The present application provides a method and a system for integrating morphological characteristics and gene expression of individual cells. The method comprises the following steps: providing a microfluidic device, which comprises a microwell array and an interdigital electrode, and each microwell comprises a plurality of capture oligonucleotides; injecting cells into the microwells, capturing a single cell and recording morphological characteristics of the cell; lysing the cell so that the mRNA released by the cell is captured by the capture oligonucleotide; reverse transcribing the captured mRNA to obtain cDNA; performing a PCR amplification reaction on the cDNA to obtain a cDNA library and sequencing the cDNA library; reading the cell barcode sequence and the unique molecular identifier sequence according to sequencing results, and the morphological characteristics and gene expression of the cell in the microwell are integrated together.

Provided are methods for preparation and analysis of nucleic acids. Some embodiments include reverse transcribing the RNA with barcoded primers to produce cDNA while maintaining the DNA in the sample, sequencing the DNA and cDNA together, and differentiating the sequenced DNA and cDNA using the barcode or barcodes of the primers. Some embodiments include analyzing the DNA and cDNA sequences of multiple samples separating reads into k-mers, and comparing the k-mers between samples to identify differential sequences between the sequences of the samples.

This disclosure provides methods and systems for single-cell, multi-omic analysis of target cells without microfluidic devices. The disclosed methods involve the use of template particles to template the formation of monodisperse droplets to generally capture a single target cell from a population of cells in an encapsulation, derive a plurality of distinct mRNA molecules from the single target cell, and quantify the distinct mRNA molecules to generate an expression profile. Nucleic-acid-tagged antibody conjugates are used for simultaneous proteomic analysis along with the gene expression profiling.

Methods for measuring subpopulations of ribonucleic acid (RNA) molecules are provided. In some embodiments, methods of generating a sequencing library from a plurality of RNA molecules in a test sample obtained from a subject are provided, as well as methods for analyzing the sequencing library to detect, e.g., the presence or absence of a disease.

Systems, methods, and apparatuses for generating and using machine learning models using genetic data. A set of input features for training the machine learning model can be identified and used to train the model based on training samples, e.g., for which one or more labels are known. As examples, the input features can include aligned variables (e.g., derived from sequences aligned to a population level or individual references) and/or non-aligned variables (e.g., sequence content). The features can be classified into different groups based on the underlying genetic data or intermediate values resulting from a processing of the underlying genetic data. Features can be selected from a feature space for creating a feature vector for training a model. The selection and creation of feature vectors can be performed iteratively to train many models as part of a search for optimal features and an optimal model.

The present invention relates to a method of obtaining an enriched personalized population of a target polynucleotide using a synthetic single guide RNA (sgRNA) for an sgRNA-guided nucleic acid-binding protein, as well as to a method of obtaining a pool of personalized target-irrelevant synthetic single guide RNAs (sgRNAs) for a sgRNA-guided nucleic acid-binding protein. Also provided is a kit comprising a pool of sgRNAs obtainable by the methods of the invention, the use of a pool of sgRNAs obtainable by the methods of the invention and a method of monitoring a disease state.

Systems and methods for recovering content of a sample from a microcapillary array are provided. The microcapillary array includes a plurality of microcapillary wells. A laser is positioned to target a first microcapillary well in the plurality of microcap-wells. The laser pulses at least one time at the first microcapillary well. The content from the first microcapillary well is extracted, recovering the content of the first microcapillary well.

The invention provides high-throughput systems and methods for screening CRISPR-edited cells in bulk with single cell resolution. Methods of the invention use cells expressing polyadenylated guide RNAs that are detectable by RNA sequencing. Methods of the invention provide for the detection of each cell's guide RNA along with its single cell transcriptome to provide useful gene expression data for assessing CRISPR activity from cells in bulk. In addition, methods of the invention offer a high throughput single cell analytical framework for generating single cell transcriptome data from which CRISPR activity may be evaluated.

The invention provides high-throughput systems and methods for screening CRISPR-edited cells in bulk with single cell resolution. Methods of the invention use cells expressing polyadenylated guide RNAs that are detectable by RNA sequencing. Methods of the invention provide for the detection of each cell's guide RNA along with its single cell transcriptome to provide useful gene expression data for assessing CRISPR activity from cells in bulk. In addition, methods of the invention offer a high throughput single cell analytical framework for generating single cell transcriptome data from which CRISPR activity may be evaluated.

This disclosure provides methods and systems for single-extracellular (EV), multi-omic analysis of target EVs without microfluidic devices. The disclosed methods involve the use of template particles to template the formation of monodisperse droplets to generally capture a single target EV from a population of EVs in an encapsulation, derive a plurality of distinct mRNA molecules from the single target EV, and quantify the distinct mRNA molecules to generate an expression profile. Nucleic-acid-tagged antibody conjugates are used for simultaneous proteomic analysis along with the gene expression profiling, which enables classification of an EV in a sample.