl for human and mouse, < transMapEnsemblV5 | for other Ensembl sources, only ones with full gene builds are used. < transMapEnsemblV5 | Projection Ensembl gene annotations will not be used as sources. < transMapEnsemblV5 | For closer evolutionary distances, the alignments are created using < transMapEnsemblV5 | syntenically filtered BLASTZ alignment chains, resulting in a prediction of the < transMapEnsemblV5 | orthologous genes in garter snake. < transMapEnsemblV5 |

< transMapEnsemblV5 | < transMapEnsemblV5 | < transMapEnsemblV5 |

Display Conventions and Configuration

< transMapEnsemblV5 | < transMapEnsemblV5 |

< transMapEnsemblV5 | This track follows the display conventions for < transMapEnsemblV5 | PSL alignment tracks.

< transMapEnsemblV5 |

< transMapEnsemblV5 | This track may also be configured to display codon coloring, a feature that < transMapEnsemblV5 | allows the user to quickly compare cDNAs against the genomic sequence. For more < transMapEnsemblV5 | information about this option, click < transMapEnsemblV5 | here. < transMapEnsemblV5 | Several types of alignment gap may also be colored; < transMapEnsemblV5 | for more information, click < transMapEnsemblV5 | here. < transMapEnsemblV5 | < transMapEnsemblV5 |

Methods

< transMapEnsemblV5 | < transMapEnsemblV5 |

< transMapEnsemblV5 |

    < transMapEnsemblV5 |
  1. Source transcript alignments were obtained from vertebrate organisms < transMapEnsemblV5 | in the UCSC Genome Browser Database. BLAT alignments of RefSeq Genes, GenBank < transMapEnsemblV5 | mRNAs, and GenBank Spliced ESTs to the cognate genome, along with UCSC Genes, < transMapEnsemblV5 | were used as available. < transMapEnsemblV5 |
  2. For all vertebrate assemblies that had BLASTZ alignment chains and < transMapEnsemblV5 | nets to the garter snake (thaSir1) genome, a subset of the alignment chains were < transMapEnsemblV5 | selected as follows: < transMapEnsemblV5 | < transMapEnsemblV5 |
  3. The pslMap program was used to do a base-level projection of < transMapEnsemblV5 | the source transcript alignments via the selected chains < transMapEnsemblV5 | to the garter snake genome, resulting in pairwise alignments of the source transcripts to < transMapEnsemblV5 | the genome. < transMapEnsemblV5 |
  4. The resulting alignments were filtered with pslCDnaFilter < transMapEnsemblV5 | with a global near-best criteria of 0.5% in finished genomes < transMapEnsemblV5 | (human and mouse) and 1.0% in other genomes. Alignments < transMapEnsemblV5 | where less than 20% of the transcript mapped were discarded. < transMapEnsemblV5 |
< transMapEnsemblV5 |

< transMapEnsemblV5 | < transMapEnsemblV5 |

< transMapEnsemblV5 | To ensure unique identifiers for each alignment, cDNA and gene accessions were < transMapEnsemblV5 | made unique by appending a suffix for each location in the source genome and < transMapEnsemblV5 | again for each mapped location in the destination genome. The format is: < transMapEnsemblV5 | 

< transMapEnsemblV5 |    accession.version-srcUniq.destUniq
< transMapEnsemblV5 |
< transMapEnsemblV5 | < transMapEnsemblV5 | Where srcUniq is a number added to make each source alignment unique, and < transMapEnsemblV5 | destUniq is added to give the subsequent TransMap alignments unique < transMapEnsemblV5 | identifiers. < transMapEnsemblV5 |

< transMapEnsemblV5 |

< transMapEnsemblV5 | For example, in the cow genome, there are two alignments of mRNA BC149621.1. < transMapEnsemblV5 | These are assigned the identifiers BC149621.1-1 and BC149621.1-2. < transMapEnsemblV5 | When these are mapped to the human genome, BC149621.1-1 maps to a single < transMapEnsemblV5 | location and is given the identifier BC149621.1-1.1. However, BC149621.1-2 < transMapEnsemblV5 | maps to two locations, resulting in BC149621.1-2.1 and BC149621.1-2.2. Note < transMapEnsemblV5 | that multiple TransMap mappings are usually the result of tandem duplications, where both < transMapEnsemblV5 | chains are identified as syntenic. < transMapEnsemblV5 |

< transMapEnsemblV5 | < transMapEnsemblV5 |

Data Access

< transMapEnsemblV5 | < transMapEnsemblV5 |

< transMapEnsemblV5 | The raw data for these tracks can be accessed interactively through the < transMapEnsemblV5 | Table Browser or the < transMapEnsemblV5 | Data Integrator. < transMapEnsemblV5 | For automated analysis, the annotations are stored in < transMapEnsemblV5 | bigPsl files (containing a < transMapEnsemblV5 | number of extra columns) and can be downloaded from our < transMapEnsemblV5 | download server, < transMapEnsemblV5 | or queried using our API. For more < transMapEnsemblV5 | information on accessing track data see our < transMapEnsemblV5 | Track Data Access FAQ. < transMapEnsemblV5 | The files are associated with these tracks in the following way: < transMapEnsemblV5 |

< transMapEnsemblV5 | Individual regions or the whole genome annotation can be obtained using our tool < transMapEnsemblV5 | bigBedToBed which can be compiled from the source code or downloaded as < transMapEnsemblV5 | a precompiled binary for your system. Instructions for downloading source code and < transMapEnsemblV5 | binaries can be found < transMapEnsemblV5 | here. < transMapEnsemblV5 | The tool can also be used to obtain only features within a given range, for example: < transMapEnsemblV5 |

< transMapEnsemblV5 | bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/thaSir1/transMap/V4/thaSir1.refseq.transMapV4.bigPsl < transMapEnsemblV5 | -chrom=chr6 -start=0 -end=1000000 stdout < transMapEnsemblV5 | < transMapEnsemblV5 | < transMapEnsemblV5 |

Credits

< transMapEnsemblV5 | < transMapEnsemblV5 |

< transMapEnsemblV5 | This track was produced by Mark Diekhans at UCSC from cDNA and EST sequence data < transMapEnsemblV5 | submitted to the international public sequence databases by < transMapEnsemblV5 | scientists worldwide and annotations produced by the RefSeq, < transMapEnsemblV5 | Ensembl, and GENCODE annotations projects.

< transMapEnsemblV5 | < transMapEnsemblV5 |

References

< transMapEnsemblV5 |

< transMapEnsemblV5 | Siepel A, Diekhans M, Brejová B, Langton L, Stevens M, Comstock CL, Davis C, Ewing B, Oommen S, < transMapEnsemblV5 | Lau C et al. < transMapEnsemblV5 | < transMapEnsemblV5 | Targeted discovery of novel human exons by comparative genomics. < transMapEnsemblV5 | Genome Res. 2007 Dec;17(12):1763-73. < transMapEnsemblV5 | PMID: 17989246; PMC: PMC2099585 < transMapEnsemblV5 |

< transMapEnsemblV5 | < transMapEnsemblV5 |

< transMapEnsemblV5 | Stanke M, Diekhans M, Baertsch R, Haussler D. < transMapEnsemblV5 | < transMapEnsemblV5 | Using native and syntenically mapped cDNA alignments to improve de novo gene finding. < transMapEnsemblV5 | Bioinformatics. 2008 Mar 1;24(5):637-44. < transMapEnsemblV5 | PMID: 18218656 < transMapEnsemblV5 |

< transMapEnsemblV5 | < transMapEnsemblV5 |

< transMapEnsemblV5 | Zhu J, Sanborn JZ, Diekhans M, Lowe CB, Pringle TH, Haussler D. < transMapEnsemblV5 | < transMapEnsemblV5 | Comparative genomics search for losses of long-established genes on the human lineage. < transMapEnsemblV5 | PLoS Comput Biol. 2007 Dec;3(12):e247. < transMapEnsemblV5 | PMID: 18085818; PMC: PMC2134963 < transMapEnsemblV5 |

< transMapEnsemblV5 | < transMapEnsemblV5 | < transMapEstV5 | html < transMapEstV5 |

Description

< transMapEstV5 | < transMapEstV5 |

< transMapEstV5 | This track contains GenBank spliced EST alignments produced by < transMapEstV5 | the TransMap cross-species alignment algorithm < transMapEstV5 | from other vertebrate species in the UCSC Genome Browser. < transMapEstV5 | For closer evolutionary distances, the alignments are created using < transMapEstV5 | syntenically filtered BLASTZ alignment chains, resulting in a prediction of the < transMapEstV5 | orthologous genes in garter snake. < transMapEstV5 |

< transMapEstV5 | < transMapEstV5 | < transMapEstV5 |

Display Conventions and Configuration

< transMapEstV5 | < transMapEstV5 |

< transMapEstV5 | This track follows the display conventions for < transMapEstV5 | PSL alignment tracks.

< transMapEstV5 |

< transMapEstV5 | This track may also be configured to display codon coloring, a feature that < transMapEstV5 | allows the user to quickly compare cDNAs against the genomic sequence. For more < transMapEstV5 | information about this option, click < transMapEstV5 | here. < transMapEstV5 | Several types of alignment gap may also be colored; < transMapEstV5 | for more information, click < transMapEstV5 | here. < transMapEstV5 | < transMapEstV5 |

Methods

< transMapEstV5 | < transMapEstV5 |

< transMapEstV5 |

    < transMapEstV5 |
  1. Source transcript alignments were obtained from vertebrate organisms < transMapEstV5 | in the UCSC Genome Browser Database. BLAT alignments of RefSeq Genes, GenBank < transMapEstV5 | mRNAs, and GenBank Spliced ESTs to the cognate genome, along with UCSC Genes, < transMapEstV5 | were used as available. < transMapEstV5 |
  2. For all vertebrate assemblies that had BLASTZ alignment chains and < transMapEstV5 | nets to the garter snake (thaSir1) genome, a subset of the alignment chains were < transMapEstV5 | selected as follows: < transMapEstV5 | < transMapEstV5 |
  3. The pslMap program was used to do a base-level projection of < transMapEstV5 | the source transcript alignments via the selected chains < transMapEstV5 | to the garter snake genome, resulting in pairwise alignments of the source transcripts to < transMapEstV5 | the genome. < transMapEstV5 |
  4. The resulting alignments were filtered with pslCDnaFilter < transMapEstV5 | with a global near-best criteria of 0.5% in finished genomes < transMapEstV5 | (human and mouse) and 1.0% in other genomes. Alignments < transMapEstV5 | where less than 20% of the transcript mapped were discarded. < transMapEstV5 |
< transMapEstV5 |

< transMapEstV5 | < transMapEstV5 |

< transMapEstV5 | To ensure unique identifiers for each alignment, cDNA and gene accessions were < transMapEstV5 | made unique by appending a suffix for each location in the source genome and < transMapEstV5 | again for each mapped location in the destination genome. The format is: < transMapEstV5 | 

< transMapEstV5 |    accession.version-srcUniq.destUniq
< transMapEstV5 |
< transMapEstV5 | < transMapEstV5 | Where srcUniq is a number added to make each source alignment unique, and < transMapEstV5 | destUniq is added to give the subsequent TransMap alignments unique < transMapEstV5 | identifiers. < transMapEstV5 |

< transMapEstV5 |

< transMapEstV5 | For example, in the cow genome, there are two alignments of mRNA BC149621.1. < transMapEstV5 | These are assigned the identifiers BC149621.1-1 and BC149621.1-2. < transMapEstV5 | When these are mapped to the human genome, BC149621.1-1 maps to a single < transMapEstV5 | location and is given the identifier BC149621.1-1.1. However, BC149621.1-2 < transMapEstV5 | maps to two locations, resulting in BC149621.1-2.1 and BC149621.1-2.2. Note < transMapEstV5 | that multiple TransMap mappings are usually the result of tandem duplications, where both < transMapEstV5 | chains are identified as syntenic. < transMapEstV5 |

< transMapEstV5 | < transMapEstV5 |

Data Access

< transMapEstV5 | < transMapEstV5 |

< transMapEstV5 | The raw data for these tracks can be accessed interactively through the < transMapEstV5 | Table Browser or the < transMapEstV5 | Data Integrator. < transMapEstV5 | For automated analysis, the annotations are stored in < transMapEstV5 | bigPsl files (containing a < transMapEstV5 | number of extra columns) and can be downloaded from our < transMapEstV5 | download server, < transMapEstV5 | or queried using our API. For more < transMapEstV5 | information on accessing track data see our < transMapEstV5 | Track Data Access FAQ. < transMapEstV5 | The files are associated with these tracks in the following way: < transMapEstV5 |

< transMapEstV5 | Individual regions or the whole genome annotation can be obtained using our tool < transMapEstV5 | bigBedToBed which can be compiled from the source code or downloaded as < transMapEstV5 | a precompiled binary for your system. Instructions for downloading source code and < transMapEstV5 | binaries can be found < transMapEstV5 | here. < transMapEstV5 | The tool can also be used to obtain only features within a given range, for example: < transMapEstV5 |

< transMapEstV5 | bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/thaSir1/transMap/V4/thaSir1.refseq.transMapV4.bigPsl < transMapEstV5 | -chrom=chr6 -start=0 -end=1000000 stdout < transMapEstV5 | < transMapEstV5 | < transMapEstV5 |

Credits

< transMapEstV5 | < transMapEstV5 |

< transMapEstV5 | This track was produced by Mark Diekhans at UCSC from cDNA and EST sequence data < transMapEstV5 | submitted to the international public sequence databases by < transMapEstV5 | scientists worldwide and annotations produced by the RefSeq, < transMapEstV5 | Ensembl, and GENCODE annotations projects.

< transMapEstV5 | < transMapEstV5 |

References

< transMapEstV5 |

< transMapEstV5 | Siepel A, Diekhans M, Brejová B, Langton L, Stevens M, Comstock CL, Davis C, Ewing B, Oommen S, < transMapEstV5 | Lau C et al. < transMapEstV5 | < transMapEstV5 | Targeted discovery of novel human exons by comparative genomics. < transMapEstV5 | Genome Res. 2007 Dec;17(12):1763-73. < transMapEstV5 | PMID: 17989246; PMC: PMC2099585 < transMapEstV5 |

< transMapEstV5 | < transMapEstV5 |

< transMapEstV5 | Stanke M, Diekhans M, Baertsch R, Haussler D. < transMapEstV5 | < transMapEstV5 | Using native and syntenically mapped cDNA alignments to improve de novo gene finding. < transMapEstV5 | Bioinformatics. 2008 Mar 1;24(5):637-44. < transMapEstV5 | PMID: 18218656 < transMapEstV5 |

< transMapEstV5 | < transMapEstV5 |

< transMapEstV5 | Zhu J, Sanborn JZ, Diekhans M, Lowe CB, Pringle TH, Haussler D. < transMapEstV5 | < transMapEstV5 | Comparative genomics search for losses of long-established genes on the human lineage. < transMapEstV5 | PLoS Comput Biol. 2007 Dec;3(12):e247. < transMapEstV5 | PMID: 18085818; PMC: PMC2134963 < transMapEstV5 |

< transMapEstV5 | < transMapEstV5 | < transMapRefSeqV5 | html < transMapRefSeqV5 |

Description

< transMapRefSeqV5 | < transMapRefSeqV5 |

< transMapRefSeqV5 | This track contains RefSeq Gene alignments produced by < transMapRefSeqV5 | the TransMap cross-species alignment algorithm < transMapRefSeqV5 | from other vertebrate species in the UCSC Genome Browser. < transMapRefSeqV5 | For closer evolutionary distances, the alignments are created using < transMapRefSeqV5 | syntenically filtered BLASTZ alignment chains, resulting in a prediction of the < transMapRefSeqV5 | orthologous genes in garter snake. < transMapRefSeqV5 |

< transMapRefSeqV5 | < transMapRefSeqV5 | < transMapRefSeqV5 |

Display Conventions and Configuration

< transMapRefSeqV5 | < transMapRefSeqV5 |

< transMapRefSeqV5 | This track follows the display conventions for < transMapRefSeqV5 | PSL alignment tracks.

< transMapRefSeqV5 |

< transMapRefSeqV5 | This track may also be configured to display codon coloring, a feature that < transMapRefSeqV5 | allows the user to quickly compare cDNAs against the genomic sequence. For more < transMapRefSeqV5 | information about this option, click < transMapRefSeqV5 | here. < transMapRefSeqV5 | Several types of alignment gap may also be colored; < transMapRefSeqV5 | for more information, click < transMapRefSeqV5 | here. < transMapRefSeqV5 | < transMapRefSeqV5 |

Methods

< transMapRefSeqV5 | < transMapRefSeqV5 |

< transMapRefSeqV5 |

    < transMapRefSeqV5 |
  1. Source transcript alignments were obtained from vertebrate organisms < transMapRefSeqV5 | in the UCSC Genome Browser Database. BLAT alignments of RefSeq Genes, GenBank < transMapRefSeqV5 | mRNAs, and GenBank Spliced ESTs to the cognate genome, along with UCSC Genes, < transMapRefSeqV5 | were used as available. < transMapRefSeqV5 |
  2. For all vertebrate assemblies that had BLASTZ alignment chains and < transMapRefSeqV5 | nets to the garter snake (thaSir1) genome, a subset of the alignment chains were < transMapRefSeqV5 | selected as follows: < transMapRefSeqV5 | < transMapRefSeqV5 |
  3. The pslMap program was used to do a base-level projection of < transMapRefSeqV5 | the source transcript alignments via the selected chains < transMapRefSeqV5 | to the garter snake genome, resulting in pairwise alignments of the source transcripts to < transMapRefSeqV5 | the genome. < transMapRefSeqV5 |
  4. The resulting alignments were filtered with pslCDnaFilter < transMapRefSeqV5 | with a global near-best criteria of 0.5% in finished genomes < transMapRefSeqV5 | (human and mouse) and 1.0% in other genomes. Alignments < transMapRefSeqV5 | where less than 20% of the transcript mapped were discarded. < transMapRefSeqV5 |
< transMapRefSeqV5 |

< transMapRefSeqV5 | < transMapRefSeqV5 |

< transMapRefSeqV5 | To ensure unique identifiers for each alignment, cDNA and gene accessions were < transMapRefSeqV5 | made unique by appending a suffix for each location in the source genome and < transMapRefSeqV5 | again for each mapped location in the destination genome. The format is: < transMapRefSeqV5 | 

< transMapRefSeqV5 |    accession.version-srcUniq.destUniq
< transMapRefSeqV5 |
< transMapRefSeqV5 | < transMapRefSeqV5 | Where srcUniq is a number added to make each source alignment unique, and < transMapRefSeqV5 | destUniq is added to give the subsequent TransMap alignments unique < transMapRefSeqV5 | identifiers. < transMapRefSeqV5 |

< transMapRefSeqV5 |

< transMapRefSeqV5 | For example, in the cow genome, there are two alignments of mRNA BC149621.1. < transMapRefSeqV5 | These are assigned the identifiers BC149621.1-1 and BC149621.1-2. < transMapRefSeqV5 | When these are mapped to the human genome, BC149621.1-1 maps to a single < transMapRefSeqV5 | location and is given the identifier BC149621.1-1.1. However, BC149621.1-2 < transMapRefSeqV5 | maps to two locations, resulting in BC149621.1-2.1 and BC149621.1-2.2. Note < transMapRefSeqV5 | that multiple TransMap mappings are usually the result of tandem duplications, where both < transMapRefSeqV5 | chains are identified as syntenic. < transMapRefSeqV5 |

< transMapRefSeqV5 | < transMapRefSeqV5 |

Data Access

< transMapRefSeqV5 | < transMapRefSeqV5 |

< transMapRefSeqV5 | The raw data for these tracks can be accessed interactively through the < transMapRefSeqV5 | Table Browser or the < transMapRefSeqV5 | Data Integrator. < transMapRefSeqV5 | For automated analysis, the annotations are stored in < transMapRefSeqV5 | bigPsl files (containing a < transMapRefSeqV5 | number of extra columns) and can be downloaded from our < transMapRefSeqV5 | download server, < transMapRefSeqV5 | or queried using our API. For more < transMapRefSeqV5 | information on accessing track data see our < transMapRefSeqV5 | Track Data Access FAQ. < transMapRefSeqV5 | The files are associated with these tracks in the following way: < transMapRefSeqV5 |

< transMapRefSeqV5 | Individual regions or the whole genome annotation can be obtained using our tool < transMapRefSeqV5 | bigBedToBed which can be compiled from the source code or downloaded as < transMapRefSeqV5 | a precompiled binary for your system. Instructions for downloading source code and < transMapRefSeqV5 | binaries can be found < transMapRefSeqV5 | here. < transMapRefSeqV5 | The tool can also be used to obtain only features within a given range, for example: < transMapRefSeqV5 |

< transMapRefSeqV5 | bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/thaSir1/transMap/V4/thaSir1.refseq.transMapV4.bigPsl < transMapRefSeqV5 | -chrom=chr6 -start=0 -end=1000000 stdout < transMapRefSeqV5 | < transMapRefSeqV5 | < transMapRefSeqV5 |

Credits

< transMapRefSeqV5 | < transMapRefSeqV5 |

< transMapRefSeqV5 | This track was produced by Mark Diekhans at UCSC from cDNA and EST sequence data < transMapRefSeqV5 | submitted to the international public sequence databases by < transMapRefSeqV5 | scientists worldwide and annotations produced by the RefSeq, < transMapRefSeqV5 | Ensembl, and GENCODE annotations projects.

< transMapRefSeqV5 | < transMapRefSeqV5 |

References

< transMapRefSeqV5 |

< transMapRefSeqV5 | Siepel A, Diekhans M, Brejová B, Langton L, Stevens M, Comstock CL, Davis C, Ewing B, Oommen S, < transMapRefSeqV5 | Lau C et al. < transMapRefSeqV5 | < transMapRefSeqV5 | Targeted discovery of novel human exons by comparative genomics. < transMapRefSeqV5 | Genome Res. 2007 Dec;17(12):1763-73. < transMapRefSeqV5 | PMID: 17989246; PMC: PMC2099585 < transMapRefSeqV5 |

< transMapRefSeqV5 | < transMapRefSeqV5 |

< transMapRefSeqV5 | Stanke M, Diekhans M, Baertsch R, Haussler D. < transMapRefSeqV5 | < transMapRefSeqV5 | Using native and syntenically mapped cDNA alignments to improve de novo gene finding. < transMapRefSeqV5 | Bioinformatics. 2008 Mar 1;24(5):637-44. < transMapRefSeqV5 | PMID: 18218656 < transMapRefSeqV5 |

< transMapRefSeqV5 | < transMapRefSeqV5 |

< transMapRefSeqV5 | Zhu J, Sanborn JZ, Diekhans M, Lowe CB, Pringle TH, Haussler D. < transMapRefSeqV5 | < transMapRefSeqV5 | Comparative genomics search for losses of long-established genes on the human lineage. < transMapRefSeqV5 | PLoS Comput Biol. 2007 Dec;3(12):e247. < transMapRefSeqV5 | PMID: 18085818; PMC: PMC2134963 < transMapRefSeqV5 |

< transMapRefSeqV5 | < transMapRefSeqV5 | < transMapRnaV5 | html < transMapRnaV5 |

Description

< transMapRnaV5 | < transMapRnaV5 |

< transMapRnaV5 | This track contains GenBank mRNA alignments produced by < transMapRnaV5 | the TransMap cross-species alignment algorithm < transMapRnaV5 | from other vertebrate species in the UCSC Genome Browser. < transMapRnaV5 | For closer evolutionary distances, the alignments are created using < transMapRnaV5 | syntenically filtered BLASTZ alignment chains, resulting in a prediction of the < transMapRnaV5 | orthologous genes in garter snake. < transMapRnaV5 |

< transMapRnaV5 | < transMapRnaV5 | < transMapRnaV5 |

Display Conventions and Configuration

< transMapRnaV5 | < transMapRnaV5 |

< transMapRnaV5 | This track follows the display conventions for < transMapRnaV5 | PSL alignment tracks.

< transMapRnaV5 |

< transMapRnaV5 | This track may also be configured to display codon coloring, a feature that < transMapRnaV5 | allows the user to quickly compare cDNAs against the genomic sequence. For more < transMapRnaV5 | information about this option, click < transMapRnaV5 | here. < transMapRnaV5 | Several types of alignment gap may also be colored; < transMapRnaV5 | for more information, click < transMapRnaV5 | here. < transMapRnaV5 | < transMapRnaV5 |

Methods

< transMapRnaV5 | < transMapRnaV5 |

< transMapRnaV5 |

    < transMapRnaV5 |
  1. Source transcript alignments were obtained from vertebrate organisms < transMapRnaV5 | in the UCSC Genome Browser Database. BLAT alignments of RefSeq Genes, GenBank < transMapRnaV5 | mRNAs, and GenBank Spliced ESTs to the cognate genome, along with UCSC Genes, < transMapRnaV5 | were used as available. < transMapRnaV5 |
  2. For all vertebrate assemblies that had BLASTZ alignment chains and < transMapRnaV5 | nets to the garter snake (thaSir1) genome, a subset of the alignment chains were < transMapRnaV5 | selected as follows: < transMapRnaV5 | < transMapRnaV5 |
  3. The pslMap program was used to do a base-level projection of < transMapRnaV5 | the source transcript alignments via the selected chains < transMapRnaV5 | to the garter snake genome, resulting in pairwise alignments of the source transcripts to < transMapRnaV5 | the genome. < transMapRnaV5 |
  4. The resulting alignments were filtered with pslCDnaFilter < transMapRnaV5 | with a global near-best criteria of 0.5% in finished genomes < transMapRnaV5 | (human and mouse) and 1.0% in other genomes. Alignments < transMapRnaV5 | where less than 20% of the transcript mapped were discarded. < transMapRnaV5 |
< transMapRnaV5 |

< transMapRnaV5 | < transMapRnaV5 |

< transMapRnaV5 | To ensure unique identifiers for each alignment, cDNA and gene accessions were < transMapRnaV5 | made unique by appending a suffix for each location in the source genome and < transMapRnaV5 | again for each mapped location in the destination genome. The format is: < transMapRnaV5 | 

< transMapRnaV5 |    accession.version-srcUniq.destUniq
< transMapRnaV5 |
< transMapRnaV5 | < transMapRnaV5 | Where srcUniq is a number added to make each source alignment unique, and < transMapRnaV5 | destUniq is added to give the subsequent TransMap alignments unique < transMapRnaV5 | identifiers. < transMapRnaV5 |

< transMapRnaV5 |

< transMapRnaV5 | For example, in the cow genome, there are two alignments of mRNA BC149621.1. < transMapRnaV5 | These are assigned the identifiers BC149621.1-1 and BC149621.1-2. < transMapRnaV5 | When these are mapped to the human genome, BC149621.1-1 maps to a single < transMapRnaV5 | location and is given the identifier BC149621.1-1.1. However, BC149621.1-2 < transMapRnaV5 | maps to two locations, resulting in BC149621.1-2.1 and BC149621.1-2.2. Note < transMapRnaV5 | that multiple TransMap mappings are usually the result of tandem duplications, where both < transMapRnaV5 | chains are identified as syntenic. < transMapRnaV5 |

< transMapRnaV5 | < transMapRnaV5 |

Data Access

< transMapRnaV5 | < transMapRnaV5 |

< transMapRnaV5 | The raw data for these tracks can be accessed interactively through the < transMapRnaV5 | Table Browser or the < transMapRnaV5 | Data Integrator. < transMapRnaV5 | For automated analysis, the annotations are stored in < transMapRnaV5 | bigPsl files (containing a < transMapRnaV5 | number of extra columns) and can be downloaded from our < transMapRnaV5 | download server, < transMapRnaV5 | or queried using our API. For more < transMapRnaV5 | information on accessing track data see our < transMapRnaV5 | Track Data Access FAQ. < transMapRnaV5 | The files are associated with these tracks in the following way: < transMapRnaV5 |

< transMapRnaV5 | Individual regions or the whole genome annotation can be obtained using our tool < transMapRnaV5 | bigBedToBed which can be compiled from the source code or downloaded as < transMapRnaV5 | a precompiled binary for your system. Instructions for downloading source code and < transMapRnaV5 | binaries can be found < transMapRnaV5 | here. < transMapRnaV5 | The tool can also be used to obtain only features within a given range, for example: < transMapRnaV5 |

< transMapRnaV5 | bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/thaSir1/transMap/V4/thaSir1.refseq.transMapV4.bigPsl < transMapRnaV5 | -chrom=chr6 -start=0 -end=1000000 stdout < transMapRnaV5 | < transMapRnaV5 | < transMapRnaV5 |

Credits

< transMapRnaV5 | < transMapRnaV5 |

< transMapRnaV5 | This track was produced by Mark Diekhans at UCSC from cDNA and EST sequence data < transMapRnaV5 | submitted to the international public sequence databases by < transMapRnaV5 | scientists worldwide and annotations produced by the RefSeq, < transMapRnaV5 | Ensembl, and GENCODE annotations projects.

< transMapRnaV5 | < transMapRnaV5 |

References

< transMapRnaV5 |

< transMapRnaV5 | Siepel A, Diekhans M, Brejová B, Langton L, Stevens M, Comstock CL, Davis C, Ewing B, Oommen S, < transMapRnaV5 | Lau C et al. < transMapRnaV5 | < transMapRnaV5 | Targeted discovery of novel human exons by comparative genomics. < transMapRnaV5 | Genome Res. 2007 Dec;17(12):1763-73. < transMapRnaV5 | PMID: 17989246; PMC: PMC2099585 < transMapRnaV5 |

< transMapRnaV5 | < transMapRnaV5 |

< transMapRnaV5 | Stanke M, Diekhans M, Baertsch R, Haussler D. < transMapRnaV5 | < transMapRnaV5 | Using native and syntenically mapped cDNA alignments to improve de novo gene finding. < transMapRnaV5 | Bioinformatics. 2008 Mar 1;24(5):637-44. < transMapRnaV5 | PMID: 18218656 < transMapRnaV5 |

< transMapRnaV5 | < transMapRnaV5 |

< transMapRnaV5 | Zhu J, Sanborn JZ, Diekhans M, Lowe CB, Pringle TH, Haussler D. < transMapRnaV5 | < transMapRnaV5 | Comparative genomics search for losses of long-established genes on the human lineage. < transMapRnaV5 | PLoS Comput Biol. 2007 Dec;3(12):e247. < transMapRnaV5 | PMID: 18085818; PMC: PMC2134963 < transMapRnaV5 |

< transMapRnaV5 | < transMapRnaV5 | < transMapV5 | html < transMapV5 |

Description

< transMapV5 | < transMapV5 |

< transMapV5 | These tracks contain cDNA and gene alignments produced by < transMapV5 | the TransMap cross-species alignment algorithm < transMapV5 | from other vertebrate species in the UCSC Genome Browser. < transMapV5 | For closer evolutionary distances, the alignments are created using < transMapV5 | syntenically filtered LASTZ or BLASTZ alignment chains, resulting < transMapV5 | in a prediction of the orthologous genes in garter snake. For more distant < transMapV5 | organisms, reciprocal best alignments are used. < transMapV5 |

< transMapV5 | < transMapV5 | TransMap maps genes and related annotations in one species to another < transMapV5 | using synteny-filtered pairwise genome alignments (chains and nets) to < transMapV5 | determine the most likely orthologs. For example, for the mRNA TransMap track < transMapV5 | on the human assembly, more than 400,000 mRNAs from 25 vertebrate species were < transMapV5 | aligned at high stringency to the native assembly using BLAT. The alignments < transMapV5 | were then mapped to the human assembly using the chain and net alignments < transMapV5 | produced using BLASTZ, which has higher sensitivity than BLAT for diverged < transMapV5 | organisms. < transMapV5 |

< transMapV5 | Compared to translated BLAT, TransMap finds fewer paralogs and aligns more UTR < transMapV5 | bases. < transMapV5 |

< transMapV5 | < transMapV5 |

Display Conventions and Configuration

< transMapV5 | < transMapV5 |

< transMapV5 | This track follows the display conventions for < transMapV5 | PSL alignment tracks.

< transMapV5 |

< transMapV5 | This track may also be configured to display codon coloring, a feature that < transMapV5 | allows the user to quickly compare cDNAs against the genomic sequence. For more < transMapV5 | information about this option, click < transMapV5 | here. < transMapV5 | Several types of alignment gap may also be colored; < transMapV5 | for more information, click < transMapV5 | here. < transMapV5 | < transMapV5 |

Methods

< transMapV5 | < transMapV5 |

< transMapV5 |

    < transMapV5 |
  1. Source transcript alignments were obtained from vertebrate organisms < transMapV5 | in the UCSC Genome Browser Database. BLAT alignments of RefSeq Genes, GenBank < transMapV5 | mRNAs, and GenBank Spliced ESTs to the cognate genome, along with UCSC Genes, < transMapV5 | were used as available. < transMapV5 |
  2. For all vertebrate assemblies that had BLASTZ alignment chains and < transMapV5 | nets to the garter snake (thaSir1) genome, a subset of the alignment chains were < transMapV5 | selected as follows: < transMapV5 | < transMapV5 |
  3. The pslMap program was used to do a base-level projection of < transMapV5 | the source transcript alignments via the selected chains < transMapV5 | to the garter snake genome, resulting in pairwise alignments of the source transcripts to < transMapV5 | the genome. < transMapV5 |
  4. The resulting alignments were filtered with pslCDnaFilter < transMapV5 | with a global near-best criteria of 0.5% in finished genomes < transMapV5 | (human and mouse) and 1.0% in other genomes. Alignments < transMapV5 | where less than 20% of the transcript mapped were discarded. < transMapV5 |
< transMapV5 |

< transMapV5 | < transMapV5 |

< transMapV5 | To ensure unique identifiers for each alignment, cDNA and gene accessions were < transMapV5 | made unique by appending a suffix for each location in the source genome and < transMapV5 | again for each mapped location in the destination genome. The format is: < transMapV5 | 

< transMapV5 |    accession.version-srcUniq.destUniq
< transMapV5 |
< transMapV5 | < transMapV5 | Where srcUniq is a number added to make each source alignment unique, and < transMapV5 | destUniq is added to give the subsequent TransMap alignments unique < transMapV5 | identifiers. < transMapV5 |

< transMapV5 |

< transMapV5 | For example, in the cow genome, there are two alignments of mRNA BC149621.1. < transMapV5 | These are assigned the identifiers BC149621.1-1 and BC149621.1-2. < transMapV5 | When these are mapped to the human genome, BC149621.1-1 maps to a single < transMapV5 | location and is given the identifier BC149621.1-1.1. However, BC149621.1-2 < transMapV5 | maps to two locations, resulting in BC149621.1-2.1 and BC149621.1-2.2. Note < transMapV5 | that multiple TransMap mappings are usually the result of tandem duplications, where both < transMapV5 | chains are identified as syntenic. < transMapV5 |

< transMapV5 | < transMapV5 |

Data Access

< transMapV5 | < transMapV5 |

< transMapV5 | The raw data for these tracks can be accessed interactively through the < transMapV5 | Table Browser or the < transMapV5 | Data Integrator. < transMapV5 | For automated analysis, the annotations are stored in < transMapV5 | bigPsl files (containing a < transMapV5 | number of extra columns) and can be downloaded from our < transMapV5 | download server, < transMapV5 | or queried using our API. For more < transMapV5 | information on accessing track data see our < transMapV5 | Track Data Access FAQ. < transMapV5 | The files are associated with these tracks in the following way: < transMapV5 |

< transMapV5 | Individual regions or the whole genome annotation can be obtained using our tool < transMapV5 | bigBedToBed, which can be compiled from the source code or downloaded as < transMapV5 | a precompiled binary for your system. Instructions for downloading source code and < transMapV5 | binaries can be found < transMapV5 | here. < transMapV5 | The tool can also be used to obtain only features within a given range, for example: < transMapV5 |

< transMapV5 | bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/thaSir1/transMap/V5/thaSir1.refseq.transMapV5.bigPsl < transMapV5 | -chrom=chr6 -start=0 -end=1000000 stdout < transMapV5 | < transMapV5 | < transMapV5 |

Credits

< transMapV5 | < transMapV5 |

< transMapV5 | This track was produced by Mark Diekhans at UCSC from cDNA and EST sequence data < transMapV5 | submitted to the international public sequence databases by < transMapV5 | scientists worldwide and annotations produced by the RefSeq, < transMapV5 | Ensembl, and GENCODE annotations projects.

< transMapV5 | < transMapV5 |

References

< transMapV5 |

< transMapV5 | Siepel A, Diekhans M, Brejová B, Langton L, Stevens M, Comstock CL, Davis C, Ewing B, Oommen S, < transMapV5 | Lau C et al. < transMapV5 | < transMapV5 | Targeted discovery of novel human exons by comparative genomics. < transMapV5 | Genome Res. 2007 Dec;17(12):1763-73. < transMapV5 | PMID: 17989246; PMC: PMC2099585 < transMapV5 |

< transMapV5 | < transMapV5 |

< transMapV5 | Stanke M, Diekhans M, Baertsch R, Haussler D. < transMapV5 | < transMapV5 | Using native and syntenically mapped cDNA alignments to improve de novo gene finding. < transMapV5 | Bioinformatics. 2008 Mar 1;24(5):637-44. < transMapV5 | PMID: 18218656 < transMapV5 |

< transMapV5 | < transMapV5 |

< transMapV5 | Zhu J, Sanborn JZ, Diekhans M, Lowe CB, Pringle TH, Haussler D. < transMapV5 | < transMapV5 | Comparative genomics search for losses of long-established genes on the human lineage. < transMapV5 | PLoS Comput Biol. 2007 Dec;3(12):e247. < transMapV5 | PMID: 18085818; PMC: PMC2134963 < transMapV5 |

< transMapV5 | < transMapV5 | 3889,4254d3104 < unipAliSwissprot | html < unipAliSwissprot | < unipAliTrembl | html < unipAliTrembl | < unipChain | html < unipChain | < unipConflict | html < unipConflict | < unipDisulfBond | html < unipDisulfBond | < unipDomain | html < unipDomain | < unipInterest | html < unipInterest | < unipLocCytopl | html < unipLocCytopl | < unipLocExtra | html < unipLocExtra | < unipLocSignal | html < unipLocSignal | < unipLocTransMemb | html < unipLocTransMemb | < unipModif | html < unipModif | < unipMut | html < unipMut | < unipOther | html < unipOther | < unipRepeat | html < unipRepeat | < uniprot | html < uniprot |

Description

< uniprot | < uniprot |

< uniprot | This track shows protein sequences and annotations on them from the UniProt/SwissProt database, < uniprot | mapped to genomic coordinates. < uniprot |

< uniprot |

< uniprot | UniProt/SwissProt data has been curated from scientific publications by the UniProt staff, < uniprot | UniProt/TrEMBL data has been predicted by various computational algorithms. < uniprot | The annotations are divided into multiple subtracks, based on their "feature type" in UniProt. < uniprot | The first two subtracks below - one for SwissProt, one for TrEMBL - show the < uniprot | alignments of protein sequences to the genome, all other tracks below are the protein annotations < uniprot | mapped through these alignments to the genome. < uniprot |

< uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot | < uniprot |
Track NameDescription
UCSC Alignment, SwissProt = curated protein sequencesProtein sequences from SwissProt mapped to the genome. All other < uniprot | tracks are (start,end) SwissProt annotations on these sequences mapped < uniprot | through this alignment. Even protein sequences without a single curated < uniprot | annotation (splice isoforms) are visible in this track. Each UniProt protein < uniprot | has one main isoform, which is colored in dark. Alternative isoforms are < uniprot | sequences that do not have annotations on them and are colored in light-blue. < uniprot | They can be hidden with the TrEMBL/Isoform filter (see below).
UCSC Alignment, TrEMBL = predicted protein sequencesProtein sequences from TrEMBL mapped to the genome. All other tracks < uniprot | below are (start,end) TrEMBL annotations mapped to the genome using < uniprot | this track. This track is hidden by default. To show it, click its < uniprot | checkbox on the track configuration page.
UniProt Signal PeptidesRegions found in proteins destined to be secreted, generally cleaved from mature protein.
UniProt Extracellular DomainsProtein domains with the comment "Extracellular".
UniProt Transmembrane DomainsProtein domains of the type "Transmembrane".
UniProt Cytoplasmic DomainsProtein domains with the comment "Cytoplasmic".
UniProt Polypeptide ChainsPolypeptide chain in mature protein after post-processing.
UniProt Regions of InterestRegions that have been experimentally defined, such as the role of a region in mediating protein-protein interactions or some other biological process.
UniProt DomainsProtein domains, zinc finger regions and topological domains.
UniProt Disulfide BondsDisulfide bonds.
UniProt Amino Acid ModificationsGlycosylation sites, modified residues and lipid moiety-binding regions.
UniProt Amino Acid MutationsMutagenesis sites and sequence variants.
UniProt Protein Primary/Secondary Structure AnnotationsBeta strands, helices, coiled-coil regions and turns.
UniProt Sequence ConflictsDifferences between Genbank sequences and the UniProt sequence.
UniProt RepeatsRegions of repeated sequence motifs or repeated domains.
UniProt Other AnnotationsAll other annotations, e.g. compositional bias
< uniprot |

< uniprot | For consistency and convenience for users of mutation-related tracks, < uniprot | the subtrack "UniProt/SwissProt Variants" is a copy of the track < uniprot | "UniProt Variants" in the track group "Phenotype and Literature", or < uniprot | "Variation and Repeats", depending on the assembly. < uniprot |

< uniprot | < uniprot |

Display Conventions and Configuration

< uniprot | < uniprot |

< uniprot | Genomic locations of UniProt/SwissProt annotations are labeled with a short name for < uniprot | the type of annotation (e.g. "glyco", "disulf bond", "Signal peptide" < uniprot | etc.). A click on them shows the full annotation and provides a link to the UniProt/SwissProt < uniprot | record for more details. TrEMBL annotations are always shown in < uniprot | light blue, except in the Signal Peptides, < uniprot | Extracellular Domains, Transmembrane Domains, and Cytoplamsic domains subtracks.

< uniprot | < uniprot |

< uniprot | Mouse over a feature to see the full UniProt annotation comment. For variants, the mouse over will < uniprot | show the full name of the UniProt disease acronym. < uniprot |

< uniprot | < uniprot |

< uniprot | The subtracks for domains related to subcellular location are sorted from outside to inside of < uniprot | the cell: Signal peptide, < uniprot | extracellular, < uniprot | transmembrane, and cytoplasmic. < uniprot |

< uniprot | < uniprot |

< uniprot | Features in the "UniProt Modifications" (modified residues) track are drawn in < uniprot | light green. Disulfide bonds are shown in < uniprot | dark grey. Topological domains < uniprot | in maroon and zinc finger regions in < uniprot | olive green. < uniprot |

< uniprot | < uniprot |

< uniprot | Duplicate annotations are removed as far as possible: if a TrEMBL annotation < uniprot | has the same genome position and same feature type, comment, disease and < uniprot | mutated amino acids as a SwissProt annotation, it is not shown again. Two < uniprot | annotations mapped through different protein sequence alignments but with the same genome < uniprot | coordinates are only shown once.

< uniprot | < uniprot |

On the configuration page of this track, you can choose to hide any TrEMBL annotations. < uniprot | This filter will also hide the UniProt alternative isoform protein sequences because < uniprot | both types of information are less relevant to most users. Please contact us if you < uniprot | want more detailed filtering features.

< uniprot | < uniprot |

Note that for the human hg38 assembly and SwissProt annotations, there < uniprot | also is a public < uniprot | track hub prepared by UniProt itself, with < uniprot | genome annotations maintained by UniProt using their own mapping < uniprot | method based on those Gencode/Ensembl gene models that are annotated in UniProt < uniprot | for a given protein. For proteins that differ from the genome, UniProt's mapping method < uniprot | will, in most cases, map a protein and its annotations to an unexpected location < uniprot | (see below for details on UCSC's mapping method).

< uniprot | < uniprot |

Methods

< uniprot | < uniprot |

< uniprot | Briefly, UniProt protein sequences were aligned to the transcripts associated < uniprot | with the protein, the top-scoring alignments were retained, and the result was < uniprot | projected to the genome through a transcript-to-genome alignment. < uniprot | Depending on the genome, the transcript-genome alignments was either < uniprot | provided by the source database (NBCI RefSeq), created at UCSC (UCSC RefSeq) or < uniprot | derived from the transcripts (Ensembl/Augustus). The transcript set is NCBI < uniprot | RefSeq for hg38, UCSC RefSeq for hg19 (due to alt/fix haplotype misplacements < uniprot | in the NCBI RefSeq set on hg19). For other genomes, RefSeq, Ensembl and Augustus < uniprot | are tried, in this order. The resulting protein-genome alignments of this process < uniprot | are available in the file formats for liftOver or pslMap from our data archive < uniprot | (see "Data Access" section below). < uniprot |

< uniprot | < uniprot |

An important step of the mapping process protein -> transcript -> < uniprot | genome is filtering the alignment from protein to transcript. Due to < uniprot | differences between the UniProt proteins and the transcripts (proteins were < uniprot | made many years before the transcripts were made, and human genomes have < uniprot | variants), the transcript with the highest BLAST score when aligning the < uniprot | protein to all transcripts is not always the correct transcript for a protein < uniprot | sequence. Therefore, the protein sequence is aligned to only a very short list < uniprot | of one or sometimes more transcripts, selected by a three-step procedure: < uniprot |

    < uniprot |
  1. Use transcripts directly annotated by UniProt: for organisms that have a RefSeq transcript track, < uniprot | proteins are aligned to the RefSeq transcripts that are annotated < uniprot | by UniProt for this particular protein. < uniprot |
  2. Use transcripts for NCBI Gene ID annotated by UniProt: If no transcripts are annotated on the < uniprot | protein, or the annotated ones have been deprecated by NCBI, but a NCBI Gene ID is < uniprot | annotated, the RefSeq transcripts for this Gene ID are used. This can result in multiple matching transcripts for a protein. < uniprot |
  3. Use best matching transcript: If no NCBI Gene is < uniprot | annotated, then BLAST scores are used to pick the transcripts. There can be multiple transcripts for one < uniprot | protein, as their coding sequences can be identical. All transcripts within 1% of the highest observed BLAST score are used. < uniprot |
< uniprot |

< uniprot | < uniprot |

< uniprot | For strategy 2 and 3, many of the transcripts found do not differ in coding < uniprot | sequence, so the resulting alignments on the genome will be identical. < uniprot | Therefore, any identical alignments are removed in a final filtering step. The < uniprot | details page of these alignments will contain a list of all transcripts that < uniprot | result in the same protein-genome alignment. On hg38, only a handful of edge < uniprot | cases (pseudogenes, very recently added proteins) remain in 2023 where strategy < uniprot | 3 has to be used.

< uniprot | < uniprot |

In other words, when an NCBI or UCSC RefSeq track is used for the mapping and to align a < uniprot | protein sequence to the correct transcript, we use a three stage process: < uniprot |

    < uniprot |
  1. If UniProt has annotated a given RefSeq transcript for a given protein < uniprot | sequence, the protein is aligned to this transcript. Any difference in the < uniprot | version suffix is tolerated in this comparison. < uniprot |
  2. If no transcript is annotated or the transcript cannot be found in the < uniprot | NCBI/UCSC RefSeq track, the UniProt-annotated NCBI Gene ID is resolved to a < uniprot | set of NCBI RefSeq transcript IDs via the most current version of NCBI < uniprot | genes tables. Only the top match of the resulting alignments and all < uniprot | others within 1% of its score are used for the mapping. < uniprot |
  3. If no transcript can be found after step (2), the protein is aligned to all transcripts, < uniprot | the top match, and all others within 1% of its score are used. < uniprot |
< uniprot | < uniprot |

This system was designed to resolve the problem of incorrect mappings of < uniprot | proteins, mostly on hg38, due to differences between the SwissProt < uniprot | sequences and the genome reference sequence, which has changed since the < uniprot | proteins were defined. The problem is most pronounced for gene families < uniprot | composed of either very repetitive or very similar proteins. To make sure that < uniprot | the alignments always go to the best chromosome location, all _alt and _fix < uniprot | reference patch sequences are ignored for the alignment, so the patches are < uniprot | entirely free of UniProt annotations. Please contact us if you have feedback on < uniprot | this process or example edge cases. We are not aware of a way to evaluate the < uniprot | results completely and in an automated manner.

< uniprot |

< uniprot | Proteins were aligned to transcripts with TBLASTN, converted to PSL, filtered < uniprot | with pslReps (93% query coverage, keep alignments within top 1% score), lifted to genome < uniprot | positions with pslMap and filtered again with pslReps. UniProt annotations were < uniprot | obtained from the UniProt XML file. The UniProt annotations were then mapped to the < uniprot | genome through the alignment described above using the pslMap program. This approach < uniprot | draws heavily on the LS-SNP pipeline by Mark Diekhans. < uniprot | Like all Genome Browser source code, the main script used to build this track < uniprot | can be found on Github. < uniprot |

< uniprot | < uniprot |

Older releases

< uniprot |

< uniprot | This track is automatically updated on an ongoing basis, every 2-3 months. < uniprot | The current version name is always shown on the track details page, it includes the < uniprot | release of UniProt, the version of the transcript set and a unique MD5 that is < uniprot | based on the protein sequences, the transcript sequences, the mapping file < uniprot | between both and the transcript-genome alignment. The exact transcript < uniprot | that was used for the alignment is shown when clicking a protein alignment < uniprot | in one of the two alignment tracks. < uniprot |

< uniprot | < uniprot |

< uniprot | For reproducibility of older analysis results and for manual inspection, previous versions of this track < uniprot | are available for browsing in the form of the UCSC UniProt Archive Track Hub (click this link to connect the hub now). The underlying data of < uniprot | all releases of this track (past and current) can be obtained from our downloads server, including the UniProt < uniprot | protein-to-genome alignment.

< uniprot | < uniprot |

Data Access

< uniprot | < uniprot |

< uniprot | The raw data of the current track can be explored interactively with the < uniprot | Table Browser, or the < uniprot | Data Integrator. < uniprot | For automated analysis, the genome annotation is stored in a bigBed file that < uniprot | can be downloaded from the < uniprot | download server. < uniprot | The exact filenames can be found in the < uniprot | track configuration file. < uniprot | Annotations can be converted to ASCII text by our tool bigBedToBed < uniprot | which can be compiled from the source code or downloaded as a precompiled < uniprot | binary for your system. Instructions for downloading source code and binaries can be found < uniprot | here. < uniprot | The tool can also be used to obtain only features within a given range, for example: < uniprot |

< uniprot | bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/thaSir1/uniprot/unipStruct.bb -chrom=chr6 -start=0 -end=1000000 stdout < uniprot |

< uniprot | Please refer to our < uniprot | mailing list archives < uniprot | for questions, or our < uniprot | Data Access FAQ < uniprot | for more information. < uniprot |

< uniprot | < uniprot |

< uniprot | < uniprot |

Lifting from UniProt to genome coordinates in pipelines

< uniprot |

To facilitate mapping protein coordinates to the genome, we provide the < uniprot | alignment files in formats that are suitable for our command line tools. Our < uniprot | command line programs liftOver or pslMap can be used to map < uniprot | coordinates on protein sequences to genome coordinates. The filenames are < uniprot | unipToGenome.over.chain.gz (liftOver) and unipToGenomeLift.psl.gz (pslMap).

< uniprot | < uniprot |

Example commands: < uniprot | 

< uniprot | wget -q https://hgdownload.soe.ucsc.edu/goldenPath/archive/hg38/uniprot/2022_03/unipToGenome.over.chain.gz
< uniprot | wget -q https://hgdownload.soe.ucsc.edu/admin/exe/linux.x86_64/liftOver
< uniprot | chmod a+x liftOver
< uniprot | echo 'Q99697 1 10 annotationOnProtein' > prot.bed
< uniprot | liftOver prot.bed unipToGenome.over.chain.gz genome.bed
< uniprot | cat genome.bed
< uniprot |
< uniprot |

< uniprot | < uniprot |

Credits

< uniprot | < uniprot |

< uniprot | This track was created by Maximilian Haeussler at UCSC, with a lot of input from Chris < uniprot | Lee, Mark Diekhans and Brian Raney, feedback from the UniProt staff, Alejo < uniprot | Mujica, Regeneron Pharmaceuticals and Pia Riestra, GeneDx. Thanks to UniProt for making all data < uniprot | available for download. < uniprot |

< uniprot | < uniprot |

References

< uniprot | < uniprot |

< uniprot | UniProt Consortium. < uniprot | < uniprot | Reorganizing the protein space at the Universal Protein Resource (UniProt). < uniprot | Nucleic Acids Res. 2012 Jan;40(Database issue):D71-5. < uniprot | PMID: 22102590; PMC: PMC3245120 < uniprot |

< uniprot | < uniprot |

< uniprot | Yip YL, Scheib H, Diemand AV, Gattiker A, Famiglietti LM, Gasteiger E, Bairoch A. < uniprot | < uniprot | The Swiss-Prot variant page and the ModSNP database: a resource for sequence and structure < uniprot | information on human protein variants. < uniprot | Hum Mutat. 2004 May;23(5):464-70. < uniprot | PMID: 15108278 < uniprot |

< uniprot | < unipStruct | html < unipStruct |