Illumina Corporation

Pacific Biosciences of California, Inc.

Omniome, Inc.

Other

Illumina Software, Inc.

John S Vieceli

Eric Jon Ojard

Rami Mehio

Gavin Derek Parnaby

Nitin Udpa

Stephen Tanner

M Shane Bowen

Abde Ali Hunaid Kagalwalla

Paul Belitz

Robert Ezra Langlois

Alex Nemiroski

Hui Han

Kevan Samiee

Bala Murali K Venkatesan

Danny Yuan Chan

Arnold Oliphant

Kandaswamy Vijayan

Sean Stromberg

Bo Lu

John A Moon

Ryan Kelley

Xiaoyu Chen

Ryan Matthew Kelley

The technology disclosed extracts intensities from sequencing images for base calling target clusters and attenuates spatial crosstalk from neighboring clusters. The technology disclosed accesses a particular section from a plurality of sections of an image output by a sensor, the particular section of the image including at least one pixel depicting intensity emission values from a target cluster and neighboring clusters located across the sensor, and convolves the particular section of the image with a corresponding convolution kernel in a plurality of convolution kernels, to generate a feature map comprising a plurality of feature values. The technology disclosed further assigns a corresponding feature value to the target cluster based on feature values in the plurality of feature values adjoining a center of the target cluster, and processes the corresponding feature value assigned to the target cluster, to base call the target cluster.

Intensity extraction for feature values in base calling

The technology disclosed relates to equalizer-based intensity correction for base calling. In particular, the technology disclosed relates to accessing an image whose pixels depict intensity emissions from a target cluster and intensity emissions from additional adjacent clusters, selecting a lookup table that contains pixel coefficients that are configured to increase a signal-to-noise ratio, applying the pixel coefficients to intensity values of the pixels in the image to produce an output, and base calling the target cluster based on the output.

Equalizer-based intensity correction for base calling

The technology disclosed corrects inter-cluster intensity profile variation for improved base calling on a cluster-by-cluster basis. The technology disclosed accesses current intensity data and historic intensity data of a target cluster, where the current intensity data is for a current sequencing cycle and the historic intensity data is for one or more preceding sequencing cycles. A first accumulated intensity correction parameter is determined by accumulating distribution intensities measured for the target cluster at the current and preceding sequencing cycles. A second accumulated intensity correction parameter is determined by accumulating intensity errors measured for the target cluster at the current and preceding sequencing cycles. Based on the first and second accumulated intensity correction parameters, next intensity data for a next sequencing cycle is corrected to generate corrected next intensity data, which is used to base call the target cluster at the next sequencing cycle.

Inter-cluster intensity variation correction and base calling

A method of determining a nucleic acid sequence that includes steps of: (a) contacting a primed template nucleic acid with a series of mixtures for forming ternary complexes, wherein each of the mixtures includes a polymerase and nucleotide cognates for at least two different base types suspected of being present at the next template position of the template nucleic acid; (b) monitoring the next template position for ternary complexes formed by the series of mixtures, wherein a signal state indicates presence or absence of ternary complex formed at the next template position by each individual mixture, thereby determining a series of signal states that encodes a base call for the next template position; and (c) decoding the series of signal states to distinguish a correct base call for the next template position from an error in the base call.

Methods and apparatus that increase sequencing-by-binding efficiency

Intensity extraction from oligonucleotide clusters for base calling

Fiducial markers are provided on patterned arrays of the type that may be used for molecular analysis, such as sequencing. The fiducials may have configurations that enhance their detection in image or detection data, that facilitate or improve processing, that provide encoding of useful information, and so forth. Examples of the fiducials may include an 'always on' type that respond to multiple frequencies of radiation used during processing and detection so as to return signals during successive cycles of imaging.

System and method with fiducials responding to multiple excitation frequencies

Presented herein are techniques for indexing of nucleic acid, e.g., for use in conjunction with sequencing. The techniques include generating indexed nucleic acid fragments from an individual sample, whereby the index sequence incorporated into each index site of the nucleic acid fragment is selected from a plurality of distinguishable of index sequences and such that the population of generated nucleic acid fragments represents each index sequence from the plurality. In this manner, the generated indexed nucleic acid fragments from a single sample are indexed with a diverse mix of index sequences that reduce misassignment due to index read errors associated with low sequence diversity.

Nucleic acid indexing techniques

Fiducial markers are provided on patterned arrays of the type that may be used for molecular analysis, such as sequencing. The fiducials may have configurations and layouts that enhance their detection in image or detection data, that facilitate or improve processing, that provide encoding of useful information, and so forth. Examples of the fiducials may include offset layouts that may be useful in detecting the fiducials in different types and approaches in imaging, and that may help to distinguish regions of the array from one another in image data.

System and method with fiducials having offset layouts

The technology disclosed attenuates spatial crosstalk from sequencing images for base calling. The technology disclosed accesses a section of an image output by a biosensor, where the section of the image includes a plurality of pixels depicting intensity emission values from a plurality of clusters within the biosensor and from locations within the biosensor that are adjacent to the plurality of clusters. The plurality of clusters includes a target cluster. The section of the image is convolved with a convolution kernel, to generate a feature map comprising a plurality of features having a corresponding plurality of feature values. A weighted feature value is assigned to the target cluster, where the weighted feature value is based on one or more features values of the plurality of feature values of the feature map. The weighted feature value assigned to the target cluster is processed, to base call the target cluster.

Intensity extraction and crosstalk attenuation using interpolation and adaptation for base calling

Fiducial markers are provided on patterned arrays of the type that may be used for molecular analysis, such as sequencing. The fiducials may have configurations that enhance their detection in image or detection data, that facilitate or improve processing, that provide encoding of useful information, and so forth. Examples of the fiducials may include a non-closed shape that may encode information, allow for bubbles to escape during manufacture, and provide additional advantages over closed shape fiducials.

System and method with fiducials of non-closed shapes

The technology disclosed generates variation correction coefficients on a cluster-by-cluster basis to correct inter-cluster intensity profile variation for improved base calling. An amplification coefficient corrects scale variation. Channel-specific offset coefficients correct shift variation along respective intensity channels. The variation correction coefficients for a target cluster are generated based on combining analysis of historic intensity data generated for the target cluster at preceding sequencing cycles of a sequencing run with analysis of current intensity data generated for the target cluster at a current sequencing cycle of the sequencing run. The variation correction coefficients are then used to correct next intensity data generated for the target cluster at a next sequencing cycle of the sequencing run. The corrected next intensity data is then used to base call the target cluster at the next sequencing cycle.

Growing community of inventors

Encinitas, CA, United States of America

John S Vieceli