CoNVaDING (Copy Number Variation Detection In Next-generation sequencing Gene panels) is designed for small (single-exon) copy number variation (CNV) detection in high coverage next-generation sequencing (NGS) data, such as obtained by analysis of smaller targeted gene panels.
CoNVaDING makes use of a group of (at least 30) possible control samples from which the samples with the most similar overall pattern are selected as control samples. These samples are then used for read-depth normalization on all (autosomal) targets and on all targets per gene. CNV prediction is based on a combination of ratio scores and Z-scores of the sample of interest compared to the selected control samples.
Quality (QC) metrics are calculated per sample and per analyzed target.
Output is generated on three levels:
• longlist: This list contains all calls, disregarding the target quality.
• shortlist: This list contains a subset of the longlist, filtered on within sample target QC metrics.
• final list: This list contains a subset of the shortlist, filtered on target QC metrics obtained from other samples.
CoNVaDING has been written for use of CNV detection in high coverage NGS data (at least ~200x). With lower coverages it might still work, but more targets will fail QC metrics.
The program is written in perl and has dependencies on specific perl libraries as well as on samtools.
Manuscript:
Source code:
Documentation:
Easybuild:
CoNVaDING makes use of a group of (at least 30) possible control samples from which the samples with the most similar overall pattern are selected as control samples. These samples are then used for read-depth normalization on all (autosomal) targets and on all targets per gene. CNV prediction is based on a combination of ratio scores and Z-scores of the sample of interest compared to the selected control samples.
Quality (QC) metrics are calculated per sample and per analyzed target.
Output is generated on three levels:
• longlist: This list contains all calls, disregarding the target quality.
• shortlist: This list contains a subset of the longlist, filtered on within sample target QC metrics.
• final list: This list contains a subset of the shortlist, filtered on target QC metrics obtained from other samples.
CoNVaDING has been written for use of CNV detection in high coverage NGS data (at least ~200x). With lower coverages it might still work, but more targets will fail QC metrics.
The program is written in perl and has dependencies on specific perl libraries as well as on samtools.
Manuscript:
Source code:
Documentation:
Easybuild: