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2015 ; 2015
(ä): 986436
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Shaped 3D singular spectrum analysis for quantifying gene expression, with
application to the early zebrafish embryo
#MMPMID26495320
Shlemov A
; Golyandina N
; Holloway D
; Spirov A
Biomed Res Int
2015[]; 2015
(ä): 986436
PMID26495320
show ga
Recent progress in microscopy technologies, biological markers, and automated
processing methods is making possible the development of gene expression atlases
at cellular-level resolution over whole embryos. Raw data on gene expression is
usually very noisy. This noise comes from both experimental
(technical/methodological) and true biological sources (from stochastic
biochemical processes). In addition, the cells or nuclei being imaged are
irregularly arranged in 3D space. This makes the processing, extraction, and
study of expression signals and intrinsic biological noise a serious challenge
for 3D data, requiring new computational approaches. Here, we present a new
approach for studying gene expression in nuclei located in a thick layer around a
spherical surface. The method includes depth equalization on the sphere,
flattening, interpolation to a regular grid, pattern extraction by Shaped 3D
singular spectrum analysis (SSA), and interpolation back to original nuclear
positions. The approach is demonstrated on several examples of gene expression in
the zebrafish egg (a model system in vertebrate development). The method is
tested on several different data geometries (e.g., nuclear positions) and
different forms of gene expression patterns. Fully 3D datasets for developmental
gene expression are becoming increasingly available; we discuss the prospects of
applying 3D-SSA to data processing and analysis in this growing field.