STARCall integrates image stitching, alignment, and read calling to enable scalable analysis of in situ sequencing data
Fig 4
STARCall filters out background and corrects for differences in intensity when calling reads.
A) Key steps for read calling by STARCall, including background filtering, amplicon colony detection, base calling and read assembly. B) Sequencing images before and after the Laplacian of Gaussian filter from Feldman et al. and the Gaussian filter and normalization from STARCall. Amplicon colonies in each cell appear as small bright dots in the channel corresponding to their nucleobase. Violet = G, Blue = T, Green = A, Red = C. A 10 micron scale bar is included in the bottom right image. C) 50th (left) and 99.9th (right) percentile pixel intensity of sequencing images in VIS-seq image set 1.1. The 50th percentile approximates background and the 99.9th percentile approximates the intensity of signal generated by amplicon colonies. D) The percent of cells with barcodes found in the previously determined lookup table for each experiment when reads were called by STARCall (green) or the Feldman et al. pipeline (blue). E) Test set performance of STARCall (green) and the Feldman et al. pipeline (blue). Five hundred cells were selected and manually annotated with their sequence F) The read count per cell of STARCall (left) and the Feldman et al. pipeline (right) on image set 2.1. G) The nucleotide frequency at each cycle from reads called by STARCall (left) or the Feldman et al. [4] pipeline (right), with the expected frequency in the barcode library shown by dashed lines.