Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Somatic mutations in Parkinson

ABSTRACT: Somatic mutations in Parkinson disease are enriched in synaptic and neuronal processes

PROVIDER: PRJEB43918 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other
	ERR5553981.fastq.gz	Fastqsanger.gz
	ERR5553981_1.fastq.gz	Fastqsanger.gz
	ERR5553981_2.fastq.gz	Fastqsanger.gz
	ERR5553952_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 19

Similar Datasets

Generation of isogenic pluripotent stem cells differing exclusively at two early onset Parkinson point mutations

Project description:This SuperSeries is composed of the following subset Series: GSE29772: CNV analysis for Generation of isogenic pluripotent stem cells differing exclusively at two early onset Parkinson point mutations GSE29773: Gene Expression Data for Generation of isogenic pluripotent stem cells differing exclusively at two early onset Parkinson point mutations Refer to individual Series

2011-07-25 | E-GEOD-29774 | biostudies-arrayexpress

Somatic mutations in individual skin cells

Project description:Somatic mutations in individual skin cells

| PRJNA1125506 | ENA

Somatic mutations in individual skin cells

Project description:Somatic mutations in individual skin cells

| PRJNA1125507 | ENA

Layer-specific somatic mutations in apricot

Project description:Layer-specific somatic mutations in apricot

| PRJEB71142 | ENA

Comprehensive multi-omic profiling of somatic mutations in malformations of cortical development

Project description:Malformations of cortical development (MCD) are neurological conditions displaying focal disruption of cortical architecture and cellular organization arising during embryogenesis, largely from somatic mosaic mutations. Identifying the genetic causes of MCD has been a challenge, as mutations remain at low allelic fraction in brain tissue resected to treat epilepsy. Here, we report genetic atlas from 283 brain resections, identifying 69 mutated genes through intensive profiling of somatic mutations, combining whole-exome and targeted-amplicon sequencing with functional validation and single-cell sequencing. Genotype-phenotype correlation analysis elucidated specific MCD gene sets associating distinct pathophysiological and clinical phenotypes. Moreover, the unique spatiotemporal expression patterns deconvolved from single-nuclear transcriptional sequences of mutated genes in control and patient brains suggest critical roles driving excitatory neurogenic pools during brain development, and in establishing neuronal excitation after birth.

2022-11-17 | GSE218022 | GEO

Role of Microglia Somatic Mutations in Neurodegenerative Diseases

Project description:Role of Microglia Somatic Mutations in Neurodegenerative Diseases

| PRJNA671423 | ENA

Detection of Somatic Mutations in vitro Aging Cells

Project description:Detection of Somatic Mutations in vitro Aging Cells

| PRJNA554710 | ENA

Detection of Somatic Mutations in vitro Aging Cells

Project description:Detection of Somatic Mutations in vitro Aging Cells

| PRJNA554709 | ENA

A multiscale functional map of somatic mutations in cancer integrating protein structure and network topology

Project description:A major goal of cancer biology is to understand the mechanisms underlying tumorigenesis driven by somatically acquired mutations. Two distinct types of computational methodologies have emerged: one focuses on analyzing clustering of mutations within protein sequences and 3D structures, while the other characterizes mutations by leveraging the topology of protein-protein interaction network. Their insights are largely non-overlapping, offering complementary strengths. Here, we established a unified, end-to-end 3D structurally-informed protein interaction network propagation framework, NetFlow3D, that systematically maps the multiscale mechanistic effects of somatic mutations in cancer. The establishment of NetFlow3D hinges upon the Human Protein Structurome, a comprehensive repository we compiled that incorporates the 3D structures of every single protein as well as the binding interfaces of all known protein interactions in humans. NetFlow3D leverages the Structurome to integrate information across atomic, residue, protein and network levels: It conducts 3D clustering of mutations across atomic and residue levels on protein structures to identify potential driver mutations. It then anisotropically propagates their impacts across the protein interaction network, with propagation guided by the specific 3D structural interfaces involved, to identify significantly interconnected network "modules", thereby uncovering key biological processes underlying disease etiology. Applied to 1,038,899 somatic protein-altering mutations in 9,946 TCGA tumors across 33 cancer types, NetFlow3D identified 12,378 significant 3D clusters throughout the Human Protein Structurome, of which ~54% would not have been found if using only experimentally-determined structures. It then identified 28 significantly interconnected modules that encompass ~8-fold more proteins than applying standard network analyses.

2024-03-12 | MSV000094298 | MassIVE

High-throughput phenotyping of lung cancer somatic mutations [main experiment]

Project description:Recent genome sequencing efforts have identified millions of somatic mutations in cancer. However, the functional impact of most variants is poorly understood. Here we characterize 194 somatic mutations identified in primary lung adenocarcinomas using L1000 high-throughput gene-expression assays followed by expression-based variant impact phenotyping (eVIP), a method that uses gene expression changes to distinguish impactful from netural somatic mutations. This series represents the main experiment of the study where 8 replicates of wild-type and mutant ORFs are introduced into A549 cell lines.

2016-06-28 | GSE83744 | 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