Sample Normalization


Quantile normalization


Before and after normalization.

Normalization impact


CNV ratio: After/before number of CNVs.

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.