Burge RNA-seq Track Settings

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

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Alignments

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	views^↓1	Tissue Type^↓2	Track Name^↓3
hide	Alignments	Adipose	Burge Lab RNA-seq 32mer Reads from Adipose	Data format
hide Configure	Raw Signal	Adipose	Burge Lab RNA-seq 32mer Reads from Adipose, Raw Signal	Data format
hide	Alignments	Brain	Burge Lab RNA-seq 32mer Reads from Brain	Data format
hide Configure	Raw Signal	Brain	Burge Lab RNA-seq 32mer Reads from Brain, Raw Signal	Data format
hide	Alignments	Breast	Burge Lab RNA-seq 32mer Reads from Breast	Data format
hide Configure	Raw Signal	Breast	Burge Lab RNA-seq 32mer Reads from Breast, Raw Signal	Data format
hide	Alignments	BT474	Burge Lab RNA-seq 32mer Reads from BT474 Breast Tumor Cell Line	Data format
hide Configure	Raw Signal	BT474	Burge Lab RNA-seq 32mer Reads from BT474 Breast Tumour Cell Line, Raw Signal	Data format
hide	Alignments	Colon	Burge Lab RNA-seq 32mer Reads from Colon	Data format
hide Configure	Raw Signal	Colon	Burge Lab RNA-seq 32mer Reads from Colon, Raw Signal	Data format
hide	Alignments	Heart	Burge Lab RNA-seq 32mer Reads from Heart	Data format
hide Configure	Raw Signal	Heart	Burge Lab RNA-seq 32mer Reads from Heart, Raw Signal	Data format
hide	Alignments	HME	Burge Lab RNA-seq 32mer Reads from HME (Human Mammary Epithelial) Cell Line	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	Alignments	Liver	Burge Lab RNA-seq 32mer Reads from Liver	Data format
hide Configure	Raw Signal	Liver	Burge Lab RNA-seq 32mer Reads from Liver, Raw Signal	Data format
hide	Alignments	LymphNode	Burge Lab RNA-seq 32mer Reads from Lymph Node	Data format
hide Configure	Raw Signal	LymphNode	Burge Lab RNA-seq 32mer Reads from Lymph Node, Raw Signal	Data format
hide	Alignments	MB435	Burge Lab RNA-seq 32mer Reads from MB-435 Cell Line	Data format
hide Configure	Raw Signal	MB435	Burge Lab RNA-seq 32mer Reads from MB-435 Cell Line, Raw Signal	Data format
hide	Alignments	MCF7	Burge Lab RNA-seq 32mer Reads from MCF-7 Breast Adenocarcinoma Cell Line	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	Alignments	SkelMuscle	Burge Lab RNA-seq 32mer Reads from Skeletal Muscle	Data format
hide Configure	Raw Signal	SkelMuscle	Burge Lab RNA-seq 32mer Reads from Skeletal Muscle, Raw Signal	Data format
hide	Alignments	T47D	Burge Lab RNA-seq 32mer Reads from T-47D Breast Ductal Carcinoma Cell Line	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	Alignments	Testes	Burge Lab RNA-seq 32mer Reads from Testes	Data format
hide Configure	Raw Signal	Testes	Burge Lab RNA-seq 32mer Reads from Testes, Raw Signal	Data format

Assembly: Human Feb. 2009 (GRCh37/hg19)

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:

Brain
Liver
Heart
Muscle
Colon
Adipose
Testes
Lymph Node
Breast
BT474 - Breast Tumour Cell Line
HME - Human Mammary Epithelial Cell Line
MCF7 - Breast Adenocarcinoma Cell Line
MB-435 - Breast Ductal Adenocarcinoma Cell Line*
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