TransMap V5 TransMap ESTs Track Settings
TransMap EST Mappings Version 5

Track collection: TransMap Alignments Version 5

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Label: common name    organism abbreviation    source database    source transcript id    alignment Id   

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Data last updated: 2019-06-10 09:51:45


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

Display Conventions and Configuration

This track follows the display conventions for PSL alignment tracks.

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


  1. Source transcript alignments were obtained from vertebrate organisms in the UCSC Genome Browser Database. BLAT alignments of RefSeq Genes, GenBank mRNAs, and GenBank Spliced ESTs to the cognate genome, along with UCSC Genes, were used as available.
  2. For all vertebrate assemblies that had BLASTZ alignment chains and nets to the human (hg38) genome, a subset of the alignment chains were selected as follows:
    • For organisms whose branch distance was no more than 0.5 (as computed by phyloFit, see Conservation track description for details), syntenic filtering was used. Reciprocal best nets were used if available; otherwise, nets were selected with the netfilter -syn command. The chains corresponding to the selected nets were used for mapping.
    • For more distant species, where the determination of synteny is difficult, the full set of chains was used for mapping. This allows for more genes to map at the expense of some mapping to paralogous regions. The post-alignment filtering step removes some of the duplications.
  3. The pslMap program was used to do a base-level projection of the source transcript alignments via the selected chains to the human genome, resulting in pairwise alignments of the source transcripts to the genome.
  4. The resulting alignments were filtered with pslCDnaFilter with a global near-best criteria of 0.5% in finished genomes (human and mouse) and 1.0% in other genomes. Alignments where less than 20% of the transcript mapped were discarded.

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

Where srcUniq is a number added to make each source alignment unique, and destUniq is added to give the subsequent TransMap alignments unique identifiers.

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

Data Access

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

  • TransMap Ensembl - hg38.ensembl.transMapV4.bigPsl
  • TransMap RefGene - hg38.refseq.transMapV4.bigPsl
  • TransMap RNA - hg38.rna.transMapV4.bigPsl
  • TransMap ESTs - hg38.est.transMapV4.bigPsl
Individual regions or the whole genome annotation can be obtained using our tool bigBedToBed which can be compiled from the source code or downloaded as a precompiled binary for your system. Instructions for downloading source code and binaries can be found here. The tool can also be used to obtain only features within a given range, for example:

bigBedToBed -chrom=chr6 -start=0 -end=1000000 stdout


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


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

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

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