# US 11,306,354 B2 · Methods and compositions for analyzing nucleic acid > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,306,354 B2 - Document ID: US11306354B2 - Status: Granted - Kind: B2 - Application number: 15/894,283 - Filed: 2018-02-12 - Published: 2018-08-16 - Granted: 2022-04-19 - Earliest claimed: 2012-05-21 - Assignees: Sequenom, Inc. - Applicants: Sequenom, Inc. - Inventors: Sung K. Kim; Cosmin Deciu - Web page: https://patentgrep.com/patent/US11306354B2 ## CPC - C12Q 1/6869: Methods for sequencing - G16B 30/00: ICT specially adapted for sequence analysis involving nucleotides or amino acids - G16B 30/10: Sequence alignment; Homology search - G16B 30/20: Sequence assembly - G16B 40/00: ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding - G16B 40/10: Signal processing, e.g. from mass spectrometry [MS] or from PCR - C12Q: MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS (immunoassay G01N33/53); COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES - G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY ## Abstract Technology provided herein relates in part to methods, processes, compositions and apparatuses for analyzing nucleic acid. ## Claims ### Claim 1 A method for in silico enrichment of sequence read counts from fetal nucleic acid with reduced experimental bias, comprising: a) sequencing test sample nucleic acid by a non-loci-specific massively parallel sequencing process that generates thousands to millions of sequence reads, which test sample nucleic acid comprises circulating cell-free nucleic acid from a test sample from a pregnant female bearing a fetus; b) mapping the thousands to millions of sequence reads to portions of a reference genome; c) counting the thousands to millions of sequence reads mapped to the portions, which counting generates counts of the thousands to millions of sequence reads mapped to the portions of the reference genome; d) measuring the length of nucleic acid fragments from which the thousands to millions of sequence reads are generated; e) selecting counts for the thousands to millions of sequence reads from nucleic acid fragments that are shorter than about 160 bases, thereby generating selected counts of the thousands to millions of sequence reads, wherein the selected counts are enriched for counts of reads from fetal nucleic acid; and f) normalizing the selected counts of the thousands to millions of sequence reads for the test sample according to an experimental bias for the test sample, an experimental bias for each of multiple samples from multiple pregnant females, and counts of sequence reads mapped to each of the genomic portions for the multiple samples, thereby generating normalized selected counts, wherein experimental bias in the normalized selected counts is reduced. ### Claim 2 (depends on 1) The method of claim 1, wherein sequence coverage of reads from nucleic acid fragments shorter than about 160 bases is reduced relative to sequence coverage of reads not restricted by fragment length. ### Claim 3 (depends on 1) The method of claim 1, wherein sequence read count of reads from nucleic acid fragments shorter than about 160 bases is reduced relative to sequence read count of reads not restricted by fragment length. ### Claim 4 (depends on 3) The method of claim 3, wherein sequence read count is reduced by at least about 50%. ### Claim 5 (depends on 1) The method of claim 1, wherein measuring the length of the nucleic acid fragments comprises a paired-end sequencing method. ### Claim 6 (depends on 1) The method of claim 1, wherein sequence read length is about 15 bases to about 25 bases. ### Claim 7 (depends on 1) The method of claim 1, wherein the test sample is blood, serum, or plasma. ### Claim 8 (depends on 1) The method of claim 1, wherein the experimental bias for the test sample in (f) is a guanine and cytosine (GC) bias, and the experimental bias for each of multiple samples from multiple pregnant females in (f) is a guanine and cytosine (GC) bias. ### Claim 9 (depends on 8) The method of claim 8, wherein the normalizing in (f) comprises 1) determining a guanine and cytosine (GC) bias coefficient for the test sample based on a fitted relation between (i) the counts of the sequence reads mapped to each of the genomic portions and (ii) GC content for each of the genomic portions, wherein the GC bias coefficient is a slope for a linear fitted relation or a curvature estimation for a non-linear fitted relation; and 2) determining a fitted relation, for each of the genomic portions, between (i) a GC bias coefficient for each of the multiple samples from multiple pregnant females and (ii) counts of sequence reads mapped to each of the genomic portions for the multiple samples. ### Claim 10 (depends on 1) The method of claim 1, wherein (b) comprises mapping the thousands to millions of sequence reads to portions of a complete human reference genome. ### Claim 11 (depends on 1) The method of claim 1, wherein millions of sequence reads are generated in (a). ### Claim 12 (depends on 1) The method of claim 1, wherein the portions in (b) comprise multiple chromosome portions from multiple chromosomes. ### Claim 13 (depends on 1) The method of claim 1, wherein the portions in (b) comprise portions that are about 10 kilobases (kb) to about 100 kb. ### Claim 14 (depends on 1) The method of claim 1, wherein the sequencing is performed at about 0.1-fold coverage, about 0.2-fold coverage, about 0.3-fold coverage, about 0.4-fold coverage, about 0.5-fold coverage, about 0.6-fold coverage, about 0.7-fold coverage, about 0.8-fold coverage, about 0.9-fold coverage, about 1-fold coverage, or greater than 1-fold coverage.