Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: Metabarcoding by Capture using a Single COI probe

PROVIDER: PRJNA472431 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR7193580_1.fastq.gz	Fastqsanger.gz
	SRR7193580_2.fastq.gz	Fastqsanger.gz
	SRR7193581_1.fastq.gz	Fastqsanger.gz
	SRR7193581_2.fastq.gz	Fastqsanger.gz
	SRR7193573_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 18

Similar Datasets

Project description:Oligochaete COI metabarcoding

| PRJNA548862 | ENA

Single Molecule Molecular Inversion Probe Capture Developed Using the CIViC Database

Project description:Single Molecule Molecular Inversion Probe Capture Developed Using the CIViC Database

| PRJNA562571 | ENA

Single Molecule Molecular Inversion Probe Capture Developed Using the CIViC Database

Project description:Single Molecule Molecular Inversion Probe Capture Developed Using the CIViC Database

| PRJNA562572 | ENA

Project description:Grand Lake Meadows COI metabarcoding

| PRJNA640405 | ENA

eDNA metabarcoding vs. DNA sequence-capture

Project description:Comparing diversity levels in environmental samples: DNA sequence capture vs. metabarcoding approaches using 18S and COI genes

| PRJEB35354 | ENA

Project description:Comparing diversity levels in environmental samples: DNA sequence capture and metabarcoding approaches using 18S and COI genes

| PRJNA634612 | ENA

Effect of methyl jasmonate treatment on rice leaves of wild-type and rice COI mutatns

Project description:Analysis of leaves of wild-type and rice COI mutants treated with methyl jasmonate (MeJA). Results provide the role of rice COI on response to jasmonic acid.

2022-06-11 | GSE205750 | GEO

Project description:COI metabarcoding from benthos and water

| PRJNA564750 | ENA

Well-ST-seq: cost-effective and cellular level spatial transcriptomics with high RNA capture efficiency

Project description:Spatial transcriptomic technologies are promising tools to reveal fine anatomical profiles of tissues. In the case of methodologies utilizing barcoded probe arrays, achieving a balance among probe barcoding complexity, cost, gene capture sensitivity, and spatial resolution is crucial for accelerating the spreading speed of spatial transcriptomic in basic science and clinical work. Here, we developed spatially cellular-level RNA-capture probe arrays using miniaturized microfluidic and microarray technologies. By leveraging the predetermined and cost-effective probe fixation characteristics of this methodology, we significantly reduced the consumable cost of the probe array to $0.31/mm2 and fabrication time to approximately 2 hours. Furthermore, the modification of the RNA-capture probe on sequencing slides by microfluidic chip does not rely on large imaging or printing instruments. Notably, the efficiency of the transcript captured by the probe array is even comparable to conventional single-cell RNA sequencing. Based on this technology, the stacked three-dimensional transcriptome atlas and the spatial cell heterogeneity of mouse brains were successfully visualized. Taken together, we present an experimental and analytical framework for the spatial investigation of mouse brain structures and cell phenotypes.

2024-05-01 | GSE247834 | GEO

Project description:'Comparison of environmental DNA and bulk-sample metabarcoding using highly degenerate COI primers

| PRJNA480165 | ENA