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AtlasGrabber: a software facilitating the high throughput analysis of the human protein atlas online database

BACKGROUND: The human protein atlas (HPA) is an online database containing large sets of protein expression data in normal and cancerous tissues in image form from immunohistochemically (IHC) stained tissue microarrays. In these, the tissue architecture is preserved and thus provides information on...

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Autores principales: Bozoky, Benedek, Szekely, Laszlo, Ernberg, Ingemar, Savchenko, Andrii
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758778/
https://www.ncbi.nlm.nih.gov/pubmed/36526955
http://dx.doi.org/10.1186/s12859-022-05097-9
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author Bozoky, Benedek
Szekely, Laszlo
Ernberg, Ingemar
Savchenko, Andrii
author_facet Bozoky, Benedek
Szekely, Laszlo
Ernberg, Ingemar
Savchenko, Andrii
author_sort Bozoky, Benedek
collection PubMed
description BACKGROUND: The human protein atlas (HPA) is an online database containing large sets of protein expression data in normal and cancerous tissues in image form from immunohistochemically (IHC) stained tissue microarrays. In these, the tissue architecture is preserved and thus provides information on the spatial distribution and localization of protein expression at the cellular and extracellular levels. The database is freely available online through the HPA website but currently without support for large-scale screening and analysis of the images in the database. Features like spatial information are typically lacking in gene expression datasets from homogenized tissues or single-cell analysis. To enable high throughput analysis of the HPA database, we developed the AtlasGrabber software. It is available freely under an open-source license. Based on a predefined gene list, the software fetches the images from the database and displays them for the user. Several filters for specific antibodies or images enable the user to customize her/his image analysis. Up to four images can be displayed simultaneously, which allows for the comparison of protein expression between different tissues and between normal and cancerous tissues. An additional feature is the XML parser that allows the extraction of a list of available antibodies, images, and genes for specific tissues or cancer types from the HPA’s database file. RESULTS: Compared to existing software designed for a similar purpose, ours provide more functionality and is easier to use. To demonstrate the software’s usability, we identified six new markers of basal cells of the prostate. A comparison to prostate cancer showed that five of them are absent in prostate cancer. CONCLUSIONS: The HPA is a uniquely valuable database. By facilitating its usefulness with the AtlasGrabber, we enable researchers to exploit its full capacity. The loss of basal cell markers is diagnostic for prostate cancer and can help refine the histopathological diagnosis of prostate cancer. As proof of concept, with the AtlasGrabber we identified five new potential biomarkers specific for prostate basal cells which are lost in prostate cancer and thus can be used for prostate cancer diagnostics.
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spelling pubmed-97587782022-12-18 AtlasGrabber: a software facilitating the high throughput analysis of the human protein atlas online database Bozoky, Benedek Szekely, Laszlo Ernberg, Ingemar Savchenko, Andrii BMC Bioinformatics Software BACKGROUND: The human protein atlas (HPA) is an online database containing large sets of protein expression data in normal and cancerous tissues in image form from immunohistochemically (IHC) stained tissue microarrays. In these, the tissue architecture is preserved and thus provides information on the spatial distribution and localization of protein expression at the cellular and extracellular levels. The database is freely available online through the HPA website but currently without support for large-scale screening and analysis of the images in the database. Features like spatial information are typically lacking in gene expression datasets from homogenized tissues or single-cell analysis. To enable high throughput analysis of the HPA database, we developed the AtlasGrabber software. It is available freely under an open-source license. Based on a predefined gene list, the software fetches the images from the database and displays them for the user. Several filters for specific antibodies or images enable the user to customize her/his image analysis. Up to four images can be displayed simultaneously, which allows for the comparison of protein expression between different tissues and between normal and cancerous tissues. An additional feature is the XML parser that allows the extraction of a list of available antibodies, images, and genes for specific tissues or cancer types from the HPA’s database file. RESULTS: Compared to existing software designed for a similar purpose, ours provide more functionality and is easier to use. To demonstrate the software’s usability, we identified six new markers of basal cells of the prostate. A comparison to prostate cancer showed that five of them are absent in prostate cancer. CONCLUSIONS: The HPA is a uniquely valuable database. By facilitating its usefulness with the AtlasGrabber, we enable researchers to exploit its full capacity. The loss of basal cell markers is diagnostic for prostate cancer and can help refine the histopathological diagnosis of prostate cancer. As proof of concept, with the AtlasGrabber we identified five new potential biomarkers specific for prostate basal cells which are lost in prostate cancer and thus can be used for prostate cancer diagnostics. BioMed Central 2022-12-17 /pmc/articles/PMC9758778/ /pubmed/36526955 http://dx.doi.org/10.1186/s12859-022-05097-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Software
Bozoky, Benedek
Szekely, Laszlo
Ernberg, Ingemar
Savchenko, Andrii
AtlasGrabber: a software facilitating the high throughput analysis of the human protein atlas online database
title AtlasGrabber: a software facilitating the high throughput analysis of the human protein atlas online database
title_full AtlasGrabber: a software facilitating the high throughput analysis of the human protein atlas online database
title_fullStr AtlasGrabber: a software facilitating the high throughput analysis of the human protein atlas online database
title_full_unstemmed AtlasGrabber: a software facilitating the high throughput analysis of the human protein atlas online database
title_short AtlasGrabber: a software facilitating the high throughput analysis of the human protein atlas online database
title_sort atlasgrabber: a software facilitating the high throughput analysis of the human protein atlas online database
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758778/
https://www.ncbi.nlm.nih.gov/pubmed/36526955
http://dx.doi.org/10.1186/s12859-022-05097-9
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