A method (100) for determining a copy number variation (CNV) profile, comprising: (i) receiving (110) sparse genome sequencing data; (ii) determining (120) an unadjusted CNV profile; (iii) normalizing (130) the unadjusted CNV profile; (iv) receiving (140) a range for possible ploidy and for a possible contamination rate; (v) determining (150) adjusted segmentation values for the CNV profile; (vi) determining (160) a plurality of adjustment scores comprising a distance between an adjusted segmentation value and a closest whole integer for a CNV call; (vii) comparing (170) the determined plurality of adjustment scores to one or more predetermined factors for selecting a CNV profile best fit; (viii) selecting (180) one of the plurality of adjustment scores as a best fit for the copy number variation profile of the tumor cells of the tumor; (ix) generating (190) an adjusted CNV profile report; and (x) reporting (192) the generated adjusted CNV profile report.

A method (100) for determining a copy number variation (CNV) profile, comprising: (i) receiving (110) sparse genome sequencing data; (ii) determining (120) an unadjusted CNV profile; (iii) normalizing (130) the unadjusted CNV profile; (iv) receiving (140) a range for possible ploidy and for a possible contamination rate; (v) determining (150) adjusted segmentation values for the CNV profile; (vi) determining (160) a plurality of adjustment scores comprising a distance between an adjusted segmentation value and a closest whole integer for a CNV call; (vii) comparing (170) the determined plurality of adjustment scores to one or more predetermined factors for selecting a CNV profile best fit; (viii) selecting (180) one of the plurality of adjustment scores as a best fit for the copy number variation profile of the tumor cells of the tumor; (ix) generating (190) an adjusted CNV profile report; and (x) reporting (192) the generated adjusted CNV profile report.

Computer software products, methods, and systems are described which provide functionality to a user conducting experiments designed to detect and/or identify genetic sequences and other characteristics of a genetic sample, such as, for instance, gene copy number and aberrations thereof. The presently described software allows the user to interact with a graphical user interface which depicts the genetic information obtained from the experiment. The presently disclosed methods and software are related to bioinformatics and biological data analysis. Specifically, provided are methods, computer software products and systems for analyzing and visually depicting genotyping data on a screen or other visual projection. The presently disclosed methods and software allow the user conducting the experiment to differentially filter complex genetic data and information by varying genetic parameters and removing or highlighting visually various regions of genetic data of interest (CytoRegions). These differential filters may be applied by the user to the entire set of genetic data and/or only to the specific CytoRegions of interest.

A method to correct amplification bias in amplicon sequencing is disclosed. Amplification efficiency is not constant among different loci in a sample, nor for the same locus in different samples. Differences in 3′-end stability, primer Tm, amplicon length, amplicon GC content, and GC content of amplicon flanking regions all may contribute to amplification bias. Such bias interferes with accurate calculation of copy number for a genomic region of interest and hinders the application of amplicon sequencing for detection of minor copy number variation. The methods of the invention allow correction of amplification bias and enable detection of minor copy number variation using amplicon sequence data.

A method to correct amplification bias in amplicon sequencing is disclosed. Amplification efficiency is not constant among different loci in a sample, nor for the same locus in different samples. Differences in 3′-end stability, primer Tm, amplicon length, amplicon GC content, and GC content of amplicon flanking regions all may contribute to amplification bias. Such bias interferes with accurate calculation of copy number for a genomic region of interest and hinders the application of amplicon sequencing for detection of minor copy number variation. The methods of the invention allow correction of amplification bias and enable detection of minor copy number variation using amplicon sequence data.

Disclosed are methods for determining at least one sequence of interest of a fetus of a pregnant mother. In various embodiments, the method can determine one or more sequences of interest in a test sample that comprises a mixture of fetal cellular DNA and mother-and-fetus cfDNA. In some embodiments, methods are provided for determining whether the fetus has a genetic disease. In some embodiments, methods are provided for determining whether the fetus is homozygous in a disease causing allele when the mother is heterozygous of the same allele. In some embodiments, methods are provided for determining whether the fetus has a copy number variation (CNV) or a non-CNV genetic sequence anomaly.

Methods and systems for determining copy number variants are disclosed. An example method can comprise applying a sample grouping technique to select reference coverage data, normalizing sample coverage data comprising a plurality of genomic regions, and fitting a mixture model to the normalized sample coverage data based on the selected reference coverage data. An example method can comprise identifying one or more copy number variants (CNVs) according to a Hidden Markov Model (HMM) based on the normalized sample coverage data and the fitted mixture model. An example method can comprise outputting the one or more copy number variants.

Methods and systems for determining copy number variants are disclosed. An example method can comprise applying a sample grouping technique to select reference coverage data, normalizing sample coverage data comprising a plurality of genomic regions, and fitting a mixture model to the normalized sample coverage data based on the selected reference coverage data. An example method can comprise identifying one or more copy number variants (CNVs) according to a Hidden Markov Model (HMM) based on the normalized sample coverage data and the fitted mixture model. An example method can comprise outputting the one or more copy number variants.

Provided are a method of detecting chromosomal aneuploidy of a targeted fetal chromosome, and a computer-readable medium having recorded thereon a program to be applied to performing the method. According to the present disclosure, fetal chromosomal aneuploidy may be non-invasively and prenatally diagnosed with excellent sensitivity and specificity.

Provided are a method of detecting chromosomal aneuploidy of a targeted fetal chromosome, and a computer-readable medium having recorded thereon a program to be applied to performing the method. According to the present disclosure, fetal chromosomal aneuploidy may be non-invasively and prenatally diagnosed with excellent sensitivity and specificity.