Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: A modified method for whole exome resequencing from minimal amounts of starting DNA

PROVIDER: PRJEB2788 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	ERR058834_1.fastq.gz	Fastqsanger.gz
	ERR058834_2.fastq.gz	Fastqsanger.gz
	ERR058835_1.fastq.gz	Fastqsanger.gz
	ERR058835_2.fastq.gz	Fastqsanger.gz
	ERR058836_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 24

Similar Datasets

Project description:A modified method for whole exome resequencing from minimal amounts of starting DNA

| PRJEB2786 | ENA

WES

Project description:Exome sequencing from nanogram amounts of starting DNA: Comparing three approaches

| PRJEB6077 | ENA

Quantitative reduced representation bisulfite sequencing with unique molecular identifiers of single cell

Project description:Reduced representation bisulfite sequencing (RRBS) has been proven a powerful method in DNA methylome profiling. Since the initial development of this method, the RRBS protocol has been modified in order to optimize it for genomic coverage, starting material, and library-construction throughput, which has resulted in new methods such as enhanced RRBS (ERRBS), double-enzyme RRBS (dRRBS), gel-free and multiplexed RRBS (mRRBS), and single-cell RRBS (scRRBS). However, each of these methods has failed to address PCR-derived duplication artifacts, which can bias the results of DNA methylation analyses. To overcome the aforementioned complication, we developed quantitative RRBS (Q-RRBS), a method in which unique molecular identifiers (UMIs) are used to eliminate PCR-induced duplication. By performing Q-RRBS on varying amounts of starting material, we determined that duplication-induced artifacts were more severe when small quantities of the starting material were used. However, through using the UMIs, we successfully eliminated these artifacts. Our results demonstrate that Q-RRBS is an optimal strategy for DNA methylation profiling of single cells or samples containing ultra-trace amounts of cells.

2016-01-14 | GSE76863 | GEO

Candidate driver genes in Sѐzary syndrome

Project description:Illumina human Omni5Exome arrays were used to investigate CNVs in Sѐzary syndrome tumours as part of a larger study involving whole exome sequencing of the same samples and targeted resequencing of a further cohort.

2016-07-22 | GSE80650 | GEO

Plasmodium falciparum custom resequencing array testing and validation

Project description:A custom resequencing array for analysis of field isolates of plasmdium falciparum was created. Test of DNA with genotypes known at all loci genotyped by the microarray as well as test of accuracy correlation with amounts of DNA added to each array

2014-03-28 | GSE56305 | GEO

Candidate driver genes in SÑzary syndrome

Project description:Illumina human Omni5Exome arrays were used to investigate CNVs in SÑzary syndrome tumours as part of a larger study involving whole exome sequencing of the same samples and targeted resequencing of a further cohort. 16 Samples underwent SNP array including 10 tumour/gDNA matched samples that also underwent whole exome sequencing, public databases were used as further control data for calling CNVs.

2016-07-22 | E-GEOD-80650 | biostudies-arrayexpress

Genetically defined syngeneic mouse models of ovarian cancer as tools for the discovery of combination immunotherapy (Exome)

Project description:Purpose: There are three goals of this study: 1. To compare the genomic, exome and chromatin accessiblity profiles of the specific engineered fallopian tube cells of high-grade serous tubo-ovarian cancer (HGSC) models (this study) using whole-exome, whole-genome and ATAC-seq sequencing. Methods: For whole-exome analysis, genomic DNA was extracted from the cell lines mentioned below. Conclusions: We conclude that whole-exome, whole-genome and ATAC-seq characterization would expedite genetic network analyses and permit the dissection of complex biological functions.

2020-11-17 | GSE159253 | GEO

Super cChIP-seq, a robust and universal epigenetic profiling method using 10 cells

Project description:ChIP-seq is the standard technique to characterize the genome-wide epigenomic modifications, which requires millions of cells as starting material. Although some methods have recently reported to be suitable for epigenomic profiling with a small number of cells, there are still no methods capable of profiling both histone modifications and DNA methylation with extremely low input. Here, we developed a new method by supplementing carrier materials of chemically modified epigenetic markers and dUPT-containing DNA fragments during ChIP procedures. Using this strategy, we generated high-quality epigenomic profiles of both histone modifications (super cChIP-seq) and DNA methylation (super cMeDIP-seq) with as few as 10 cells. Thus, we provide a robust and straightforward universal approach for epigenomic profiling starting with extremely low input.

2024-04-07 | GSE136578 | GEO

Optimised linear amplification method for whole transcriptome analysis from low quantity RNA isolated from archival FFPE tissue

Project description:The study described a comprehensive high-fidelity method to successfully amplify low starting amounts of RNA extracted from FFPE tissue obtained from bronchial biopsies. Both amplified and unamplified RNA resulted in comparable gene expression for lung cancer and asthma samples.

2023-03-30 | GSE228217 | GEO

Genome-wide Chromatin Maps Derived from Limited Numbers of Hematopoietic Progenitors

Project description:Whole genome mapping of protein-DNA interactions can be performed by coupling chromatin immunoprecipitation (ChIP) with high-throughput sequencing (ChIP-Seq). However, current methods require large amounts of starting materials which precludes their application to rare cell types. Here, we combine a high-sensitivity ChIP assay with a novel library preparation procedure to map histone modifications in as few as 10,000 cells. We apply the technique to acquire genome-wide chromatin maps for an enriched population of hematopoietic progenitors, and thereby gain insight into their developmental program.

2010-07-01 | GSE22075 | 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