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Shaped singular spectrum analysis for quantifying gene expression, with application to the early Drosophila embryo.

Shlemov A, Golyandina N, Holloway D, Spirov A - Biomed Res Int (2015)

Bottom Line: We consider the commonly used cylindrical projection of the ellipsoidal Drosophila embryo.We demonstrate how circular and shaped versions of 2D-SSA help to decompose expression data into identifiable components (such as trend and noise), as well as separating signals from different genes.Detection and improvement of under- and overcorrection in multichannel imaging is addressed, as well as the extraction and analysis of 3D features in 3D gene expression patterns.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Mathematics and Mechanics, St. Petersburg State University, Universitetsky Pr. 28, Peterhof, St. Petersburg 198504, Russia.

ABSTRACT
In recent years, with the development of automated microscopy technologies, the volume and complexity of image data on gene expression have increased tremendously. The only way to analyze quantitatively and comprehensively such biological data is by developing and applying new sophisticated mathematical approaches. Here, we present extensions of 2D singular spectrum analysis (2D-SSA) for application to 2D and 3D datasets of embryo images. These extensions, circular and shaped 2D-SSA, are applied to gene expression in the nuclear layer just under the surface of the Drosophila (fruit fly) embryo. We consider the commonly used cylindrical projection of the ellipsoidal Drosophila embryo. We demonstrate how circular and shaped versions of 2D-SSA help to decompose expression data into identifiable components (such as trend and noise), as well as separating signals from different genes. Detection and improvement of under- and overcorrection in multichannel imaging is addressed, as well as the extraction and analysis of 3D features in 3D gene expression patterns.

No MeSH data available.


hb ((a) to (d)): original image, unstriped pattern, stripes, and residual noise.
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fig8: hb ((a) to (d)): original image, unstriped pattern, stripes, and residual noise.

Mentions: Simultaneously, with removing stripes, this process also decomposes an image into pattern and noise (residuals): Figure 8 shows reconstruction of hb expression from the “unstriped” components 1–4, alongside the striped components (strongly affected by ftz) 5–12 and the residuals. Circular 2D-SSA provides a method for removing under- or overcorrection in the unmixing algorithm and therefore of clearing gene patterns from crosstalk effects. For an image without stripes, 2D-SSA produces a direct decomposition into pattern and noise. We show here that SSA decomposition is robust for data with crosstalk stripes.


Shaped singular spectrum analysis for quantifying gene expression, with application to the early Drosophila embryo.

Shlemov A, Golyandina N, Holloway D, Spirov A - Biomed Res Int (2015)

hb ((a) to (d)): original image, unstriped pattern, stripes, and residual noise.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4402483&req=5

fig8: hb ((a) to (d)): original image, unstriped pattern, stripes, and residual noise.
Mentions: Simultaneously, with removing stripes, this process also decomposes an image into pattern and noise (residuals): Figure 8 shows reconstruction of hb expression from the “unstriped” components 1–4, alongside the striped components (strongly affected by ftz) 5–12 and the residuals. Circular 2D-SSA provides a method for removing under- or overcorrection in the unmixing algorithm and therefore of clearing gene patterns from crosstalk effects. For an image without stripes, 2D-SSA produces a direct decomposition into pattern and noise. We show here that SSA decomposition is robust for data with crosstalk stripes.

Bottom Line: We consider the commonly used cylindrical projection of the ellipsoidal Drosophila embryo.We demonstrate how circular and shaped versions of 2D-SSA help to decompose expression data into identifiable components (such as trend and noise), as well as separating signals from different genes.Detection and improvement of under- and overcorrection in multichannel imaging is addressed, as well as the extraction and analysis of 3D features in 3D gene expression patterns.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Mathematics and Mechanics, St. Petersburg State University, Universitetsky Pr. 28, Peterhof, St. Petersburg 198504, Russia.

ABSTRACT
In recent years, with the development of automated microscopy technologies, the volume and complexity of image data on gene expression have increased tremendously. The only way to analyze quantitatively and comprehensively such biological data is by developing and applying new sophisticated mathematical approaches. Here, we present extensions of 2D singular spectrum analysis (2D-SSA) for application to 2D and 3D datasets of embryo images. These extensions, circular and shaped 2D-SSA, are applied to gene expression in the nuclear layer just under the surface of the Drosophila (fruit fly) embryo. We consider the commonly used cylindrical projection of the ellipsoidal Drosophila embryo. We demonstrate how circular and shaped versions of 2D-SSA help to decompose expression data into identifiable components (such as trend and noise), as well as separating signals from different genes. Detection and improvement of under- and overcorrection in multichannel imaging is addressed, as well as the extraction and analysis of 3D features in 3D gene expression patterns.

No MeSH data available.