Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

International Cancer Proteogenomics Consortium (ICPC): Proteogenomics of East-Asian Breast Cancer

ABSTRACT: International Cancer Proteogenomics Consortium (ICPC): Proteogenomics of East-Asian Breast Cancer

PROVIDER: PRJNA909918 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

International Cancer Proteogenomics Consortium (ICPC): Proteogenomics of East-Asian Breast Cancer

Project description:International Cancer Proteogenomics Consortium (ICPC): Proteogenomics of East-Asian Breast Cancer

| PRJNA909917 | ENA

International Cancer Proteogenome Consortium (ICPC): Proteogenomics of Early Stage Lung Adenocarcinoma in Taiwan

Project description:International Cancer Proteogenome Consortium (ICPC): Proteogenomics of Early Stage Lung Adenocarcinoma in Taiwan

| PRJNA597627 | ENA

International Cancer Proteogenome Consortium (ICPC): Proteogenomics of Early Stage Lung Adenocarcinoma in Taiwan

Project description:International Cancer Proteogenome Consortium (ICPC): Proteogenomics of Early Stage Lung Adenocarcinoma in Taiwan

| PRJNA597628 | ENA

International Cancer Proteogenome Consortium (ICPC): Proteogenomics of Oral Squamous Cell Carcinoma in Taiwan

Project description:International Cancer Proteogenome Consortium (ICPC): Proteogenomics of Oral Squamous Cell Carcinoma in Taiwan

| PRJNA758588 | ENA

International Cancer Proteogenome Consortium (ICPC): Proteogenomics of Oral Squamous Cell Carcinoma in Taiwan

Project description:International Cancer Proteogenome Consortium (ICPC): Proteogenomics of Oral Squamous Cell Carcinoma in Taiwan

| PRJNA758587 | ENA

Homo sapiens

Project description:International Cancer Proteogenome Consortium (ICPC): Proteogenomics of Early Stage Lung Adenocarcinoma in Taiwan

| PRJNA594250 | ENA

Prokaryotic Proteogenomics

Project description:Prokaryotic Proteogenomics

| PRJNA66995 | ENA

The International Cancer Genome project: Pan-Cancer Analysis of Whole Genomes (PCAWG)

Project description:The Pan-Cancer Analysis of Whole Genomes (PCAWG) study is an international collaboration to identify common patterns of mutation in more than 2,800 cancer whole genomes from the International Cancer Genome Consortium. Building upon previous work which examined cancer coding regions, this project is exploring the nature and consequences of somatic and germline variations in both coding and non-coding regions, with specific emphasis on cis-regulatory sites, non-coding RNAs, and large-scale structural alterations. Read more on the <a href=\"https://dcc.icgc.org/pcawg\" target=\"_blank\">project website</a>.<br>This is a subset featuring RNA-seq transcription profiling data of 27 cancer subtypes in 19 tissues. Some donors have matched normal tissue. As general reference, a subset of normal tissue samples from the GTEx project were included in this experiment.

2020-02-05 | E-MTAB-5200 | biostudies-arrayexpress

The International Cancer Genome project: Pan-Cancer Analysis of Whole Genomes (PCAWG)- Alternative view by individual

Project description:The Pan-Cancer Analysis of Whole Genomes (PCAWG) study is an international collaboration to identify common patterns of mutation in more than 2,800 cancer whole genomes from the International Cancer Genome Consortium. Building upon previous work which examined cancer coding regions, this project is exploring the nature and consequences of somatic and germline variations in both coding and non-coding regions, with specific emphasis on cis-regulatory sites, non-coding RNAs, and large-scale structural alterations. Read more on the <a href=\"https://dcc.icgc.org/pcawg\" target=\"_blank\">project website</a>.<br>This is a subset featuring RNA-seq transcription profiling data of 27 cancer subtypes in 19 tissues. Some donors have matched normal tissue.<br>This is the alternative view of the experiment for Expression Atlas to show gene expression per donor.

2020-02-05 | E-MTAB-5423 | biostudies-arrayexpress

The influence of transcript assembly on the proteogenomics discovery of microproteins

Project description:Proteogenomics methods have identified many non-annotated protein-coding genes in the human genome. Many of the newly discovered protein-coding genes encode peptides and small proteins, referred to collectively as microproteins. Microproteins are produced through ribosome translation of small open reading frames (smORFs). The discovery of many smORFs reveals a blind spot in traditional gene-finding algorithms for these genes. Biological studies have found roles for microproteins in cell biology and physiology, and the potential that there exists additional bioactive microproteins drives the interest in detection and discovery of these molecules. A key step in any proteogenomics workflow is the assembly of RNA-Seq data into likely mRNA transcrips that are then used to create a searchable protein databases. Here we demonstrate that specific features of the assembled transcriptome impact microprotein detection by shotgun proteomics. By tailoring transcript assembly for downstream mass spectrometry searching, we show that we can detect more than double the number of high-quality microprotein candidates and introduce a novel open-source mRNA assembler for proteogenomics (MAPS) that incorporates all of these features. By integrating our specialized assembler, MAPS, and a popular generalized assembler into our proteogenomics pipeline, we detect 45 novel human microproteins from a high quality proteogenomics dataset of a human cell line. We then characterize the features of the novel microproteins, identifying two classes of microproteins. Our work highlights the importance of specialized transcriptome assembly upstream of proteomics validation when searching for short and potentially rare and poorly conserved proteins.

2017-12-20 | GSE92659 | GEO

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