US 11,756,286 B2
Systems and methods for identifying morphological patterns in tissue samplers
Jeffrey Clark Mellen, Martinez, CA (US); Jasper Staab, Honolulu, HI (US); Kevin J. Wu, San Francisco, CA (US); Neil Ira Weisenfeld, Lynnfield, MA (US); Florian Baumgartner, Stockholm (SE); and Brynn Claypoole, San Francisco, CA (US)
Assigned to 10X GENOMICS, INC., Pleasanton, CA (US)
Filed by 10X Genomics, Inc., Pleasanton, CA (US)
Filed on Oct. 18, 2022, as Appl. No. 18/47,620.
Application 18/047,620 is a continuation of application No. 17/039,935, filed on Sep. 30, 2020, granted, now 11,514,575.
Claims priority of provisional application 63/041,823, filed on Jun. 20, 2020.
Claims priority of provisional application 62/980,077, filed on Feb. 21, 2020.
Claims priority of provisional application 62/909,071, filed on Oct. 1, 2019.
Prior Publication US 2023/0081613 A1, Mar. 16, 2023
Int. Cl. G06V 10/762 (2022.01); G16B 15/00 (2019.01); G01N 1/30 (2006.01); G06T 7/00 (2017.01)
CPC G06V 10/762 (2022.01) [G01N 1/30 (2013.01); G06T 7/0012 (2013.01); G16B 15/00 (2019.02); G01N 2001/302 (2013.01); G06T 2207/30024 (2013.01)] 21 Claims
OG exemplary drawing
 
1. A method for identifying a morphological pattern, the method comprising:
at a computer system comprising one or more processing cores, a memory, and a display:
A) obtaining a discrete attribute value dataset associated with a plurality of probe spots having a spatial arrangement, wherein each probe spot in the plurality of probe spots is assigned a barcode in a plurality of barcodes and the plurality of probe spots comprises at least 1000 probe spots, the discrete attribute value dataset comprising:
(i) one or more two-dimensional images, wherein each respective two-dimensional image in the one or more two-dimensional images (a) is taken of a tissue section, obtained from a biological sample, overlaid on a substrate having the plurality of probe spots arranged in the spatial arrangement and (b) comprises at least 100,000 pixel values, and
(ii) a corresponding plurality of discrete attribute values for each respective probe spot in the plurality of probe spots, wherein each respective discrete attribute value in the corresponding plurality of discrete attribute values is for a loci in a plurality of loci;
B) obtaining a corresponding cluster assignment in a plurality of clusters, of each respective probe spot in the plurality of probe spots of the discrete attribute value dataset, wherein the corresponding cluster assignment is based, at least in part, on the corresponding plurality of discrete attribute values of the respective probe spot, or a corresponding plurality of dimension reduction components derived, at least in part, from the corresponding plurality of discrete attribute values of the respective probe spot;
C) displaying, on the display, pixel values of all or portion of a first two-dimensional image in the one or more two-dimensional images; and
D) overlaying on the first two-dimensional image and co-aligned with the first two-dimensional image (i) first indicia for one or more probe spots in the plurality of probe spots that have been assigned to a first cluster in the plurality of clusters and (ii) second indicia for one or more probes spots in the plurality of probe spots that have been assigned to a second cluster in the plurality of clusters, thereby identifying the morphological pattern.