New methods for computational decomposition of whole-mount in situ images enable effective curation of a large, highly redundant collection of Xenopus images.
New methods for computational decomposition of whole-mount in situ images enable effective curation of a large, highly redundant collection of Xenopus images.
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DOI：
10.1371/journal.pcbi.1006077
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发表时间：
2018-08
影响因子：
4.3
通讯作者：
Gilchrist MJ
中科院分区：
文献类型：
--
作者：
Patrushev I;James-Zorn C;Ciau-Uitz A;Patient R;Gilchrist MJ
基因表达的精确解剖位置是大多数模型生物的基因功能的重要组成部分。 ，特别是在果蝇中表现出均匀的形状和大纲，我们在这里解决了基因计算分析的挑战。在Xenopus中的表达，其中感兴趣的发育阶段涵盖了各种胚胎的大小和形状我们报告了一组能够处理具有可变特征的大图像集的计算工具。胚胎中的组织化学染色和自然猪区域都可以根据基因表达模式的相似性从相同基因和发育阶段进行分类，而没有有关相对方向的信息。原位杂交图像，使我们可以在不同的胚胎方向选择表达模式的代表性图像。以有效的方式进入公共领域。
研究基因在发育生物中的功能的重要组成部分是对何时何地表达基因的理解。在不同的开发阶段拍摄此类处理的胚胎，以建立少量这些表达模式图像的故事。从训练有素的科学家中，大量图像的信息将在时间上进行巨大的投资。到目前为止，没有纯粹用于分析基因表达的计算方法。针对多种背景的胚胎，在胚胎中分别识别基因表达和自然色素沉着的区域。脊椎动物胚胎学中的解剖基因表达注释。
The precise anatomical location of gene expression is an essential component of the study of gene function. For most model organisms this task is usually undertaken via visual inspection of gene expression images by interested researchers. Computational analysis of gene expression has been developed in several model organisms, notably in Drosophila which exhibits a uniform shape and outline in the early stages of development. Here we address the challenge of computational analysis of gene expression in Xenopus, where the range of developmental stages of interest encompasses a wide range of embryo size and shape. Embryos may have different orientation across images, and, in addition, embryos have a pigmented epidermis that can mask or confuse underlying gene expression. Here we report the development of a set of computational tools capable of processing large image sets with variable characteristics. These tools efficiently separate the Xenopus embryo from the background, separately identify both histochemically stained and naturally pigmented regions within the embryo, and can sort images from the same gene and developmental stage according to similarity of gene expression patterns without information about relative orientation. We tested these methods on a large, but highly redundant, collection of 33,289 in situ hybridization images, allowing us to select representative images of expression patterns at different embryo orientations. This has allowed us to put a much smaller subset of these images into the public domain in an effective manner. The ‘isimage’ module and the scripts developed are implemented in Python and freely available on https://pypi.python.org/pypi/isimage/. An important component of research into the function of genes in the developing organism is an understanding of both when and where the gene is expressed. Well established molecular techniques can be used to colour the embryo in regions where the gene of interest appears, and researchers will photograph such treated embryos at different stages of development to build up the story of the gene’s use. Small numbers of these expression pattern images may easily be examined by eye, but getting usable information from large collections of such images would take an enormous investment in time by trained scientists. Computational analysis is much to be preferred, but the task is complex and difficult to generalise. The frog Xenopus is an important model for studying vertebrate development, but up till now has had no purely computational methods available for analysing gene expression. Here we present a suite of computational tools based on a range of mathematical methods, capable of recognising the outline of the embryo against a variety of backgrounds, and within the embryo separately recognising areas of both gene expression and natural pigmentation. These tools work over a wide range of embryo shapes and imaging conditions, and, in our opinion, represent a major step towards full automation of anatomical gene expression annotation in vertebrate embryology.
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影响因子：
1.9
作者：
Segerdell, Erik;Ponferrada, Virgilio G.;Zorn, Aaron M.
通讯作者：
Zorn, Aaron M.
DOI：
10.1093/bioinformatics/btt206
发表时间：
2013-07-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Pruteanu-Malinici I;Majoros WH;Ohler U
通讯作者：
Ohler U
影响因子：
5.8
作者：
Mace, Daniel L.;Varnado, Nicole;Ohler, Uwe
通讯作者：
Ohler, Uwe
DOI：
10.1093/bioinformatics/btq172
发表时间：
2010-06-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Puniyani K;Faloutsos C;Xing EP
通讯作者：
Xing EP
影响因子：
8.3
作者：
BURT, PJ;ADELSON, EH
通讯作者：
ADELSON, EH