Burge RNA-seq Track Settings
 
Burge Lab RNA-seq Aligned by GEM Mapper   (All Expression tracks)

Maximum display mode:       Reset to defaults   
Select views (Help):
Raw Signal ▾       Alignments      
Select subtracks by tissue type:
Tissue Type
BT474
HME
MB435
MCF7
T47D
Adipose
Brain
Breast
Colon
Heart
Liver
LymphNode
SkelMuscle
Testes
List subtracks: only selected/visible    all    ()
  views↓1 Tissue Type↓2   Track Name↓3  
 
hide
 Alignments  BT474  Burge Lab RNA-seq 32mer Reads from BT474 Breast Tumor Cell Line   Data format 
 
hide
 Alignments  HME  Burge Lab RNA-seq 32mer Reads from HME (Human Mammary Epithelial) Cell Line   Data format 
 
hide
 Alignments  MB435  Burge Lab RNA-seq 32mer Reads from MB-435 Cell Line   Data format 
 
hide
 Alignments  MCF7  Burge Lab RNA-seq 32mer Reads from MCF-7 Breast Adenocarcinoma Cell Line   Data format 
 
hide
 Alignments  T47D  Burge Lab RNA-seq 32mer Reads from T-47D Breast Ductal Carcinoma Cell Line   Data format 
 
hide
 Alignments  Adipose  Burge Lab RNA-seq 32mer Reads from Adipose   Data format 
 
hide
 Alignments  Brain  Burge Lab RNA-seq 32mer Reads from Brain   Data format 
 
hide
 Alignments  Breast  Burge Lab RNA-seq 32mer Reads from Breast   Data format 
 
hide
 Alignments  Colon  Burge Lab RNA-seq 32mer Reads from Colon   Data format 
 
hide
 Alignments  Heart  Burge Lab RNA-seq 32mer Reads from Heart   Data format 
 
hide
 Alignments  Liver  Burge Lab RNA-seq 32mer Reads from Liver   Data format 
 
hide
 Alignments  LymphNode  Burge Lab RNA-seq 32mer Reads from Lymph Node   Data format 
 
hide
 Alignments  SkelMuscle  Burge Lab RNA-seq 32mer Reads from Skeletal Muscle   Data format 
 
hide
 Alignments  Testes  Burge Lab RNA-seq 32mer Reads from Testes   Data format 
 
hide
 Configure
 Raw Signal  BT474  Burge Lab RNA-seq 32mer Reads from BT474 Breast Tumour Cell Line, Raw Signal   Data format 
 
hide
 Configure
 Raw Signal  HME  Burge Lab RNA-seq 32mer Reads from HME (Human Mammary Epithelial) Cell Line, Raw Signal   Data format 
 
hide
 Configure
 Raw Signal  MB435  Burge Lab RNA-seq 32mer Reads from MB-435 Cell Line, Raw Signal   Data format 
 
hide
 Configure
 Raw Signal  MCF7  Burge Lab RNA-seq 32mer Reads from MCF-7 Breast Adenocarcinoma Cell Line, Raw Signal   Data format 
 
hide
 Configure
 Raw Signal  T47D  Burge Lab RNA-seq 32mer Reads from T-47D Breast Ductal Carcinoma Cell Line, Raw Signal   Data format 
 
hide
 Configure
 Raw Signal  Adipose  Burge Lab RNA-seq 32mer Reads from Adipose, Raw Signal   Data format 
 
hide
 Configure
 Raw Signal  Brain  Burge Lab RNA-seq 32mer Reads from Brain, Raw Signal   Data format 
 
hide
 Configure
 Raw Signal  Breast  Burge Lab RNA-seq 32mer Reads from Breast, Raw Signal   Data format 
 
hide
 Configure
 Raw Signal  Colon  Burge Lab RNA-seq 32mer Reads from Colon, Raw Signal   Data format 
 
hide
 Configure
 Raw Signal  Heart  Burge Lab RNA-seq 32mer Reads from Heart, Raw Signal   Data format 
 
hide
 Configure
 Raw Signal  Liver  Burge Lab RNA-seq 32mer Reads from Liver, Raw Signal   Data format 
 
hide
 Configure
 Raw Signal  LymphNode  Burge Lab RNA-seq 32mer Reads from Lymph Node, Raw Signal   Data format 
 
hide
 Configure
 Raw Signal  SkelMuscle  Burge Lab RNA-seq 32mer Reads from Skeletal Muscle, Raw Signal   Data format 
 
hide
 Configure
 Raw Signal  Testes  Burge Lab RNA-seq 32mer Reads from Testes, Raw Signal   Data format 
    
Assembly: Human Mar. 2006 (NCBI36/hg18)

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 2b, February 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.