# US 11,898,206 B2 · Systems and methods for clonotype screening > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,898,206 B2 - Document ID: US11898206B2 - Status: Granted - Kind: B2 - Application number: 15/984,324 - Filed: 2018-05-19 - Published: 2018-12-27 - Granted: 2024-02-13 - Earliest claimed: 2017-05-19 - Assignees: 10x Genomics, Inc. - Applicants: 10X Genomics, Inc. - Inventors: Alexander Y. Wong; Jeffrey Mellen; Kevin Wu; Paul Ryvkin - Web page: https://patentgrep.com/patent/US11898206B2 ## CPC - C12Q 1/6881: for tissue or cell typing, e.g. human leukocyte antigen [HLA] probes - C07K 14/7051: {T-cell receptor (TcR)-CD3 complex} - C07K 16/2809: {against the T-cell receptor (TcR)-CD3 complex} - G16B 30/00: ICT specially adapted for sequence analysis involving nucleotides or amino acids - G16B 40/30: Unsupervised data analysis - G16B 45/00: ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks - C07K 2317/565: Complementarity determining region [CDR] - C12Q 1/6806: Preparing nucleic acids for analysis, e.g. for polymerase chain reaction [PCR] assay (C12Q1/6804 takes precedence) - C12Q 1/686: Polymerase chain reaction [PCR] - C12Q 1/6883: for diseases caused by alterations of genetic material - C12Q 2600/156: Polymorphic or mutational markers - C12Q 2600/158: Expression markers - C12Q 2600/16: Primer sets for multiplex assays - G16B 30/10: Sequence alignment; Homology search - 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 - C07K: PEPTIDES (peptides in foodstuffs A23; obtaining protein compositions for foodstuffs, working-up proteins for foodstuffs A23J; preparations for medicinal purposes A61K; peptides containing beta-lactam rings C07D; cyclic dipeptides not having in their molecule any other peptide link than those which form their ring, e.g. piperazine-2,5-diones, C07D; ergot alkaloids of the cyclic peptide type C07D519/02; macromolecular compounds having statistically distributed amino acid units in their molecules, i.e. when the preparation does not provide for a specific; but for a random sequence of the amino acid units, homopolyamides and block copolyamides derived from amino acids C08G69/00; macromolecular products derived from proteins C08H1/00; preparation of glue or gelatine C09H; single cell proteins, enzymes C12N; genetic engineering processes for obtaining peptides C12N15/00; compositions for measuring or testing processes involving enzymes C12Q; investigation or analysis of biological material G01N33/00) - G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY ## Abstract Methods for screening clonotypes are provided. Data representing a plurality of cells from a single subject is obtained. The data represents a plurality of clonotypes. The data includes a plurality of contigs for each respective clonotype in the plurality of clonotypes. Each respective contig in the plurality of contigs comprises (i) an indication of chain type for the respective contig and (ii) a contig sequence of an mRNA of the respective cell. There is determined, using the data, for each respective clonotype in the plurality of clonotypes, a number of the plurality of cells that represent the respective clonotype. In some instances, more than one cell in the plurality of cells have the same clonotype in the plurality of clonotypes. In some instances, the plurality of clonotypes comprises 25 clonotypes and where the plurality of cells includes at least one cell for each clonotype in the plurality of clonotypes. ## Claims ### Claim 1 A method of screening a plurality of clonotypes, the method comprising: at a computer system having one or more processors, and memory storing one or more programs for execution by the one or more processors: obtaining, in electronic form, a clonotype dataset formed using a first plurality of sequence reads of nucleic acids in a first aliquot of nucleic acids pooled from a plurality of 100 or more cells from a biological sample of a single subject comprising B cells or T cells, wherein each respective sequence read in the first plurality of sequence reads includes a corresponding barcode, from a plurality of barcodes, that indicates which cell in the plurality of cells originated the nucleic acid represented by the respective sequence read, the clonotype dataset comprises, for each respective cell in the plurality of cells, a corresponding contig entry in a plurality of contig entries, wherein the plurality of contig entries represents the plurality of clonotypes, and wherein the plurality of clonotypes comprises 25 clonotypes, each respective clonotype in the plurality of clonotypes corresponds to one or more contig entries in the clonotype dataset, and for each respective cell in the plurality of cells, a corresponding contig entry in the plurality of contig entries: (i) corresponds to a T-cell receptor or B-cell receptor from the respective cell in the plurality of cells and (ii) comprises an indication of chain type for the corresponding T-cell receptor or B-cell receptor, a corresponding contig sequence, and a corresponding barcode, from the plurality of barcodes, that identifies the respective cell for the respective contig entry, wherein the corresponding contig sequence determined by a subset of sequence reads in the first plurality of sequence reads (i) having the respective barcode for the respective cell and (ii) encoding all or a portion of the corresponding T-cell receptor chain or B-cell receptor chain from the respective cell; obtaining, in electronic form, a discrete attribute value dataset formed using a second plurality of sequence reads of nucleic acids in a second aliquot of nucleic acids pooled from the plurality of cells, wherein each respective sequence read in the second plurality of sequence reads includes a corresponding barcode, from the plurality of barcodes, that indicates which cell in the plurality of cells originated the nucleic acid represented by the respective sequence read, and the discrete attribute value data set comprises: for each respective cell in the plurality of cells, for each respective gene in a plurality of genes, a corresponding discrete attribute value for a count of a number of mRNA mapping to the respective gene in the respective cell determined from a number of sequence reads in the second plurality of sequence reads that map to the respective gene and have the barcode for the respective cell; clustering the plurality of cells into a plurality of clusters by (i) computing a plurality of distances using each discrete attribute value of each cell in the plurality of cells for each unique pair of cells in the plurality of cells and (ii) evaluating the plurality of distances with a criterion function, wherein the plurality of distances includes a separate distance for each pair of cells in the plurality of cells, each respective distance in the plurality of distances represents a different pair of cells in the plurality of cells and quantifies a distance between a respective first vector formed by the discrete attribute values for a respective first cell in the different pair of cells and a respective second vector formed by the discrete attribute values for a respective second cell in the different pair of cells, and each respective cluster in the plurality of clusters represents a corresponding subset of cells of the plurality of cells that are clustered together based on evaluation of distances in the plurality of distances representing different pairs of cells within the corresponding subset of cells with the criterion function; matching, for each respective cell in a first cluster in the plurality of clusters, the corresponding barcode of the respective cell with a corresponding barcode for a respective contig entry in the plurality of contig entries, thereby obtaining a corresponding contig entry for the respective cell; and providing, for each respective clonotype in the plurality of clonotypes represented in the first cluster, a number of cells in the plurality of cells in the clonotype dataset, that represent the respective clonotype that are in the first cluster, based on the corresponding contig entry of each respective cell in the first cluster. ### Claim 2 (depends on 1) The method of claim 1, further comprising ordering respective clonotypes in the first cluster by the number of the plurality of cells that have the respective clonotype in the first cluster. ### Claim 3 (depends on 1) The method of claim 1, wherein more than one cell in the plurality of cells have the same clonotype in the plurality of clonotypes. ### Claim 4 (depends on 1) The method of claim 1, wherein more than ten cells in the plurality of cells have the same clonotype in the plurality of clonotypes. ### Claim 5 (depends on 1) The method of claim 1, wherein the plurality of clonotypes comprises 100 clonotypes. ### Claim 6 (depends on 1) The method of claim 1, wherein the plurality of cells consists of B-cells from the single subject. ### Claim 7 (depends on 1) The method of claim 1, wherein the plurality of cells consists of T-cells from the single subject. ### Claim 8 (depends on 1) The method of claim 1, wherein the single subject is mammalian. ### Claim 9 (depends on 1) The method of claim 1, wherein the single subject is a reptile, avian, amphibian, fish, ungulate, ruminant, bovine, equine, caprine, ovine, swine, camelid, monkey, ape, ursid, poultry, dog, cat, mouse, rat, fish, dolphin, whale or shark. ### Claim 10 (depends on 1) The method of claim 1, wherein the clonotype dataset comprises a file that includes a series of data blocks with a master JSON table of contents at the beginning of the file and a JSON table of contents describing the addresses and structure of each block at the end of the file. ### Claim 11 (depends on 10) The method of claim 10, wherein a block in the series of data blocks consists of a database, the database comprises a first table for the plurality of clonotypes, a second table for the plurality of contig entries in the clonotype dataset, and a secondary table that maps a respective barcode in the plurality of barcodes to a respective clonotype in the plurality of clonotypes, and the database is queried to create a clonotype list, sorted by frequency, for the matching step. ### Claim 12 (depends on 1) The method of claim 1, wherein the plurality of cells comprises 1000 or more cells. ### Claim 13 A computer system for screening a plurality of clonotypes, the computer system comprising: one or more processors; and memory addressable by the one or more processors, the memory storing at least one program for execution by the one or more processors, the at least one program comprising instructions for: obtaining, in electronic form, a clonotype dataset formed using a first plurality of sequence reads of nucleic acids in a first aliquot of nucleic acids pooled from a plurality of 100 or more cells from a biological sample of a single subject comprising B cells or T cells, wherein each respective sequence read in the first plurality of sequence reads includes a corresponding barcode, from a plurality of barcodes, that indicates which cell in the plurality of cells originated the nucleic acid represented by the respective sequence read, the clonotype dataset comprises, for each respective cell in the plurality of cells, a corresponding contig entry in a plurality of contig entries, wherein the plurality of contig entries represents the plurality of clonotypes, and wherein the plurality of clonotypes comprises 25 clonotypes, each respective clonotype in the plurality of clonotypes corresponds to one or more contig entries in the clonotype dataset, and for each respective cell in the plurality of cells, a corresponding contig entry in the plurality of contig entries: (i) corresponds to a T-cell receptor or B-cell receptor from the respective individual cell in the plurality of cells and iii) comprises an indication of chain type for the corresponding T-cell receptor or B-cell receptor, a corresponding contig sequence, and a corresponding barcode, from the plurality of barcodes, that identifies the respective cell for the respective contig entry, wherein the corresponding contig sequence is determined by a subset of sequence reads in the first plurality of sequence reads (i) having the respective barcode for the respective cell and (ii) encoding all or a portion of the corresponding T-cell receptor chain or B-cell receptor chain from the respective cell; obtaining, in electronic form, a discrete attribute value dataset formed using a second plurality of sequence reads of nucleic acids in a second aliquot of nucleic acids pooled from the plurality of cells, wherein each respective sequence read in the second plurality of sequence reads includes a corresponding barcode, from the plurality of barcodes, that indicates which cell in the plurality of cells originated the nucleic acid represented by the respective sequence read, and the discrete attribute value data set comprises: for each respective cell in the plurality of cells, for each respective gene in a plurality of genes, a corresponding discrete attribute value for a count of a number of mRNA mapping to the respective gene in the respective cell determined from a number of sequence reads in the second plurality of sequence reads that map to the respective gene and have the barcode for the respective cell; clustering the plurality of cells into a plurality of clusters by (i) computing a plurality of distances using each discrete attribute value of each cell in the plurality of cells for each unique pair of cells in the plurality of cells and (ii) evaluating the plurality of distances with a criterion function, wherein the plurality of distances includes a separate distance for each pair of cells in the plurality of cells, each respective distance in the plurality of distances represents a different pair of cells in the plurality of cells and quantifies a distance between a respective first vector formed by the discrete attribute values for a respective first cell in the different pair of cells and a respective second vector formed by the discrete attribute values for a respective second cell in the different pair of cells, and each respective cluster in the plurality of clusters represents a corresponding subset of cells of the plurality of cells that are clustered together based on evaluation of distances in the plurality of distances representing different pairs of cells within the corresponding subset of cells with the criterion function; matching, for each respective cell in a first cluster in the plurality of clusters, the corresponding barcode of the respective cell with a corresponding barcode for a respective contig entry in the plurality of contig entries, thereby obtaining a corresponding contig entry for the respective cell; and providing, for each respective clonotype in the plurality of clonotypes represented in the first cluster, a number of cells in the plurality of cells in the clonotype dataset, that represent the respective clonotype that are in the first cluster, based on the corresponding contig entry of each respective cell in the first cluster. ### Claim 14 A non-transitory computer readable storage medium, wherein the non-transitory computer readable storage medium stores instructions, which when executed by a computer system, cause the computer system to perform a method for screening a plurality of clonotypes, the method comprising: obtaining, in electronic form, a clonotype dataset formed using a first plurality of sequence reads of nucleic acids in a first aliquot of nucleic acids pooled from plurality of 100 or more cells from a biological sample of a single subject comprising B cells or T cells, wherein each respective sequence read in the first plurality of sequence reads includes a corresponding barcode, from a plurality of barcodes, that indicates which cell in the plurality of cells originated the nucleic acid represented by the respective sequence read, the clonotype dataset comprises, for each respective cell in the plurality of cells, a corresponding contig entry in a plurality of contig entries, wherein the plurality of contig entries represents the plurality of clonotypes, and wherein the plurality of clonotypes comprises 25 clonotypes, each respective clonotype in the plurality of clonotypes corresponds to one or more contig entries in the clonotype dataset, and for each respective cell in the plurality of cells, a corresponding contig entry in the plurality of contig entries: (i) corresponds to a T-cell receptor or B-cell receptor from the respective cell in the plurality of cells and (ii) comprises an indication of chain type for the corresponding T-cell receptor or B-cell receptor, a corresponding contig sequence, and a corresponding barcode, from the plurality of barcodes, that identifies the respective cell, wherein the corresponding contig sequence is determined by a subset of sequence reads in the first plurality of sequence reads (i) having the respective barcode for the respective cell and (ii) encoding all or a portion of the corresponding T-cell receptor chain or B-cell receptor chain from the respective cell; obtaining, in electronic form, a discrete attribute value dataset formed using a second plurality of sequence reads of nucleic acids in a second aliquot of nucleic acids pooled from the plurality of cells, wherein each respective sequence read in the second plurality of sequence reads includes a corresponding barcode, from the plurality of barcodes, that indicates which cell in the plurality of cells originated the nucleic acid represented by the respective sequence read, and the discrete attribute value data set comprises: for each respective cell in the plurality of cells, for each respective gene in a plurality of genes, a corresponding discrete attribute value for a count of a number of mRNA mapping to the respective gene in the respective cell determined from a number of sequence reads in the second plurality of sequence reads that map to the respective gene and have the barcode for the respective cell; clustering the plurality of cells into a plurality of clusters by (i) computing a plurality of distances using each discrete attribute value of each cell in the plurality of cells for each unique pair of cells in the plurality of cells and (ii) evaluating the plurality of distances with a criterion function, wherein the plurality of distances includes a separate distance for each pair of cells in the plurality of cells, each respective distance in the plurality of distances represents a different pair of cells in the plurality of cells and quantifies a distance between a respective first vector formed by the discrete attribute values for a respective first cell in the different pair of cells and a respective second vector formed by the discrete attribute values for a respective second cell in the different pair of cells, and each respective cluster in the plurality of clusters represents a corresponding subset of cells of the plurality of cells that are clustered together based on evaluation of distances in the plurality of distances representing different pairs of cells within the corresponding subset of cells with the criterion function; matching, for each respective cell in a first cluster in the plurality of clusters, the corresponding barcode of the respective cell with a corresponding barcode for a respective contig entry in the plurality of contig entries, thereby obtaining a corresponding contig entry for the respective cell; and providing, for each respective clonotype in the plurality of clonotypes represented in the first cluster, a number of cells in the plurality of cells in the clonotype dataset that represent the respective clonotype that are in the first cluster, based on the corresponding contig entry of each respective cell in the first cluster.