Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Soil/sediment of a riparian zone

ABSTRACT: soil/sediment Raw sequence reads

PROVIDER: PRJNA694565 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR13617318_1.fastq.gz	Fastqsanger.gz
	SRR13617318_2.fastq.gz	Fastqsanger.gz
	SRR13617319_1.fastq.gz	Fastqsanger.gz
	SRR13617319_2.fastq.gz	Fastqsanger.gz
	SRR13617320_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 72

Similar Datasets

soil and sediment in reservoir riparian zones

Project description:soil and sediment Raw sequence reads

| PRJNA888823 | ENA

soil sediment

Project description:soil sediment Raw sequence reads

| PRJNA1018281 | ENA

High-throughput 16S rRNA amplicon pyrosequencing of contaminated aquifer sediment

Project description:Contaminated aquifer (Dusseldorf-Flinger, Germany) templates extracted from 5 sediment depths ranging between 6.4 and 8.4 m below ground and over 3 years of sampling were amplified for amplicon pyrosequencing using the primers Ba27f (5’-aga gtt tga tcm tgg ctc ag-3’) and Ba519r (5’- tat tac cgc ggc kgc tg-3’), extended as amplicon fusion primers with respective primer A or B adapters, key sequence and multiplex identifiers (MID) as recommended by 454/Roche. Amplicons were purified and pooled as specified by the manufacturer. Emulsion PCR (emPCR), purification of DNA-enriched beads and sequencing run were performed following protocols and using a 2nd generation pyrosequencer (454 GS FLX Titanium, Roche) as recommended by the developer. Quality filtering of the pyrosequencing reads was performed using the automatic amplicon pipeline of the GS Run Processor (Roche), with a slight modification concerning the valley filter (vfScanAllFlows false instead of TiOnly) to extract the sequences. Demultiplexed raw reads were furhter trimmed for quality and lenght (>250 bp).

2012-11-11 | GSE25345 | GEO

sediment and soil

Project description:sediment and soil Raw sequence reads

| PRJNA859394 | ENA

Baiyangdian DNRA riparian zone

Project description:Baiyangdian DNRA riparian zone Raw sequence reads

| PRJNA605093 | ENA

soil and sediment of Beijing Miyun reservoir riparian zone

Project description:soil and sediment of Beijing Miyun reservoir riparian zone Genome sequencing and assembly

| PRJNA689115 | ENA

High-throughput 16S rRNA amplicon pyrosequencing of contaminated aquifer sediment

2012-11-11 | E-GEOD-25345 | biostudies-arrayexpress

sediment metagenome

Project description:Soil sediment Raw sequence reads

| PRJNA312261 | ENA

Soil and freshwater sediment enrichment

Project description:Soil and freshwater sediment enrichment Raw sequence reads

| PRJNA1010380 | ENA

RNA-Seq Analysis to confirm Different Transcriptomic Profiles of Soil-Derived Functional Module Consortia.

Project description:Purpose: Deconstructing the soil microbiome into reduced-complexity functional modules represents a novel method of microbiome analysis. The goals of this study are to confirm differences in transcriptomic patterns among five functional module consortia. Methods: mRNA profiles of 3 replicates each of functional module enrichments of soil inoculum in M9 media with either 1) xylose, 2) n-acetylglucosamine, 3) glucose and gentamycin, 4) xylan, or 5) pectin were generated by sequencing using an Illumina platform (GENEWIZ performed sequencing). Sequence reads that passed quality filters were aligned to a soil metagenome using Burrows Wheeler Aligner. Resulting SAM files were converted to raw reads using HTSeq, and annotated using Uniref90 or EGGNOG databases. Results: To reduce the size of the RNA-Seq counts table and increase its computational tractability, transcripts containing a minimum of 75 total counts, but no more than 3 zero counts, across the 15 samples were removed. The subsequent dataset was normalized using DESeq2, resulting in a dataset consisting of 6947 unique transcripts across the 15 samples, and 185,920,068 reads. We identified gene categories that were enriched in a sample type relative to the overall dataset using Fisher’s exact test. Conclusions: our dataset confirms that the functional module consortia generated from targeted enrichments of a starting soil inoculum had distinct functional trends by enrichment type.

2020-01-14 | GSE143587 | 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