Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Experimental and Bioinformatics considerations in cancer application of single cell genomics

ABSTRACT: Experimental and Bioinformatics considerations in cancer application of single cell genomics

PROVIDER: PRJEB22052 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	ERR2274750_1.fastq.gz	Fastqsanger.gz
	ERR2274750_2.fastq.gz	Fastqsanger.gz
	ERR2274231_1.fastq.gz	Fastqsanger.gz
	ERR2274231_2.fastq.gz	Fastqsanger.gz
	ERR2275111_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 186

Similar Datasets

Experimental and bioinformatics considerations in cancer application of single cell genomics.

Project description:Single cell genomics offers an unprecedented resolution to interrogate genetic heterogeneity in a patient's tumour at the intercellular level. However, the DNA yield per cell is insufficient for today's sequencing library preparation protocols. This necessitates DNA amplification which is a key source of experimental noise. We provide an evaluation of two protocols using micro-fluidics based amplification for whole exome sequencing, which is an experimental scenario commonly used in single cell genomics. The results highlight their respective biases and relative strengths in identification of single nucleotide variations. Towards this end, we introduce a workflow SoVaTSiC, which allows for quality evaluation and somatic variant identification of single cell data. As proof of concept, the framework was applied to study a lung adenocarcinoma tumour. The analysis provides insights into tumour phylogeny by identifying key mutational events in lung adenocarcinoma evolution. The consequence of this inference is supported by the histology of the tumour and demonstrates usefulness of the approach.

| S-EPMC7788095 | biostudies-literature

Application of single-cell genomics

Project description:Comprehensive application of single-cell genomics

| PRJEB12266 | ENA

HOPE-Genomics Intervention for the Improvement of Cancer Patient Knowledge of Genomics

Project description:This clinical trial studies the effectiveness of a web-based cancer education tool called Helping Oncology Patients Explore Genomics (HOPE-Genomics) in improving patient knowledge of personal genomic testing results and cancer and genomics in general. HOPE-Genomics is a web-based education tool that teaches cancer/leukemia patients, and patients who may be at high-risk for developing cancer, about genomic testing and provide patients with information about their own genomic test results. The HOPE-Genomics tool may improve patient’s genomic knowledge and quality of patient-centered care. In addition, it may also improve education and care quality for future patients.

| 2378933 | ecrin-mdr-crc

Replicates, Read Numbers, and Other Important Experimental Design Considerations for Microbial RNA-seq Identified Using Bacillus thuringiensis Datasets.

Project description:RNA-seq has recently become a popular choice for gene expression studies. It is revolutionizing the fields of genomics and transcriptomics by enabling a wide range of applications along with high genome coverage and the ability to detect weakly expressed genes, which makes it an attractive alternative to microarrays. However, the field of RNA-Seq analysis is still evolving. In this study transcriptomic data from Bacillus thuringiensis strains ATCC10792 and CT43, grown in two Luria broth medium lots on four dates was obtained from Illumina High-Seq2000 and analyzed using DESeq2. Genome coverages across samples ranged from 87-450X with medium lots and culture dates as major variation sources. Significantly differentially expressed genes (5% FDR, two-fold change) were detected between cultures grown in different medium lots as well as on different dates for both ATCC10792 and CT43. Genes related to iron acquisition and metabolism were also consistently differentially expressed for both strains, in different media lots. RNA-seq is highly sensitive and can identify differential gene expression at predictive biology levels. The noise in data can be controlled and minimized with appropriate experimental design, number of replicates and reads. Here we outline some experimental design parameters for an efficient and cost effective microbial transcriptomics study.

2016-07-13 | GSE71189 | GEO

Canadian Genomics R&D Initiative on AMR One Health -- Experimental

Project description:Canadian Genomics R&D Initiative on AMR One Health -- Experimental Genome sequencing and assembly

| PRJNA1143527 | ENA

Bioinformatics prediction and experimental verification of a novel microRNA for myocardial fibrosis after myocardial infarction in rats

Project description:Bioinformatics prediction and experimental verification of a novel microRNA for myocardial fibrosis after myocardial infarction in rats

| PRJNA858539 | ENA

Application of the ISM bioinformatics platform in detection of new therapeutic targets and potential therapeutic molecules

Project description:Application of EIIP / ISM bioinformatics platform in detection of new therapeutic targets and potential therapeutic molecules. Study of the molecular basis of rare human diseases

2020-12-16 | PRJEB42044 | EVA

CNB Lipid Rafts reAnalysis. - This dataset represents an example for a textbook: Genomics and Proteomics for Clinical Discovery and Development

Project description:This dataset represents an example for a textbook: Genomics and Proteomics for Clinical Discovery and Development, http://www.springer.com/life+sciences/systems+biology+and+bioinformatics/book/978-94-017-9201-1 ReAnalysis of the work Proteomic analysis of apical microvillous membranes of syncytiotrophoblast cells reveals a high degree of similarity with lipid rafts. Experiment described at: Paradela et al. J Proteome Res. 2005 Nov-Dec;4(6):2435-41 PMID: 16335998. For protein annotations, revise, Medina-Aunon et at. Proteomics. 2010 Sep;10(18):3262-71 PMID: 20707001. Genomics and Proteomics for Clinical Discovery and Development Translational Bioinformatics Volume 6, 2014, pp 41-68

2014-07-14 | PXD000744 | Pride

P application

Project description:P application Raw sequence reads

| PRJNA932121 | ENA

N application

Project description:N application Raw sequence reads

| PRJNA552400 | ENA