Abstract: Provided herein are methods, compositions and systems for identifying spatial gene expression of analytes from glioblastoma derived tissue. The methods discloses herein include using templated ligation probe pairs to identify location of a disease proliferating region in a glioblastoma-derived sample by detecting analytes in the region and hybridizing a ligation product comprising the probe pairs to a capture probe on a spatial array.

Abstract: Systems and methods for spatial analysis of analytes are provided. A data structure is obtained comprising an image, as an array of pixel values, of a sample on a substrate having intersecting border regions, fiducial markers encoding N-digit codes, and a set of capture spots, where at least two border regions includes a fiducial marker. The pixel values are analyzed to identify locations of fiducial markers. The locations are aligned with locations of reference fiducial markers in a template using an alignment algorithm to obtain a final transformation between the fiducial markers in the image and the reference fiducial markers in the template. The final transformation and a coordinate system of the template are used to register the image to the set of capture spots. The registered image is then analyzed in conjunction with spatial analyte data associated with each capture spot, thereby performing spatial analysis of analytes.

Abstract: Provided herein are systems and methods for optimizing feature fill processes. The feature fill optimization systems and methods may be used to optimize feature fill from a small number of patterned wafer tests. The systems and methods may be used for optimizing enhanced feature fill processes including those that include inhibition and/or etch operations along with deposition operations. Results from experiments may be used to calibrate a feature scale behavioral model. Once calibrated, parameter space may be iteratively explored to optimize the process.

Abstract: Provided herein are systems and methods for optimizing feature fill processes. The feature fill optimization systems and methods may be used to optimize feature fill from a small number of patterned wafer tests. The systems and methods may be used for optimizing enhanced feature fill processes including those that include inhibition and/or etch operations along with deposition operations. Results from experiments may be used to calibrate a feature scale behavioral model. Once calibrated, parameter space may be iteratively explored to optimize the process.