dc5d2fedb09bf9a1ea4ea9d9348f5cbfe7a21a82 jeltje.van.baren Wed Apr 23 11:08:39 2025 -0700 fix typos in recount3.html diff --git src/hg/makeDb/trackDb/recount3.html src/hg/makeDb/trackDb/recount3.html index 1dfccbf8870..481ad806789 100644 --- src/hg/makeDb/trackDb/recount3.html +++ src/hg/makeDb/trackDb/recount3.html @@ -1,81 +1,81 @@

Description

Recount3 is a comprehensive resource for re-analyzing RNA-seq data. It provides uniformly processed RNA-seq data and associated metadata from a wide range of studies, enabling researchers to access and analyze gene expression data in a consistent manner. Recount3 aggregates data from multiple sources, including the Sequence Read Archive (SRA) and the Genotype-Tissue Expression (GTEx) project, and reprocesses it using a standardized pipeline. This allows for cross-study comparisons and meta-analyses, facilitating discoveries in genomics and transcriptomics.

These tracks display the recount3 intron data including split read counts.

Display Conventions

Intron blocks are grayscale colored based on read support (darker tones indicate higher coverage).
Split read counts and splice motifs are shown on mouseover.
By default only introns with a minimum read count of 10,000 are shown. This setting can be changed on the track configuration page.
The intron ends are color coded:

Dark blue GT donors and AG acceptors (CT and AC on the minus strand)
Teal GC donors (GT on the minus strand)
Faded red AT donors and AC acceptors (GT and GT on the minus strand)

Introns with non standard ends do not have colored tags.
The SRA track is only visible when zoomed in within 10 million bases because of its data density.

Data Access

The raw data can be explored interactively with the Table Browser or the Data Integrator. For automated analysis, the data may be queried from our REST API.
Please refer to our mailing list archives for questions, or our Data Access FAQ for more information.

Methods

Junction files were converted to bed format. For grayscaling total read count was log10 transformed and multiplied by 10 to get a score between 0 and 225, which can be found in the bed score field.

References

Wilks C, Zheng SC, Chen FY, Charles R, Solomon B, Ling JP, Imada EL, Zhang D, Joseph L, Leek JT et al. recount3: summaries and queries for large-scale RNA-seq expression and splicing. Genome Biol. 2021 Nov 29;22(1):323. PMID: 34844637; PMC: PMC8628444