CoNIFER uses Exome sequencing data to find CNV and genotype the copy-number of duplicated genes. As exome capture reactions are subject to strong and systematic capture biases between sample batches, we implemented Singular value decomposition (SVD) to eliminate these biases in exome data.
It is to detect rare population-level variants. It's not for CNA.
- Python 2.7 above and Python 3 is not supported yet.
- NumPy: vector calculation
- PyTables: data store in HDF5
- pysam: BAM file parsing
- matplotlib: Duplication/deletion region visualization
- Create RPKM values for all samples BAM
- Analyze all RPKM values for all samples and create SVD-ZRPKM values.
- Call CNV by SVD-ZRPKM
- Visualize CNV region
Incoming Links #
Related Articles (Article 0) #
Related Medical Scholarly Articles (MedicalScholarlyArticle 1) #
- An evaluation of copy number variation detection tools from whole-exome sequencing data
- Gene-based comparative analysis of tools for estimating copy number alterations using whole-exome sequencing data
Suggested Pages #
- 0.154 ngCGH
- 0.088 Allele-specific copy number profiling by next-generation DNA sequencing
- 0.066 falcon
- 0.052 SAAS-CNV: A Joint Segmentation Approach on Aggregated and Allele Specific Signals for the Identification of Somatic Copy Number Alterations with Next-Generation Sequencing Data
- 0.035 AscatNgs
- 0.027 CODEX
- 0.025 C
- 0.025 Programming language
- 0.025 SAM
- More suggestions...