Schema for Burge RNA-seq - Burge Lab RNA-seq Aligned by GEM Mapper
  Database: hg19    Primary Table: burgeRnaSeqGemMapperAlignBrainAllRawSignal    Row Count: 6,673,794   Data last updated: 2010-05-16
Format description: bed-like graphing data
On download server: MariaDB table dump directory
fieldexampleSQL type description
bin 585smallint(5) unsigned Indexing field to speed chromosome range queries.
chrom chr1varchar(255) Reference sequence chromosome or scaffold
chromStart 17466int(10) unsigned Start position in chromosome
chromEnd 17489int(10) unsigned End position in chromosome
dataValue 0.0912191float data value for this range

Sample Rows
 
binchromchromStartchromEnddataValue
585chr117466174890.0912191
585chr117489174980.182438
585chr117498175210.0912191
585chr124879248910.0912191
585chr129533295550.0912191
586chr11349881350200.0912191
586chr11368781369100.0912191
586chr11379701380020.0912191
586chr12378702379020.0912191
588chr14461654461770.0912191

Note: all start coordinates in our database are 0-based, not 1-based. See explanation here.

Burge RNA-seq (burgeRnaSeqGemMapperAlign) Track Description
 

Description

RNA-Seq is a method for mapping and quantifying the transcriptome of any organism that has a genomic DNA sequence assembly. RNA-Seq was performed by reverse-transcribing an RNA sample into cDNA, followed by high throughput DNA sequencing on an Illumina Genome Analyser. This track shows the RNA-seq data published by Chris Burge's lab (Wang et al.,2008) mapped to the genome using GEM Mapper by the Guigó lab at the Center for Genomic Regulation (CRG). The subtracks display RNA-seq data from various tissues/cell lines:

  1. Brain
  2. Liver
  3. Heart
  4. Muscle
  5. Colon
  6. Adipose
  7. Testes
  8. Lymph Node
  9. Breast
  10. BT474 - Breast Tumour Cell Line
  11. HME - Human Mammary Epithelial Cell Line
  12. MCF7 - Breast Adenocarcinoma Cell Line
  13. MB-435 - Breast Ductal Adenocarcinoma Cell Line*
  14. T-47D - Breast Ductal Carcinoma Cell Line

Tissues were obtained from unrelated anonymous donors. HME is a mammary epithelial cell line immortalized with telomerase reverse transcriptase (TERT). The other cell lines are breast cancer cell lines produced from invasive ductal carcinomas (ATCC).

*NOTE: studies have shown that the MDA-MB-435 cell line appears to have been contaminated with the M14 melanoma cell line. See this entry on the American Type Culture Collection (ATCC) website for more details.

Display Conventions and Configuration

This track is a multi-view composite track that contains multiple data types (views). For each view, there are multiple subtracks that display individually on the browser. Instructions for configuring multi-view tracks are here. The following views are in this track:

Raw Signal
Density graph (bedGraph) of signal enrichment based on a normalized aligned read density (counts per million mapped reads for each subtrack). This normalized measure assists in visualizing the relative amount of a given transcript across multiple samples.
Alignments
The Alignments view shows reads mapped to the genome.

Methods

The group at CRG obtained RNA-seq reads, generated by Wang et al. (2008), from the Short Read Archive section of GEO at NCBI under accession number GSE12946. Using their GEM mapper program, CRG mapped the RNA-seq reads to the genome and transcriptome (GENCODE Release 3, October 2009 Freeze). GEM mapper was run using default parameters and allowing up to two mismatches in the read alignments. Since mapping to the transcriptome depends on length of the reads mapped, reads were only mapped for the 14 tissues or cell lines where reads were of length 32 bp. This excluded reads from MAQC human cell lines (mixed human brain) and MAQC UHR (mixed human cell lines).

Credits

These data were generated by Chris Burge's lab at the Massachusetts Institute of Technology and by Roderic Guigó's lab at the Center for Genomic Regulation (CRG) in Barcelona, Spain. GTF files of the mapped data were provided by Thomas Derrien and Paolo Ribeca from CRG. GEM mapper software can be obtained here.

References

Wang ET, Sandberg R, Luo S, Khrebtukova I, Zhang L, Mayr C, Kingsmore SF, Schroth GP, Burge CB. Alternative isoform regulation in human tissue transcriptomes. Nature. 2008 Nov 27;456(7221):470-6. PMID: 18978772; PMC: PMC2593745