Illumina Corporation

Illumina Cambridge Limited

Hongji Ren

John A Moon

Robert Ezra Langlois

Andrew Antony Brown

Wayne N George

Daniel Bratton

Joseph Francis Pinto

Darren Segale

Ryan Christopher Smith

Bo Lu

Austin Corbett

Stanley S Hong

Michael J Carney

Kevin Wayne Bartig

Rico Otto

Olga Andreevna Souverneva

Jonathan Mark Boutell

M Shane Bowen

Peter Clarke Newman

Ryan M Smith

Simon Prince

Alex Nemiroski

Gary Mark Skinner

Kenny Chen

Bahram Ghaffarzadeh Kermani

Yu Hsuan Chen

Theo Kotseroglou

Nels A Olson

Yu Chen

A structured illumination microscopy (SIM) system comprises: a light source; a light-structuring component to provide light from the light source with a SIM pattern for performing illuminations of a sample at a substrate having a substrate pattern, wherein a pitch of the SIM pattern is based on a characteristic of the substrate pattern; and an image sensor to detect emissions that the sample generates in response to the illuminations.

Performing structured illumination microscopy on a patterned substrate

A method is used to generate a distortion model for a structured illumination microscopy (SIM) optical system. A sliding window is moved in relation to a plurality of images to define a plurality of sub-tiles. Each sub-tile represents a portion of the corresponding image. Parameters are estimated for each sub-tiles. The parameters include two or more parameters selected from the group consisting of modulation, angle, spacing, phase offset, and phase deviation. A full width at half maximum (FWHM) value associated with each sub-tile is estimated. A distortion model is estimated, based at least in part on a combination of the estimated parameters and FWHM values stored in the predetermined format and an estimated center window parameter. A two-dimensional image may be generated, based at least in part on the estimated distortion model. The two-dimensional image may include representations indicating where distortions occur in the optical system.

Apparatus and method of estimating values from images

A method for scanning a microarray, including (a) providing a microarray to an optical scanner, wherein the microarray includes a surface having features having different target molecules; (b) scanning the surface in the x or y direction to acquire optical signals from the features at sequential regions of the surface, wherein the focus setting between the optical scanner and the surface is dynamically controlled in real time by repeatedly (i) adding a predetermined focal offset, thereby introducing an error in the focus setting, and (ii) adjusting the focus setting to reduce the error in the focus setting, thereby acquiring the optical signals from different regions at different degrees of focus such that a subset of the regions that are scanned have an introduced focus error; and (c) analyzing the optical signals that are obtained at the different degrees of focus to identify the different target molecules.

Dynamic autofocus method and system for assay imager

The present disclosure relates to polymer coatings covalently attached to the surface of a substrate and the preparation of the polymer coatings, such as poly(N-(5-azidoacetamidylpentyl)acrylamide-co-acrylamide) (PAZAM), in the formation and manipulation of substrates, such as molecular arrays and flow cells. The present disclosure also relates to methods of preparing a substrate surface by using beads coated with a covalently attached polymer, such as PAZAM, and the method of determining a nucleotide sequence of a polynucleotide attached to a substrate surface described herein.

Polymer coatings

In an example of the method, a functionalized coating layer is applied in depressions of a patterned flow cell substrate. The depressions are separated by interstitial regions. A primer is grafted to the functionalized coating layer to form a grafted functionalized coating layer in the depressions. A hydrogel is applied on at least the grafted functionalized coating layer.

Flow cells with hydrogel coating

A method is used to generate a report presenting parameter values corresponding to a structured illumination microscopy (SIM) optical system. The parameter values are based at least in part on the performed modulation calculation corresponding to an image set captured with the SIM optical system. A minimum FWHM slice is identified, based at least in part on an average FWHM value across the images in the first image set. Parameter estimation is performed on the identified minimum FWHM slice. Best in-focus parameters are identified based at least in part on the performed estimation. A phase estimate is performed for each image in the set. A modulation calculation is performed based at least in part on the identified best in-focus parameters. The report is based at least in part on the performed modulation calculation.

Apparatus and method of providing parameter estimation

Implementations of the disclosure are directed to predicting structured illumination parameters for a particular point in time, space, and/or temperature using estimates of structured illumination parameters obtained from structured illumination images captured by a structured illumination system. Particular implementations are directed to predicting structured illumination frequency, phase, orientation, and/or modulation order parameters.

Predicting structured illumination parameters

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San Diego, CA, United States of America

Hongji Ren