G16B35/10

TUMOR CELL ANALYSIS USING APTAMERS AND MICROFLUIDIC SYSTEMS
20220341934 · 2022-10-27 · ·

Methods described herein include receiving data from flowing a plurality of aptamers over a sample of tumor cells randomly affixed to a surface of a microfluidic device. The tumor cells may include one or more unknown tumor subtypes of cells. The plurality of aptamers may include a plurality of aptamer families. Each aptamer family of the plurality of aptamer families may be determined to bind to at least one possible subtype of the tumor cells. The data may include a measure of binding affinity of each aptamer family to the tumor cells. The method may include analyzing the measure of the binding affinity of each aptamer family to the tumor cells. The analyzing may include classifying the binding affinity. The method may also include determining one or more aptamer families that characterize the one or more unknown tumor subtypes of cells based on the classifying.

Alignment methods, devices and systems

The disclosure discloses an alignment method, device, and system. The alignment method includes: converting each read into a set of short fragments corresponding to the read to obtain a plurality of sets of short fragments; determining a corresponding position of the short fragment in a reference library to obtain a first positioning result, wherein the reference library is a hash table constructed based on a reference sequence, the reference library includes a plurality of entries, one entry of the reference library corresponds to one seed sequence, and the seed sequence is capable of matching at least one sequence on the reference sequence, a distance between two seed sequences corresponding to two adjacent entries of the reference library on the reference sequence is less than a length of the short fragment; removing a short fragment positioned on any one of the adjacent entries of the reference library in the first positioning result to obtain a second positioning result; and extending based on short fragments from the same read in the second positioning result to obtain an alignment result of the read. The alignment method can efficiently and accurately process and position sequencing data.

Alignment methods, devices and systems

The disclosure discloses an alignment method, device, and system. The alignment method includes: converting each read into a set of short fragments corresponding to the read to obtain a plurality of sets of short fragments; determining a corresponding position of the short fragment in a reference library to obtain a first positioning result, wherein the reference library is a hash table constructed based on a reference sequence, the reference library includes a plurality of entries, one entry of the reference library corresponds to one seed sequence, and the seed sequence is capable of matching at least one sequence on the reference sequence, a distance between two seed sequences corresponding to two adjacent entries of the reference library on the reference sequence is less than a length of the short fragment; removing a short fragment positioned on any one of the adjacent entries of the reference library in the first positioning result to obtain a second positioning result; and extending based on short fragments from the same read in the second positioning result to obtain an alignment result of the read. The alignment method can efficiently and accurately process and position sequencing data.

USING MACHINE LEARNING TO OPTIMIZE ASSAYS FOR SINGLE CELL TARGETED SEQUENCING

Disclosed herein is an amplicon design workflow for improving the design of amplicons such that panels including newly designed amplicons can achieve improved performance (e.g., improved panel uniformity). The amplicon design workflow involves performing a feature selection process to identify key amplicon attributes that likely lead to improved amplicon performance. Therefore, improved amplicons can be designed based on these key attributes. A sequencing panel, such as a DNA sequencing panel or RNA sequencing panel can be constructed using these improved amplicons and further validated. Thus, such panels including improved amplicons can be deployed for analyzing single cells e.g., through a single cell workflow analysis, for characterizing the cells for nucleic acid events, such as the presence or absence of RNA fusion transcripts.

USING MACHINE LEARNING TO OPTIMIZE ASSAYS FOR SINGLE CELL TARGETED SEQUENCING

Disclosed herein is an amplicon design workflow for improving the design of amplicons such that panels including newly designed amplicons can achieve improved performance (e.g., improved panel uniformity). The amplicon design workflow involves performing a feature selection process to identify key amplicon attributes that likely lead to improved amplicon performance. Therefore, improved amplicons can be designed based on these key attributes. A sequencing panel, such as a DNA sequencing panel or RNA sequencing panel can be constructed using these improved amplicons and further validated. Thus, such panels including improved amplicons can be deployed for analyzing single cells e.g., through a single cell workflow analysis, for characterizing the cells for nucleic acid events, such as the presence or absence of RNA fusion transcripts.

AUTOMATED PRIMING AND LIBRARY LOADING DEVICE

Provided herein are automated apparatus and methods for the identification of microorganisms in various samples. The disclosure solves existing challenges encountered in identifying and distinguishing various types of microorganisms, including viruses and bacteria in a timely, efficient, and automated manner by library preparation and sequencing.

AUTOMATED PRIMING AND LIBRARY LOADING DEVICE

Provided herein are automated apparatus and methods for the identification of microorganisms in various samples. The disclosure solves existing challenges encountered in identifying and distinguishing various types of microorganisms, including viruses and bacteria in a timely, efficient, and automated manner by library preparation and sequencing.

Alignment free filtering for identifying fusions

Cell free nucleic acids from a test sample obtained from an individual are analyzed to identify possible fusion events. Cell free nucleic acids are sequenced and processed to generate fragments. Fragments are decomposed into kmers and the kmers are either analyzed de novo or compared to targeted nucleic acid sequences that are known to be associated with fusion gene pairs of interest. Thus, kmers that may have originated from a fusion event can be identified. These kmers are consolidated to generate gene ranges from various genes that match sequences in the fragment. A candidate fusion event can be called given the spanning of one or more gene ranges across the fragment.

Alignment free filtering for identifying fusions

Cell free nucleic acids from a test sample obtained from an individual are analyzed to identify possible fusion events. Cell free nucleic acids are sequenced and processed to generate fragments. Fragments are decomposed into kmers and the kmers are either analyzed de novo or compared to targeted nucleic acid sequences that are known to be associated with fusion gene pairs of interest. Thus, kmers that may have originated from a fusion event can be identified. These kmers are consolidated to generate gene ranges from various genes that match sequences in the fragment. A candidate fusion event can be called given the spanning of one or more gene ranges across the fragment.

DESIGNED IL-2 VARIANTS
20220324934 · 2022-10-13 ·

Variant IL-2 proteins and uses thereof are provided. In some embodiments, the IL-2 variant proteins have greater potency for activation of IL-2 signaling pathways in cells lacking CD25 expression, relative to wild-type IL-2.