Normalization and analysis of DNA microarray data by self-consistency and local regression
A robust semi-parametric normalization technique has been developed, based on the assumption that the large majority of genes will not have their relative expression levels changed from one treatment group to the next, and on the assumption that departures of the response from linearity are small and slowly varying. The method was tested using data simulated under various error models and it performs well.
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[
"009:25"
]
|
| contactPoint |
{
"fn": "NIH",
"@type": "vcard:Contact",
"hasEmail": "mailto:info@nih.gov"
}
|
| description | A robust semi-parametric normalization technique has been developed, based on the assumption that the large majority of genes will not have their relative expression levels changed from one treatment group to the next, and on the assumption that departures of the response from linearity are small and slowly varying. The method was tested using data simulated under various error models and it performs well. |
| distribution |
[
{
"@type": "dcat:Distribution",
"title": "Official Government Data Source",
"mediaType": "text/html",
"description": "Visit the original government dataset for complete information, documentation, and data access.",
"downloadURL": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC126242/"
}
]
|
| identifier | https://healthdata.gov/api/views/exke-snpu |
| issued | 2025-07-14 |
| keyword |
[
"dna-microarray",
"gene-expression",
"nih",
"normalization-method",
"statistical-analysis"
]
|
| landingPage | https://healthdata.gov/d/exke-snpu |
| modified | 2025-09-06 |
| programCode |
[
"009:033"
]
|
| publisher |
{
"name": "National Institutes of Health",
"@type": "org:Organization"
}
|
| theme |
[
"NIH"
]
|
| title | Normalization and analysis of DNA microarray data by self-consistency and local regression |
