GTEx RNA-Seq Coverage Track Settings
 
GTEx V8 RNA-Seq Read Coverage by Tissue   (All Expression tracks)

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Graph configuration help
All subtracks:
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 Adip Subcut  Adipose Subcutaneous   Data format 
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 Adip Visc Om  Adipose Visceral Omentum - GTEX-14BMU-0626-SM-73KZ6   Data format 
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 Adren Gland  Adrenal Gland   Data format 
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 Artery Aorta  Artery Aorta   Data format 
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 Artery Coron  Artery Coronary   Data format 
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 Artery Tibia  Artery Tibial   Data format 
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 Bladder  Bladder   Data format 
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 Brain Amygd  Brain Amygdala   Data format 
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 Brain Ant cin cort  Brain Anterior cingulate cortex BA24   Data format 
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 Brain Caud bas gangl  Brain Caudate basal ganglia   Data format 
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 Brain Cereb  Brain Cerebellum   Data format 
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 Brain Cereb Hemisph  Brain Cerebellar Hemisphere   Data format 
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 Brain Cortex  Brain Cortex   Data format 
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 Brain Front Cortex  Brain Frontal Cortex BA9   Data format 
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 Brain Hippocamp  Brain Hippocampus   Data format 
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 Brain Hypothal  Brain Hypothalamus   Data format 
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 Brain Nucl acc bas gang  Brain Nucleus accumbens basal ganglia   Data format 
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 Brain Put bas gang  Brain Putamen basal ganglia   Data format 
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 Brain Spinal cord cerv  Brain Spinal cord cervical c-1   Data format 
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 Brain Subst nigr  Brain Substantia nigra   Data format 
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 Breast Mammary  Breast Mammary Tissue   Data format 
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 Cells EBV lymphoc  Cells EBV-transformed lymphocytes   Data format 
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 Cells fibrobl cult  Cells Cultured fibroblasts   Data format 
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 Cervix Ectocerv  Cervix Ectocervix   Data format 
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 Cervix Endocerv  Cervix Endocervix   Data format 
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 Colon Sigmoid  Colon Sigmoid   Data format 
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 Colon Transverse  Colon Transverse   Data format 
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 Esoph Gastroes Junc  Esophagus Gastroesophageal Junction   Data format 
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 Esoph Mucosa  Esophagus Mucosa   Data format 
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 Esoph Muscularis  Esophagus Muscularis   Data format 
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 Fallopian Tube  Fallopian Tube   Data format 
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 Heart Atr Append  Heart Atrial Appendage   Data format 
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 Heart Left Ventr  Heart Left Ventricle   Data format 
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 Kidney Cortex  Kidney Cortex   Data format 
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 Kidney Medulla  Kidney Medulla   Data format 
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 Liver  Liver   Data format 
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 Lung  Lung   Data format 
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 Minor Saliv Gland  Minor Salivary Gland   Data format 
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 Muscle Skeletal  Muscle Skeletal   Data format 
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 Nerve Tibial  Nerve Tibial   Data format 
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 Ovary  Ovary   Data format 
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 Pancreas  Pancreas   Data format 
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 Pituitary  Pituitary   Data format 
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 Prostate  Prostate   Data format 
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 Skin not sun exp  Skin Not Sun Exposed Suprapubic   Data format 
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 Skin sun exp  Skin Sun Exposed Lower leg   Data format 
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 Small Intestine  Small Intestine Terminal Ileum   Data format 
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 Spleen  Spleen   Data format 
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 Stomach  Stomach   Data format 
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 Testis  Testis   Data format 
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 Thyroid  Thyroid   Data format 
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 Uterus  Uterus   Data format 
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 Vagina  Vagina   Data format 
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 Whole Blood  Whole Blood   Data format 
    
Assembly: Human Dec. 2013 (GRCh38/hg38)

Description

The NIH Genotype-Tissue Expression (GTEx) project determined genetic variation and gene expression in 52 tissues and 2 cell lines using RNA-seq data (V8, August 2019), on 17,382 samples from 948 adults. This track focuses on the gene expression part. It shows read coverage, from one single sample per tissue, selected for high-quality and high read depth. The data is summarized to one number per base pair, the number of sequencing reads that cover this position. The plot allows finding out if a given exon is transcribed primarily in certain tissues and also whether transcription is uniform over the length of a single exon.

Display Conventions

This track follows the display conventions for composite "wiggle" tracks. The subtracks, one per tissue, of this track may be configured in a variety of ways to highlight different aspects of the displayed data. The graphical configuration options are shown at the top of the track description page, followed by a list of subtracks. To display only selected subtracks, uncheck the boxes next to the tracks you wish to hide. For more information about the graphical configuration options, click the Graph configuration help link.

Tissue colors were assigned to conform to the GTEx Consortium publication conventions.

In Dense mode, the darkness of the grayscale rectangle displayed for the gene reflects the absolute read count.

Methods

For background information about GTEx sample selection, see our GTEx gene expression track. In short, samples were sequenced with the Illumina TrueSeq protocol on unstranded polyA+ librarires to obtain 76-bp paired end reads with HiSeq 2000 and 2500 machines.

Sequence reads were aligned to the hg38/GRCh38 human genome using STAR v2.5.3a and the GENCODE 26 transcriptome. The alignment pipeline is available here. For further method details, see the GTEx Portal Documentation page.

To obtain read coverage, the GTEx Laboratory, Data Analysis and Coordinating Center (LDACC) at the Broad Institute decided to select a single, high-quality representative sample for each tissue type, since aggregated tracks may obscure certain features or even introduce some artifacts (e.g. intronic coverage). For each tissue, the selected sample has the highest RIN value with a high coverage (>80M reads) and exonic rate (>85%). The alignment-to-coverage pipeline is available from Github: Python script, Docker file and Pipeline WDL description.

To show the exact GTEx sample that was used for each tissue, click the "Schema" link on the track configuration page (above), the filename under "bigDataUrl" includes the identifier.

Subject and Sample Characteristics

The scientific goal of the GTEx project required that the donors and their biospecimen present with no evidence of disease. The tissue types collected were chosen based on their clinical significance, logistical feasibility and their relevance to the scientific goal of the project and the research community. Summary plots of GTEx sample characteristics are available at the GTEx Portal Tissue Summary page.

Data Access

The raw data for the GTEx Read Coverage track can be accessed interactively through the Table Browser.

For automated analysis and downloads, the track data files can be downloaded from our downloads server or the JSON API. Individual regions or the whole genome annotation can be accessed as text using our utility bigBedToBed. Instructions for downloading the utility can be found here. That utility can also be used to obtain features within a given range, e.g. bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/hg38/gtex/gtexGeneV8.bb -chrom=chr21 -start=0 -end=100000000 stdout

Data can also be obtained directly from GTEx at the following link: https://gtexportal.org/home/datasets

Credits

Statistical analysis and data interpretation was performed by The GTEx Consortium Analysis Working Group. Data was provided by the GTEx LDACC at The Broad Institute of MIT and Harvard.

References

GTEx Consortium. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science. 2020 Sep 11;369(6509):1318-1330. PMID: 32913098; PMC: PMC7737656

GTEx Consortium. The Genotype-Tissue Expression (GTEx) project. Nat Genet. 2013 Jun;45(6):580-5. PMID: 23715323; PMC: PMC4010069

Carithers LJ, Ardlie K, Barcus M, Branton PA, Britton A, Buia SA, Compton CC, DeLuca DS, Peter-Demchok J, Gelfand ET et al. A Novel Approach to High-Quality Postmortem Tissue Procurement: The GTEx Project. Biopreserv Biobank. 2015 Oct;13(5):311-9. PMID: 26484571; PMC: PMC4675181

Melé M, Ferreira PG, Reverter F, DeLuca DS, Monlong J, Sammeth M, Young TR, Goldmann JM, Pervouchine DD, Sullivan TJ et al. Human genomics. The human transcriptome across tissues and individuals. Science. 2015 May 8;348(6235):660-5. PMID: 25954002; PMC: PMC4547472

DeLuca DS, Levin JZ, Sivachenko A, Fennell T, Nazaire MD, Williams C, Reich M, Winckler W, Getz G. RNA-SeQC: RNA-seq metrics for quality control and process optimization. Bioinformatics. 2012 Jun 1;28(11):1530-2. PMID: 22539670; PMC: PMC3356847