gallery


Long mock prediction.

iPsychCNV prediction.

Gada prediction.

PennCNV prediction.



Hotspot visual inspection.

Example of true hotspot duplication (CN=3) on real data. Plot data from multiple CNVs in a hotspots.




PennCNV and iPsychCNV on DBS data: Hotspots and telomere regions.

DBS data from chromosome 16 from PennCNV and iPsychCNV. Example of hotspots and false positive at telomere region.




PennCNV on mock data: Telomere regions.

Mock data example of false positive prediction on telomere regions by PennCNV.




PennCNV and iPsychCNV: DBS and blood data.

iPsychCNV and PennCNV prediction on blood and DBS data. Example of large number of false positives on DBS data, specially from PennCNV.




Mock data: Hotspots and CNV prediction.

CNV prediction from iPsychCNV and hotspots on mock data for all 22 autosome chromosomes.



Single CNV plot for four copy-number states (CN=0, 1, 3 and 4).

Example of mock CNV with CN = 0.

Example of mock CNV with CN = 1.

Example of mock CNV with CN = 3.

Example of mock CNV with CN = 4.



Example of single CNV plot false positive calls.

False positive CNV called by PennCNV on DBS data.

False positive CNV called by PennCNV mock data, simulating telomere region.


Example of false positives on chromosome 19 from PennCNV, specially on short arm (high GC content).

False positive CNVs called by PennCNV on DBS data.

Challenges

Amplified DNA from dried blood spots offers number of challenges for copy number of variation detection. Here we describe some of the challenges one can find working with DBS data.

Tools

iPsychCNV package offers a series of tools that can be used in the CNV prediction pipeline, but also independent with other programs.

Classification

Evaluation of CNV prediction performance is an important step for methods comparison. Here we describe how binary classification is used to evaluate the method performance.

Methods

iPsychCNV uses many different methods to perform a series of functions. Here we describe in detail the methods used by iPsychCNV.

  • Github

    iPsychCNV is an open source R package project. People are welcome to give suggestions, code new functions and/or improve existing ones. The source code is available at Github .

  • About iPsychCNV

    iPsychCNV is a method to find copy number variation from amplified DNA from dried blood spots on Illumina SNP array. It is designed to handle large variation on Log R ratio, and uses B allele frequency to improve CNV calls. iPsychCNV is an open source project on Github

  • About iPSYCH

    The project will study five specific mental disorders; autism, ADHD, schizophrenia, bipolar disorder and depression. All disorders are associated with major human and societal costs all over the world. The iPSYCH project will study these disorders from many different angles, ranging from genes and cells to population studies, from fetus to adult, from cause to symptoms of the disorder, and this knowledge will be combined in new ways across scientific fields, visit iPSYCH.