Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Mock community metagenomes and 16S rRNA amplicons

ABSTRACT: Quantification of mock microbial communities with metagenomes, 16S rRNA gene amplicons and metaproteomics

OTHER RELATED OMICS DATASETS IN: PXD006118PXD006366PXD006343

PROVIDER: PRJEB19901 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	ERR1877480_1.fastq.gz	Fastqsanger.gz
	ERR1877480_2.fastq.gz	Fastqsanger.gz
	ERR1877490_1.fastq.gz	Fastqsanger.gz
	ERR1877490_2.fastq.gz	Fastqsanger.gz
	ERR1877481_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 90

Similar Datasets

Quantification of mock microbial communities with metagenomes, 16S rRNA gene amplicons and metaproteomics

Project description:In this study we developed metaproteomics based methods for quantifying taxonomic composition of microbiomes (microbial communities). We also compared metaproteomics based quantification to other quantification methods, namely metagenomics and 16S rRNA gene amplicon sequencing. The metagenomic and 16S rRNA data can be found in the European Nucleotide Archive (Study number: PRJEB19901). For the method development and comparison of the methods we analyzed three types of mock communities with all three methods. The communities contain between 28 to 32 species and strains of bacteria, archaea, eukaryotes and bacteriophage. For each community type 4 biological replicate communities were generated. All four replicates were analyzed by 16S rRNA sequencing and metaproteomics. Three replicates of each community type were analyzed with metagenomics. The "C" type communities have same cell/phage particle number for all community members (C1 to C4). The "P" type communities have the same protein content for all community members (P1 to P4). The "U" (UNEVEN) type communities cover a large range of protein amounts and cell numbers (U1 to U4). We also generated proteomic data for four pure cultures to test the specificity of the protein inference method. This data is also included in this submission.

2017-05-12 | PXD006118 | Pride

Soil 16S rRNA amplicons

Project description:Soil 16S rRNA amplicons Raw sequence reads

| PRJNA523632 | ENA

SYBH 16S rDNA/rRNA amplicons

Project description:SYBH 16S rDNA/rRNA amplicons Raw sequence reads

| PRJNA958612 | ENA

16S rRNA and mcrA amplicons

Project description:16S rRNA and mcrA amplicons Raw sequence reads

| PRJNA821506 | ENA

Evaluation of in-field Nanopore sequencing of 16S rRNA genes and metagenomes using mock communities

Project description:Evaluation of in-field Nanopore sequencing of 16S rRNA genes and metagenomes using mock communities

| PRJEB30868 | ENA

Evaluation of 16S rRNA Databases for Taxonomic Assignments Using Mock Community.

Project description:Taxonomy identification is fundamental to all microbiology studies. Particularly in metagenomics, which identify the composition of microorganisms using thousands of sequences, its importance is even greater. Identification is inevitably affected by the choice of database. This study was conducted to evaluate the accuracy of three widely used 16S databases, Greengenes, Silva, and EzBioCloud, and to suggest basic guidelines for selecting reference databases. Using public mock community data, each database was used to assign taxonomy and to test its accuracy. We showed that EzBioCloud performs well compared to other existing databases.

| S-EPMC6440677 | biostudies-literature

MinION™ Nanopore Sequencing of Skin Microbiome 16S and 16S-23S rRNA Gene Amplicons.

Project description:Human skin microbiome dysbiosis can have clinical consequences. Characterizing taxonomic composition of bacterial communities associated with skin disorders is important for dermatological advancement in both diagnosis and novel treatments. This study aims to analyze and improve the accuracy of taxonomic classification of skin bacteria with MinION™ nanopore sequencing using a defined skin mock community and a skin microbiome sample. We compared the Oxford Nanopore Technologies recommended procedures and concluded that their protocols highly bias the relative abundance of certain skin microbiome genera, most notably a large overrepresentation of Staphylococcus and underrepresentation of Cutibacterium and Corynebacterium. We demonstrated that changes in the amplification protocols improved the accuracy of the taxonomic classification for these three main skin bacterial genera. This study shows that MinION™ nanopore could be an efficient technology for full-length 16S rRNA sequencing; however, the analytical advantage is strongly influenced by the methodologies. The suggested alternatives in the sample processing improved characterization of a complex skin microbiome community using MinION™ nanopore sequencing.

| S-EPMC8766866 | biostudies-literature

Antarctic Peninsula 16S rRNA metagenomes

Project description:16S rRNA Gene Amplicon based metagenomes of microbial soil communities in the Antarctic Peninsula

| PRJEB44228 | ENA

Surface water 16S rRNA gene amplicons Raw sequence reads

Project description:Surface water 16S rRNA gene amplicons

| PRJNA507089 | ENA

Project description:EMG produced TPA metagenomics assembly of PRJEB19901 data set (Quantification of mock microbial communities with metagenomes, 16S rRNA gene amplicons and metaproteomics).

| PRJEB43811 | ENA

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