Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

XClone for analyzing somatic copy number alterations

ABSTRACT: Somatic copy number alterations (CNAs) are major mutations that contribute to the development and progression of various cancers. Despite a few computational methods proposed to detect CNAs from single-cell transcriptomic data, the technical sparsity of such data makes it challenging to identify allele-specific CNAs, particularly in complex clonal structures. In this study, we present a statistical method, XClone, that strengthens the signals of read depth and allelic imbalance by effective smoothing on cell neighborhood and gene coordinate graphs to detect haplotype-aware CNAs from scRNA-seq data. By applying XClone to multiple datasets with challenging compositions, we demonstrated its ability to robustly detect different types of allele-specific CNAs and potentially indicate whole genome duplication, therefore enabling the discovery of corresponding subclones and the dissection of their phenotypic impacts.

PROVIDER: EGAS00001007854 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Json Xml

Similar Datasets

Robust partitioning of microRNA targets from downstream regulatory changes [miRNA-seq]

Project description:The biological impact of microRNAs is determined by their targets, and robustly identifying direct miRNA targets remains challenging. Existing methods suffer from high false-positive rates and are unable to effectively differentiate direct miRNA targets from downstream regulatory changes. Here, we present a simple approach to deconvolute post-transcriptional and transcriptional changes using PRO-seq with RNA-seq. In combination, these methods allow us to systematically profile the regulatory impact of a miRNA. We refer to this approach as CARP: Combined Analysis of RNA-seq and PRO-seq. We apply CARP to multiple miRNAs and show that it robustly distinguishes direct targets from downstream changes, while greatly reducing false positives. We validate our approach using Argonaute eCLIP-seq and ribosome profiling, demonstrating that CARP defines a comprehensive repertoire of targets. We identify miRNA-specific activity of target sites within the coding region. CARP facilitates the dissection of complex changes in gene regulatory networks triggered by miRNAs and identification of transcription factors that underlie downstream regulatory changes. Given the robustness of the approach, CARP is particularly suitable for dissecting miRNA regulatory networks in vivo.

2020-08-07 | GSE142898 | GEO

Robust partitioning of microRNA targets from downstream regulatory changes [AGO-eCLIP-seq]

2020-08-07 | GSE142897 | GEO

Robust partitioning of microRNA targets from downstream regulatory changes [RNA-seq]

2020-08-07 | GSE142895 | GEO

Robust partitioning of microRNA targets from downstream regulatory changes [PRO-seq]

2020-08-07 | GSE140365 | GEO

Transcription profiling of human skeletal muscle from males with type 2 diabetes to identify genes involved in oxidative phosphorylation

Project description:DNA microarrays can be used to discover gene expression changes characteristic of human disease. This is challenging, however, when relevant differences are subtle at the level of individual genes. We introduce an analytical strategy, Gene Set Enrichment Analysis, designed to detect modest but coordinate changes in the expression of groups of functionally related genes. Using this approach, we identify a set of genes involved in oxidative phosphorylation whose expression is coordinately decreased in human diabetic muscle. Expression of these genes is high at sites of insulin-mediated glucose disposal, activated by PGC-1a, and correlated with total-body aerobic capacity. Our results associate this gene set with clinically important variation in human metabolism, and illustrate the value of pathway relationships in the analysis of genomic profiling experiments.

2007-07-17 | E-CBIL-30 | biostudies-arrayexpress

Project description:Predicting allele specific expression from allele specific binding

| PRJEB53044 | ENA

Homo sapiens

Project description:Affymetrix 6.0 SNP arrays interrogated to detect allele-specific DNA modification in the brain

| PRJNA291241 | ENA

Fat-type specific effects of high fat diets

Project description:High fat diet (HF) rodent models have contributed significantly to the dissection of the pathophysiology of the insulin resistance syndrome, but their phenotype varies distinctly between different studies. Here, we have analyzed gene expression patterns in livers of animals fed with different HF with varying fatty acid compositions. Keywords: diet-gene interaction

2005-10-28 | GSE3512 | GEO

F1 allele specific gene expression

Project description:By comparing mouse fibroblasts from two parental strains (Bl6 and Spretus) with fibroblasts from their first generation offspring (F1) we can detect allele specific expression of proteins. The Bl6 and Spretus lines are evolutionary distant and harbour many SNPs in their genomes which when synonomous we can detect on the protein level using mass spectrometry. By mixing SILAC labeled Bl6, Spretus and F1 offspring cell lines we can detect peptides shared between all three cell lines and also SNP peptides that are only expressed in the F1 cells and either Bl6 or Spretus cells. By comparing the abundance of the shared peptides and the SNP peptides we can quantify how much of a protein in the F1 cells that comes from the paternal or maternal allele. This data were then further compared to polysome profiling data. Azidohomoalanine labeling was used to enrich newly synthesized proteins from the three cell lines.

2015-08-18 | PXD002337 | Pride

A comparison of DNA copy number profiling platforms using a panel of melanoma cell lines

Project description:The accurate mapping of recurring DNA copy number aberrations (CNAs), a hallmark feature of the cancer genome, has facilitated the discovery of tumor suppressor genes and oncogenes. Microarray-based assays designed to detect these chromosomal copy number alterations on a genome-wide and high-resolution scale have emerged as a cornerstone technology in the genomic era. The diversity of commercially-available platforms prompted a systematic comparison of five copy number profiling assays for their ability to detect 2-fold copy number gain and loss (4n or 1n, respectively) as well as focal high-amplitude CNAs. Here, using a collection of established human melanoma cell lines, we defined the reproducibility, absolute signals, signal:noise, false-positive and false-negative rates for each of the five assays against ground-truth defined by Spectral Karyotyping (SKY), in addition to comparing the concordance of CNAs detection by two high-resolution Agilent and Affymetrix microarray platforms. Our analyses concluded that the Agilent’s 60mer oligo-microarray with probe design optimized for genomic hybridization offers the highest sensitivity and specificity [area under Receiver Operator Characteristic (ROC) curve >0.99] while Affymetrix’s SNP microarray appears to offer better detection of CNAs in gene-poor region. Availability of these comparison results should guide study design decisions and facilitate further computational development. Keywords: comparative genomic hybridization

2007-11-02 | GSE7822 | 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