NanoStringNormCNV

NanoStringNormCNV performs normalization and copy number variation (CNV) detection on raw NanoString System data to identify CNVs associated with diseases such as cancer.

Key Features:

• Pre-Processing and Quality Control: Implements pre-processing and quality-control algorithms for raw NanoString System data to ensure high-quality inputs for downstream analysis.
• Normalization: Provides normalization techniques to adjust for technical variability and make CNV measurements comparable across samples.
• Copy Number Variation Detection: Facilitates detection of copy number variations using computational methods to identify genetic alterations.
• Data Visualization and Reporting: Includes visualization tools to generate graphical representations and reports of CNV results.

Scientific Applications:

• Cancer research: Applied to study CNVs implicated in tumorigenesis and other cancer-related genetic alterations.
• Prostate tumor dataset demonstration: Demonstrated on a dataset of 96 genes from 41 prostate tumor samples and 24 matched normal samples to identify genetic variations relevant to cancer development.

Methodology:

Implemented in R and provides pre-processing, normalization, CNV detection, and visualization algorithms.