Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: Multi-omics sequencing of Batrachium bungei

PROVIDER: PRJNA1068854 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR27722700_1.fastq.gz	Fastqsanger.gz
	SRR27722700_2.fastq.gz	Fastqsanger.gz
	SRR27722701_1.fastq.gz	Fastqsanger.gz
	SRR27722701_2.fastq.gz	Fastqsanger.gz
	SRR27722702_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 122

Similar Datasets

Project description:Multi omics sequencing

| PRJNA1143731 | ENA

Methylome profiling of human glioblastoma using Illumina 450K microarrays for the GlioTeX panel

Project description:Genome-wide methylation profiles were generated as part of a multi-omics characterization (SNP array, WES, RNA-seq, cDNA microarray) of a panel of gliomasphere cell lines and matched parental tumors. See https://www.ncbi.nlm.nih.gov/pubmed/27571888 about the GlioTeX panel. Methylation profiling data in this record come from tumour samples. SNP array (ArrayExpress E-MTAB-4804), cDNA microarray (ArrayExpress E-MTAB-4803), WES and RNAseq (European Genome-Phenome Archive EGAS00001001871) have been published before. In addition, for the current project we compare 450K methylation data to nanopore sequencing based methylation profiles. These sequencing data will be accessible via European Genome-Phenome Archive (EGAS00001002213). Please also refer to https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-5795/files/E-MTAB05795.additional.1.zip for further information on the background of this multi-omics study.

2017-06-24 | E-MTAB-5797 | biostudies-arrayexpress

Expression profiling of the aging epidermis [RNA seq]

Project description:Whole transcriptome sequencing data generated from epidermal samples (suction blister roofs) of healthy female subjects between 21 and 76 years. Aim of the project was the investigation of non-linearities in the human aging progression using an integrative multi-omics analysis. RNA was extracted from suction blisters taken from the volar forearms of each subject, cDNA converted and then sequenced on an Illumina HiSeq 2500 (single-end, 50 bp) to an approximate sequencing depth of 100 million reads per sample.

2020-07-24 | E-MTAB-8995 | biostudies-arrayexpress

Neurulation of the cynomolgus monkey embryo achieved from 3D blastocyst culture [Bisulfite-Seq]

Project description:To further reveal the major cell types of developing pIVC embryos and underlying epigenetic dynamics, the optimized single-cell based multi-omics sequencing method scChaRM-seq was performed (Yan et al., 2021b). 1,862 single cells Bisulfite-seq datasets were further analyzed. We then performed multi-omics profiling analysis using data obtained from9 pIVC embryos at 8 sequential developmental stages.

2023-03-24 | GSE218524 | GEO

Project description:D Multi-omics

| PRJNA976937 | ENA

Neurulation of the cynomolgus monkey embryo achieved from 3D blastocyst culture [RNA-Seq]

Project description:To further reveal the major cell types of developing pIVC embryos and underlying epigenetic dynamics, the optimized single-cell based multi-omics sequencing method scChaRM-seq was performed (Yan et al., 2021b). After stringent filtration, 3,682 single cells RNA-seq datasets were further analyzed We then performed multi-omics profiling analysis using data obtained from9 pIVC embryos at 8 sequential developmental stages.

2023-03-24 | GSE218523 | GEO

RNA-seq of yeast cell cycle, used for absolute gene expression quantification

Project description:We use Saccharomyces cerevisiae to perform absolute quantitative multi-omics analysis to map interactions of different cellular processes during the yeast cell cycle.

2020-03-30 | E-MTAB-8565 | biostudies-arrayexpress

Integrative Analysis of Transcriptomic and Epigenomic Data to Reveal Regulation Patterns for Osteoporosis Risk [methylome]

Project description:In this study, we analyzed transcriptome gene expression microarray, epigenomic miRNA microarray and methylome sequencing data simultaneously in PBMs from 5 high hip BMD subjects and 5 low hip BMD subjects. Through integrating the transcriptomic and epigenomic data, firstly we identified BMD-related genetic factors, including 9 protein coding genes and 2 miRNAs, of which 3 genes (FAM50A, ZNF473 and TMEM55B) and one miRNA (hsa-mir-4291) showed the consistent association evidence from both gene expression and methylation data, and 3 genes (TMEM55B, RNF40 and ALDOA) were confirmed in the meta-analysis of 7 GWAS samples and GEnetic Factors for OSteoporosis consortium (GEFOS-2) GWAS results. Secondly in network analysis we identified an interaction network module with 12 genes and 11 miRNAs including AKT1, STAT3, STAT5A, FLT3, hsa-mir-141 and hsa-mir-34a which have been associated with BMD in previous studies. This module revealed the crosstalk among miRNAs, mRNAs and DNA methylation and showed four potential regulatory patterns of gene expression to influence the BMD status, including regulation by gene methylation, by miRNA and its methylation, by transcription factors and co-regulation by miRNA and gene methylation. In conclusion, the integration of multiple layers of omics can yield more in-depth results than analysis of individual omics data respectively. Integrative analysis from transcriptomics and epigenomic data improves our ability to identify causal genetic factors, and more importantly uncover functional regulation pattern of multi-omics for osteoporosis etiology. 5 high hip BMD subjects and 5 low hip BMD subjects

2014-10-22 | E-GEOD-62588 | biostudies-arrayexpress

Single-cell Multi-omics Sequencing and Analyses of Human Colorectal Cancer

Project description:Although genomic instability, epigenetic abnormality, and gene expression dysregulation are hallmarks of colorectal cancer, these features have not been simultaneously analyzed at single-cell resolution. Using optimized single-cell multi-omics sequencing together with multi-regional sampling of the primary tumor, lymphatic and distant metastases, we provide insights beyond intratumoral heterogeneity. Genome-wide DNA methylation levels were relatively consistent within a single genetic sub-lineage. The genome-wide DNA demethylation patterns of cancer cells were consistent in all 10 sequenced patients. Our work demonstrates the feasibility of reconstructing genetic lineages, and tracing their epigenomic and transcriptomic dynamics with single-cell multi-omics sequencing.

2018-11-29 | GSE97693 | GEO

Single nuclei RNA-seq and snATAC-seq multiome performed in WT and Dhx36 conditional KO hearts at postnatal day 7 (PD7)

Project description:In these experiments, we aimed to investigate the role of cardiomyocyte-specific deletion of the G-quadruplex resolvase Dhx36 in heart development and cardiomyocyte differentiation. To achieve this, we conducted multi-omics analysis using single-nuclei RNA sequencing (RNA-seq) and ATAC sequencing (ATAC-seq) on hearts from postnatal day 7 (PD7) wild-type (WT) and Dhx36 conditional knockout (cKO) mice. Our findings reveal that Dhx36 plays a critical role in the development of the cardiac conduction system (CCS) and in the differentiation of both CCS and working cardiomyocytes

2024-09-15 | E-MTAB-14442 | 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