7f892f8fa5f41b18d489cfdbb0255c05b1b3e3f3 jnavarr5 Mon Oct 7 10:55:15 2019 -0700 Updating http to https for hg19, uiLinks cronjob. diff --git src/hg/makeDb/trackDb/human/geneHancer.html src/hg/makeDb/trackDb/human/geneHancer.html index 22997cf..5737ccc 100644 --- src/hg/makeDb/trackDb/human/geneHancer.html +++ src/hg/makeDb/trackDb/human/geneHancer.html @@ -1,20 +1,20 @@

Description

GeneHancer is a database of human regulatory elements (enhancers and promoters) and their inferred target genes, which is embedded -in GeneCards, a human gene +in GeneCards, a human gene compendium. The GeneHancer database was created by integrating >1 million regulatory elements from multiple genome-wide databases. Associations between the regulatory elements and target genes were based on multiple sources of linking molecular data, along with distance, as described in Methods below.

The GeneHancer track set contains tracks representing:

@@ -71,31 +71,31 @@ (with tall GeneHancer and short TSS's). Clusters composed of interactions with a single gene are colored to correspond to the gene, and those composed of interactions with multiple genes are colored dark gray.

Methods

GeneHancer identifications were created from >1 million regulatory elements obtained from seven genome-wide databases:

  1. ENCODE project Z-Lab Enhancer-like regions (version v3)
  2. Ensembl regulatory build (version 92)
  3. FANTOM5 atlas of active enhancers
    4. -
  4. VISTA Enhancer Browser
    5. +
  5. VISTA Enhancer Browser
  6. dbSUPER super-enhancers
  7. EPDnew promoters
  8. UCNEbase ultra-conserved noncoding elements

Employing an integration algorithm that removes redundancy, the GeneHancer pipeline identified ˜250k integrated candidate regulatory elements (GeneHancers). Each GeneHancer is assigned an annotation-derived confidence score. The GeneHancers that are derived from more than one information source are defined as "elite" GeneHancers.

Gene-GeneHancer associations, and their likelihood-based scores, were generated using information that helps link regulatory elements to genes:

  1. eQTLs (expression quantitative trait loci) from Cross-tissue expression correlations between a transcription factor interacting with a GeneHancer and a candidate target gene
  2. Distance-based associations, including several approaches:
    1. Nearest neighbors, where each GeneHancer is associated with its two proximal genes
    2. Overlaps with the gene territory (intragenic)
    3. Proximity to the gene TSS (<2kb)

Associations that are derived from more than one information source are defined as "elite" associations, which leads to the definition of the "double elite" dataset - elite gene associations of elite GeneHancers.

More details are provided at the GeneCards - + information page. For a full description of the methods used, refer to the GeneHancer manuscript1.

Source data for the GeneHancer version 4.8 was downloaded during May 2018.

Data Access

Limited GeneHancer positional data may be explored with the Table Browser. The complete data are not found in the UCSC download servers as per the agreement with the Weizmann Institute.

GeneHancer is the property of the Weizmann Institute of Science and is not available for download or mirroring by any third party @@ -146,18 +146,18 @@

Contact: simon. fishilevich@weizmann. ac. il

Supported in part by a grant from LifeMap Sciences Inc.

References

-Fishilevich S., Nudel R., Rappaport N., Hadar R., Plaschkes I., Iny Stein T., Rosen N., Kohn A., Twik M., Safran M., Lancet D. and Cohen D. GeneHancer: genome-wide integration of enhancers and target genes in GeneCards, Database (Oxford) (2017), doi:10.1093/database/bax028. [PDF] PMID 28605766

+Fishilevich S., Nudel R., Rappaport N., Hadar R., Plaschkes I., Iny Stein T., Rosen N., Kohn A., Twik M., Safran M., Lancet D. and Cohen D. GeneHancer: genome-wide integration of enhancers and target genes in GeneCards, Database (Oxford) (2017), doi:10.1093/database/bax028. [PDF] PMID 28605766

-Stelzer G, Rosen R, Plaschkes I, Zimmerman S, Twik M, Fishilevich S, Iny Stein T, Nudel R, Lieder I, Mazor Y, Kaplan S, Dahary, D, Warshawsky D, Guan- Golan Y, Kohn A, Rappaport N, Safran M, and Lancet D. The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analysis, Current Protocols in Bioinformatics (2016), 54:1.30.1-1.30.33. doi: 10.1002/cpbi.5. PMID 27322403

+Stelzer G, Rosen R, Plaschkes I, Zimmerman S, Twik M, Fishilevich S, Iny Stein T, Nudel R, Lieder I, Mazor Y, Kaplan S, Dahary, D, Warshawsky D, Guan- Golan Y, Kohn A, Rappaport N, Safran M, and Lancet D. The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analysis, Current Protocols in Bioinformatics (2016), 54:1.30.1-1.30.33. doi: 10.1002/cpbi.5. PMID 27322403