Illumina Corporation

Illumina Cambridge Limited

Other

Illumina Software, Inc.

Nitin Udpa

Eric Jon Ojard

Rami Mehio

John S Vieceli

Gavin Derek Parnaby

Abde Ali Hunaid Kagalwalla

Beng Keong Ang

Venkatesh Mysore Nagaraja Rao

Bo Lu

Stephen Rawlings

Dustin W Blair

Linh Tran

Nicholas Scheidler

Method includes positioning a first carrier assembly on a system stage. The carrier assembly includes a support frame having an inner frame edge that defines a window of the support frame. The first carrier assembly includes a first substrate that is positioned within the window and surrounded by the inner frame edge. The first substrate has a sample thereon. The method includes detecting optical signals from the sample of the first substrate. The method also includes replacing the first carrier assembly on the system stage with a second carrier assembly on the system stage. The second carrier assembly includes the support frame and an adapter plate held by the support frame. The second carrier assembly has a second substrate held by the adapter plate that has a sample thereon. The method also includes detecting optical signals from the sample of the second substrate.

Methods, carrier assemblies, and systems for imaging samples for biological or chemical analysis

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

Intensity extraction from oligonucleotide clusters for base calling

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

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.

Systems and methods for per-cluster intensity correction and base calling

The technology disclosed attenuates spatial crosstalk from sequencing images for base calling. In particular, the technology disclosed accesses an image whose pixels depict intensity emissions from a target cluster and intensity emissions from additional adjacent clusters. The pixels include a center pixel that contains a center of the target cluster. Each pixel in the pixels is divisible into a plurality of subpixels. Depending upon a particular subpixel, in a plurality of subpixels of the center pixel, which contains the center of the target cluster, the technology disclosed selects, from a bank of subpixel lookup tables, a subpixel lookup table that corresponds to the particular subpixel. The selected subpixel lookup table contains pixel coefficients that are configured to maximizes a signal-to-noise ratio. The technology disclosed element-wise multiplies the pixel coefficients with the pixels and determines a weighted sum.

Equalization-based image processing and spatial crosstalk attenuator

A method for tracking an item that includes the steps of (a) providing an item having a solid polymer material; (b) irradiating the item to create a spatial pattern of optical modifications in the polymer material, wherein the spatial pattern of optical modifications includes a code that indicates information; and (c) detecting the pattern of optical modifications, thereby determining the information.

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San Diego, CA, United States of America

Nitin Udpa