Methods for detecting copy-number variations in next-generation sequencing

• Main Authors: Ivanov, Dmitri, Xu, Zhenyu
• Format: Patent
• Language: English
• Published: 23.12.2021
• Subjects: BEER; BIOCHEMISTRY; CHEMISTRY; COMPOSITIONS OR TEST PAPERS THEREFOR; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL ORENZYMOLOGICAL PROCESSES; ENZYMOLOGY; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS; MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEICACIDS OR MICROORGANISMS; METALLURGY; MICROBIOLOGY; MUTATION OR GENETIC ENGINEERING; PHYSICS; PROCESSES OF PREPARING SUCH COMPOSITIONS; SPIRITS; VINEGAR; WINE

Copy Number Variants (CNV) detection methods described herein may efficiently integrate CNV detection into the workflow for a next generation sequencer (NGS) data processing, in parallel with SNP and INDEL variant calling. CNV detection methods as described herein may be performed by analyzing the coverage pattern across a suitable set of genomic regions or amplicons and across a batch of samples from different patients. The proposed methods do not require the use of specifically chosen reference samples as inputs to the workflow, but rather automatically select a set of reference samples from the same batch, for each sample being tested. The CNV detection methods may reliably detect CNVs in a set of samples without prior assumptions about the CNV status of any of those samples. Embodiments described herein may also apply the CNV detection scheme iteratively to further improve the detection performance, especially in the case of more frequent CNV occurrence. Since the knowledge on the CNVs in reference samples may improve their comparison with the sample being tested, the proposed methods may further comprise the step of iteratively feeding back the information about the CNVs found in the samples from any detection step into the next iteration step. The proposed methods may also further use additional information available from the NGS workflow about the samples, such as information on SNP fractions, as input to the NGS CNV detection.