Non-coding RNA lincRNA TUCP Track Settings
 
lincRNA and TUCP transcripts

Track collection: RNA sequences that do not code for a protein

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Data schema/format description and download
Assembly: Human Dec. 2013 (GRCh38/hg38)
Data coordinates converted via liftOver from: Feb. 2009 (GRCh37/hg19)
Data last updated at UCSC: 2015-04-09


Note: lifted from hg19

Description

This track displays the Human Body Map lincRNAs (large intergenic non coding RNAs) and TUCPs (transcripts of uncertain coding potential), as well as their expression levels across 22 human tissues and cell lines. The Human Body Map catalog was generated by integrating previously existing annotation sources with transcripts that were de-novo assembled from RNA-Seq data. These transcripts were collected from ~4 billion RNA-Seq reads across 24 tissues and cell types.

Expression abundance was estimated by Cufflinks (Trapnell et al., 2010) based on RNA-Seq. Expression abundances were estimated on the gene locus level, rather than for each transcript separately and are given as raw FPKM. The prefixes tcons_ and tcons_l2_ are used to describe lincRNAs and TUCP transcripts, respectively. Specific details about the catalog generation and data sets used for this study can be found in Cabili et al (2011). Extended characterization of each transcript in the human body map catalog can be found at the Human lincRNA Catalog website.

Expression abundance scores range from 0 to 1000, and are displayed from light blue to dark blue respectively:

01000

Credits

The body map RNA-Seq data was kindly provided by the Gene Expression Applications research group at Illumina.

References

Cabili MN, Trapnell C, Goff L, Koziol M, Tazon-Vega B, Regev A, Rinn JL. Integrative annotation of human large intergenic noncoding RNAs reveals global properties and specific subclasses. Genes Dev. 2011 Sep 15;25(18):1915-27. PMID: 21890647; PMC: PMC3185964

Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, Salzberg SL, Wold BJ, Pachter L. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010 May;28(5):511-5. PMID: 20436464; PMC: PMC3146043