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US 2024/0257912 A1Published application
Scalable Distributed Processing Software for Next-Generation in Situ Sequencing
AssigneeThe Board of Trustees of the Leland Stanford Junior University
InventorsKarl A. Deisseroth, Ethan B. Richman, Christopher M. Roat
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Abstract
Methods, systems, and devices, including computer programs encoded on a computer storage medium are provided for processing of next-generation in situ sequencing data for nucleic acids in cells in tissue. In particular, cloud-based scalable data processing software for volumetric in situ sequencing is provided.
Claims54
A computer implemented method for processing in situ sequencing imaging data, the computer performing steps comprising:
- (a) receiving in situ sequencing imaging data;
- (b) applying configuration parameters to the in situ sequencing imaging data, wherein the configuration parameters comprise an encoding scheme, a codebook, image acquisition parameters, and sample metadata;
- (c) preprocessing imaging data by removing optical aberrations, subtracting background signal, performing deconvolution, filtering the images, and merging overlapping fields of view;
- (d) performing registration of imaging data by aligning selected common features in images taken at different timepoints and across different color channels at each time point;
- (e) segmenting images to determine locations of cell nuclei and cells;
- and
- (f) performing sequential analysis of images if the in situ sequencing imaging data is from sequential sequencing, wherein said performing sequential analysis of images comprises:
- i) measuring an intensity of a fluorescent signal for each segmented cell and nucleus, wherein the intensity of the fluorescence signal is proportional to the amount of a target nucleic acid, and ii) subtracting estimated carry-over signal from a previous sequencing round, or
- performing combinatorial analysis of images if the in situ sequencing imaging data is from combinatorial sequencing, wherein said performing sequential analysis of images comprises i) identifying each amplicon labeling a target nucleic acid from detection of barcodes, wherein invalid barcodes are removed according to their encoding scheme, ii) measuring a fluorescent signal of each amplicon at each timepoint to determine which color channel has the highest signal for each detected amplicon, closest code-book entry to a vector of signals, or clustering of pixel intensities;
- iii) iteratively matching signals across rounds of sequencing to membership in the code-book;
- iv) assigning a target identity to each detected amplicon, and v) calculating the number of each target nucleic acid present in each cell and nucleus.
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