Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single Bacterial Cell Whole Genome Amplification

ABSTRACT: Single Bacterial Cell Whole Genome Amplification

PROVIDER: PRJEB2063 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	ERR022126_1.fastq.gz	Fastqsanger.gz
	ERR022126_2.fastq.gz	Fastqsanger.gz
	ERR022127_1.fastq.gz	Fastqsanger.gz
	ERR022127_2.fastq.gz	Fastqsanger.gz
	ERR022128_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 56

Similar Datasets

Comparison of seven single cell Whole Genome Amplification commercial kits using targeted sequencing

Project description:Advances in biochemical technologies have led to a boost in the field of single cell genomics. Observation of the genome at a single cell resolution is currently achieved by pre-amplification using whole genome amplification (WGA) techniques that differ by their biochemical aspects and as a result by biased amplification of the original molecule. Several comparisons between commercially available single cell dedicated WGA kits (scWGA) were performed, however, these comparisons are costly, were only performed on selected scWGA kit and more notably, are limited by the number of analyzed cells, making them limited for reproducibility analysis. We benchmarked an economical assay to compare all commercially available scWGA kits that is based on targeted sequencing of thousands of genomic regions, including highly mutable genomic regions (microsatellites), from a large cohort of human single cells (125 cells in total). Using this approach, we could analyze the genome coverage, the reproducibility of genome coverage and the error rate of each kit. Our experimental design provides an affordable and reliable comparative assay that simulates a real single cell experiment. Results demonstrate the need for a dedicated kit selection depending on the desired single cell assay.

2017-09-24 | E-MTAB-5968 | biostudies-arrayexpress

Comparison of seven single cell Whole Genome Amplification commercial kits using targeted sequencing

Project description:Comparison of seven single cell Whole Genome Amplification commercial kits using targeted sequencing

| PRJEB22132 | ENA

Plasmodium malariae selective whole genome amplification development

Project description:Plasmodium malariae selective whole genome amplification development

| PRJEB37746 | ENA

Whole genome amplification and whole genome sequencing of human single cells

Project description:Human single fibroblasts and T-lymphocytes were amplified using multiple annealing and looping-based amplification and multiple displacement amplification. Amplified products were next subjected to whole genome sequencing with the goal of performing a genetic variant analysis.

| EGAS00001003108 | EGA

Single Cell Whole Genome Amplification Technique Impacts the Accuracy of SNP Microarray Based Genotyping and Copy Number Analyses

2010-12-20 | GSE24690 | GEO

Bacterial whole genome sequencing

Project description:Bacterial whole genome sequencing Raw sequence reads

| PRJNA991232 | ENA

Whole genome amplification and de novo assembly of single bacterial cells.

Project description:BackgroundSingle-cell genome sequencing has the potential to allow the in-depth exploration of the vast genetic diversity found in uncultured microbes. We used the marine cyanobacterium Prochlorococcus as a model system for addressing important challenges facing high-throughput whole genome amplification (WGA) and complete genome sequencing of individual cells.Methodology/principal findingsWe describe a pipeline that enables single-cell WGA on hundreds of cells at a time while virtually eliminating non-target DNA from the reactions. We further developed a post-amplification normalization procedure that mitigates extreme variations in sequencing coverage associated with multiple displacement amplification (MDA), and demonstrated that the procedure increased sequencing efficiency and facilitated genome assembly. We report genome recovery as high as 99.6% with reference-guided assembly, and 95% with de novo assembly starting from a single cell. We also analyzed the impact of chimera formation during MDA on de novo assembly, and discuss strategies to minimize the presence of incorrectly joined regions in contigs.Conclusions/significanceThe methods describe in this paper will be useful for sequencing genomes of individual cells from a variety of samples.

| S-EPMC2731171 | biostudies-literature

mRNA-Seq Whole Transcriptome Analysis of a Single Cell

Project description:Here we modified a single cell whole transcriptome amplification method to make it capable of amplifying cDNAs as long as 3kb efficiently and unbiasedly. We combined this modified single cell cDNA amplification method with Applied Biosystems next generation sequencing SOLiD™ System to set up a single cell whole transcriptome assay. The modified amplification strategy allows us to amplify full-length cDNAs for most of the expressed genes. We show that it is feasible to get digital gene expression profiles at single cell resolution. This allows us to ask fundamental biological questions that could not be addressed previously, especially in the early embryonic development field, and to understand transcriptome complexity at the resolution of a single cell. gene expression profiling from two single wild-type oocytes, two single Dicer knockout oocyte, and one single Ago2 knockout oocyte

2009-02-23 | E-GEOD-14605 | biostudies-arrayexpress

Genotyping of human cell lines with amplification of single cell vs. non amplied products to examime the effect of allele bias during amplification

Project description:Single-cell human genome analysis using whole-genome amplified product is hampered by allele bias during amplification. Using an oligonucleotide SNP array, we examined the nature of the allele bias and its effect on the chromosomal copy number analysis. Experiment Overall Design: TB106, lymphoblastoid cell line; CMK11-5 and CMK86, cell line; WGA, whole-genome amplified from bulk DNA; SC, whole-genome amplified product from single cell. Genotype and copy number status were compared between non-amplified products and their single cell products.

2008-06-16 | E-GEOD-8567 | biostudies-arrayexpress

Single Cell Whole Genome Amplification Technique Impacts the Accuracy of SNP Microarray Based Genotyping and Copy Number Analyses

Project description:Methods of comprehensive microarray based analyses of single cell DNA are rapidly emerging. Whole genome amplification (WGA) remains a critical component for these methods to be successful. A number of commercially available WGA kits have been independently utilized in previous single cell microarray studies. However, direct comparison of their performance on single cells has not been conducted. The present study demonstrates that among previously published methods, a single cell GenomePlex WGA protocol provides the best combination of speed and accuracy for SNP microarray based copy number analysis when compared to a REPLI-g or GenomiPhi based protocol. Alternatively, for applications that do not have constraints on turn-around time and that are directed at accurate genotyping rather than copy number assignments, a REPLI-g based protocol may provide the best solution. Affymetrix SNP arrays were processed according to the manufacturer's directions on DNA extracted from human fibroblast cell lines and single fibroblast cells. Afflymetrix SNP array analysis was successfully completed on 46 lymphocyte single cell samples, 8 gDNA extracted from cell lines, 11 reference gDNA extracted from cell lines and 3 reference gDNA samples from the RMA of New Jersey DNA bank. GSM617116 to GSM617129: CEL files were processed using GTYPE version 4 (Affymetrix Inc., Genotyping Console 4.0 Manual) using the DM algorithm for genotype calls. Copy number and loss of heterozygosity were calculated from CHP files using CNAT version 4.1 (Affymetrix Inc., Genotyping Console 4.0 Manual) analysis against a reference set consisting of three normal females from in house gDNA bank, 11 normal females from Coriel cell lines and 16 normal females from the HapMap database (www.hapmap.org). The 16 normal females are NA10855, NA10863, NA11832, NA12057, NA12234, NA12717, NA12813, NA18505, NA18508, NA18517, NA19137, NA19152, NE00088, NE00091, NE00403, and NE01119.

2010-12-20 | E-GEOD-24690 | 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