Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Exon level expression profiling of colorectal cancer tissue samples (77 samples)

ABSTRACT: These colorectal cancer (CRC) samples have been analyzed by exon expression profiling to identify genes with overexpression of 3’ parts. By characterizing underlying transcript structures of such genes with a combination of rapid amplification of cDNA ends and deep-sequencing (RACE-seq), we identify and describe novel RNA-variants in CRC.

ORGANISM(S): Homo sapiens

PROVIDER: GSE69182 | GEO | 2016/04/12

SECONDARY ACCESSION(S): PRJNA284907

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Puccinia triticina Race 77

Project description:Puccinia triticina Race 77 Genome sequencing and assembly

| PRJNA231547 | ENA

Exon level expression profiling of colorectal cancer tissue samples

Project description:This SuperSeries is composed of the SubSeries listed below.

2011-05-19 | GSE24551 | GEO

Exon-level expression profiling of normal colonic mucosa samples.

2014-08-13 | GSE42690 | GEO

Puccinia triticina Race 77

Project description:Reference Sequencing of 13 Biotypes of Puccinia triticina Race 77

| PRJNA277090 | ENA

Exon level integration of proteomics and microarray data

Project description:Background: Previous studies comparing quantitative proteomics and microarray data have generally found poor correspondence between the two. We hypothesised that this might in part be because the different assays were targeting different parts of the expressed genome and might therefore be subjected to confounding effects from processes such as alternative splicing. Results: Using a genome database as a platform for integration, we combined quantitative protein mass spectrometry with Affymetrix Exon array data at the level of individual exons. We found significantly higher degrees of correlation than have been previously observed (r=0.808). The study was performed using cell lines in equilibrium in order to reduce a major potential source of biological variation, thus allowing the analysis to focus on the data integration methods in order to establish their performance. Conclusion: We conclude that much of the variation observed when integrating microarray and proteomics data may occur as a consequence both of the data analysis and of the high granularity to which studies have until recently been limited. The approach opens up the possibility for the first time of considering combined microarray and proteomics datasets at the level of individual exons and isoforms, important given the high proportion of alternative splicing observed in the human genome.

2009-11-24 | GSE19154 | GEO

Gene level expression profiling of colorectal cancer tissue samples

Project description:By the use of whole genome transcription analysis, we aimed to develop a gene expression classifier to increase the likelihood of identifying stage II colorectal cancer (CRC) samples with a poor prognostic outcome. Gene expression measurement were measured by the GeneChip® Human Exon 1.0 ST Arrays from Affymetrix. We analyzed genome-wide expression at the gene-level for an independent series of colorectal cancer tissue biopsies using the Affymetrix Human Exon 1.0 ST platform.

2012-01-06 | E-GEOD-29638 | biostudies-arrayexpress

Gene level expression profiling of colorectal cancer tissue samples

2012-01-06 | GSE29638 | GEO

Exon level expression profiling of colorectal cancer tissue samples

Project description:This SuperSeries is composed of the following subset Series: GSE24549: Exon level expression profiling of colorectal cancer tissue samples (test sample series). GSE24550: Exon level expression profiling of colorectal cancer tissue samples (validation sample series). Refer to individual Series

2011-05-19 | E-GEOD-24551 | biostudies-arrayexpress

Exon-level expression profiling of normal colonic mucosa samples.

Project description:These samples have been analyzed for global alternative splicing variation on exon-level expression data using the FIRMA algorithm. We have identified and described transcriptome instability as a genome-wide, pre-mRNA splicing related characteristic of solid cancers. This Series consists of 19 normal colonic mucosa samples from colorectal cancer patients, and is an amendment to a larger series of colorectal cancer and adjacent normal colonic mucosa samples analyzed for gene expression at the exon-level (GSE24550).

2014-08-13 | E-GEOD-42690 | biostudies-arrayexpress

Exon-level analyses of neuroblastoma

Project description:In this study, mRNA expression profiles of 113 primary untreated human neuroblastoma samples were compared with the aim to identify prognostic exon and gene sets as well as parameters associated with alternative exon use. The primary neuroblastoma specimens were from tumor banks in Cologne or Essen, Germany, Ghent, Belgium and Valencia, Spain. All patients were diagnosed between 1998 and 2007 and treated according to the German Neuroblastoma trials NB97, NB 2004 or the SIOPEN protocol. This submission contains 87 exon array profiles and are used together with exon array data from 26 Samples in GSE21713 (see 'Relation' links below) to predict the outcome of patients with neuroblastoma. The resulting dataset, which is linked below as a supplementary file ('GSE32664_complete_RMA_data.txt'), was used for the subsequent analyses.

2012-06-17 | E-GEOD-32664 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data