Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Effect of Soil Sample Size on DNA Extraction

ABSTRACT: Effect of Soil Sample Size on DNA Extraction

PROVIDER: PRJNA911477 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

DNA Extraction

Project description:DNA extraction method targeted loci environmental

| PRJNA315949 | ENA

Effect of DNA extraction methods

Project description:Effect of DNA extraction methods on the determination of the structure of microbial communities in the phosphogypsum waste heap soil

| PRJEB12454 | ENA

DNA extraction method from alfalfa

Project description:DNA extraction method from alfalfa Metagenome

| PRJNA901244 | ENA

PJI extraction optimization

Project description:Optimization of prosthetic joint infection sample DNA extraction for Nanopore sequencing

| PRJEB42910 | ENA

Effect of DNA extraction method on brain DNA copy number estimation

Project description:We analysed DNA from two brain regions (cerebellum, CER and frontal cortex, FC) from 4 Parkinson's disease (PD) and 4 control brains on a custom design 8x60k Agilent aCGH targeted to PD genes. All brain DNA samples were hybridised with Agilent sex-matched reference DNA, and three CER samples were hybridised against the FC of the same brain, with a dye swap in one. Male and female reference DNA were hybridised to eachother. The samples were then re-extracted with additional protocols, and hybridisations were performed for two CER samples betwen DNA extracted from the same CER with different protocols, and for one brain between the CER and FC new extraction.

2016-02-01 | GSE71360 | GEO

DNA extraction benchmarking study for gut microbiata applications

Project description:The effect of DNA extraction methodology on gut microbiota research applications

| PRJEB14875 | ENA

Method DNA extraction Mars simulant soil

Project description:DNA extraction method for synthetic Mars soil

| PRJEB68335 | ENA

Negative and positive control samples - DNA extraction

Project description:References samples to the DNA extraction

| PRJEB39304 | ENA

The effects from DNA extraction methods on the evaluation of microbial diversity associated with human colonic tissue

Project description:Recent advances in (meta)genomic methods have provided new opportunities to examine host-microbe-environment interactions in the human gut. While opportunities exist to extract DNA from freshly sourced colonic tissue there are potentially valuable sources of DNA from historical studies that might also be examined. We examined how four different tissue DNA extraction methods employed in past clinical trials might impact the recovery of microbial DNA from a colonic tissue sample as assessed using a custom designed phylogenetic microarray for human gut bacteria and archaebacteria. While all methods of DNA extraction produced similar phylogenetic profiles some extraction specific biases were also observed. Real time PCR analysis targeting several bacterial groups substantiated this observation. These data suggest that while the efficacy of different DNA extraction methods differs somewhat all the methods tested produce an accurate representation of microbial diversity. This suggests that DNA samples archived in biobanks should be suitable for retrospective analyses.

2010-01-01 | GSE18420 | GEO

Effects of sample size on differential gene expression, rank order and prediction accuracy of a gene signature

Project description:Gene expression profiles were generated from muscle biopsies from 134 individuals, and differences in expression based on sex were explored. Top differentially expressed gene lists are often inconsistent between studies and it has been suggested that small sample sizes contribute to lack of reproducibility and poor prediction accuracy in discriminative models. We considered sex differences (69♂, 65♀) in 134 human skeletal muscle biopsies using DNA microarray. The full dataset and subsamples (n= 10 (5♂, 5♀) to n=120 (60♂, 60♀)) thereof were used to assess the effect of sample size on the differential expression of single genes, gene rank order and prediction accuracy. Using our full dataset (n=134), we identified 717 differentially expressed transcripts (p-value < 0.0001; false discovery rate < 0.006) and we were able to predict sex with 92% accuracy, both within our dataset and on external datasets. Both p-values and rank order of top differentially expressed genes became more variable using smaller subsamples. For example, at n=10 (5♂, 5♀), no gene was considered differentially expressed at p<0.0001 and prediction accuracy was ~50% (no better than chance). We found that sample size clearly affects microarray analysis results; small sample sizes result in unstable gene lists and poor prediction accuracy. We anticipate this will apply to other phenotypes, in addition to sex.

2014-05-15 | GSE41726 | 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