ENC RNA-seq Tracks
ENCODE RNA-seq tracks   (All Expression tracks)

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Caltech RNA-seq  RNA-seq from ENCODE/Caltech  
CSHL Long RNA-seq  Long RNA-seq from ENCODE/Cold Spring Harbor Lab  
GIS RNA-seq  RNA-seq from ENCODE/Genome Institute of Singapore  
HAIB RNA-seq  RNA-seq from ENCODE/HAIB  
SYDH RNA-seq  RNA-seq from ENCODE/Stanford/Yale/USC/Harvard  



RNA sequencing, or RNA-seq, is a method for mapping and quantifying the total amount of RNA transcripts in a cell at any given time, otherwise known as the transcriptome, for any organism that has a genomic DNA sequence assembly. Compared to microarrays that detect and quantify transcripts by hybridization against known sequences, RNA-seq directly sequences transcripts and is especially well-suited for de novo discovery of RNA splicing patterns and for determining unequivocally the presence or absence of lower abundance class RNAs. RNA-seq is performed by reverse-transcribing an RNA sample into cDNA followed by high throughput DNA sequencing. Most data is produced in the format of either single reads or paired-end reads. In the format of single reads each sequence read comes from one end of a randomly primed cDNA molecule (and represent one end of one cDNA segment), while paired-end reads are obtained as pairs from both ends of a randomly primed cDNA (and represent two opposite ends of one cDNA segment). The resulting sequence reads are then informatically mapped onto the genome sequence (Alignments). The current mappers (TopHat and STAR) have the ability to map reads to annotated and unannotated genomic regions. Reads mapped to annotated or novel RNA splice junctions are (Splice Sites). Earlier versions of this software did not map reads to unannotated genomic regions.

Some RNA-seq protocols do not specify the coding strand. As a result, there can be ambiguity at loci where both strands are transcribed.

Display Conventions

These tracks are multi-view composite tracks that contain multiple data types (views). Each view within a track has separate display controls, as described here. Most ENCODE tracks contain multiple subtracks, corresponding to multiple experimental conditions. If a track contains a large number of subtracks, only some subtracks will be displayed by default. The user can select which subtracks are displayed via the display controls on the track details pages.


These data were generated and analyzed as part of the ENCODE project, a genome-wide consortium project with the aim of cataloging all functional elements in the human genome. This effort includes collecting a variety of data across related experimental conditions to facilitate integrative analysis. Consequently, additional ENCODE tracks may contain data that is relevant to the data in these tracks.


Morozova O, Hirst M, Marra MA. Applications of new sequencing technologies for transcriptome analysis. Annual Review of Genomics and Human Genetics. 2009;10:135-51.

Metzker ML. Sequencing technologies - the next generation. Nature Reviews: Genetics. 2010 Jan;11(1):31-46

Data Release Policy

Data users may freely use ENCODE data, but may not, without prior consent, submit publications that use an unpublished ENCODE dataset until nine months following the release of the dataset. This date is listed in the Restricted Until column on the track configuration page and the download page. The full data release policy for ENCODE is available here.