protGear: A protein microarray data pre-processing suite Article Swipe
Kennedy Mwai
,
Nelson Kibinge
,
James Tuju
,
Gathoni Kamuyu
,
Rinter Kimathi
,
James Mburu
,
Emily Chepsat
,
Lydia Nyamako
,
Timothy Chege
,
Irene N. Nkumama
,
Samson Kinyanjui
,
Eustasius Musenge
,
Faith Osier
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1016/j.csbj.2021.04.044
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1016/j.csbj.2021.04.044
Protein microarrays are versatile tools for high throughput study of the human proteome, but systematic and non-systematic sources of bias constrain optimal interpretation and the ultimate utility of the data. Published guidelines to limit technical variability whilst maintaining important biological variation favour DNA-based microarrays that often differ fundamentally in their experimental design. Rigorous tools to guide background correction, the quantification of within-sample variation, normalisation, and batch correction specifically for protein microarrays are limited, require extensive investigation and are not centrally accessible. Here, we develop a generic one-stop-shop pre-processing suite for protein microarrays that is compatible with data from the major protein microarray scanners. Our graphical and tabular interfaces facilitate a detailed inspection of data and are coupled with supporting guidelines that enable users to select the most appropriate algorithms to systematically address bias arising in customized experiments. The localization and distribution of background signal intensities determine the optimal correction strategy. A novel function overcomes the limitations in the interpretation of the coefficient of variation when signal intensities are at the lower end of the detection threshold. We demonstrate essential considerations in the experimental design and their impact on a range of algorithms for normalization and minimization of batch effects. Our user-friendly interactive web-based platform eliminates the need for prowess in programming. The open-source R interface includes illustrative examples, generates an auditable record, enables reproducibility, and can incorporate additional custom scripts through its online repository. This versatility will enhance its broad uptake in the infectious disease and vaccine development community.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.csbj.2021.04.044
- OA Status
- gold
- Cited By
- 3
- References
- 41
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3158237616
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3158237616Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.csbj.2021.04.044Digital Object Identifier
- Title
-
protGear: A protein microarray data pre-processing suiteWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-01-01Full publication date if available
- Authors
-
Kennedy Mwai, Nelson Kibinge, James Tuju, Gathoni Kamuyu, Rinter Kimathi, James Mburu, Emily Chepsat, Lydia Nyamako, Timothy Chege, Irene N. Nkumama, Samson Kinyanjui, Eustasius Musenge, Faith OsierList of authors in order
- Landing page
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https://doi.org/10.1016/j.csbj.2021.04.044Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://doi.org/10.1016/j.csbj.2021.04.044Direct OA link when available
- Concepts
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Computer science, Data mining, Protein microarray, DNA microarray, Profiling (computer programming), Suite, Normalization (sociology), Replicate, Scripting language, Biology, History, Anthropology, Archaeology, Sociology, Statistics, Mathematics, Operating system, Gene expression, Biochemistry, GeneTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
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2024: 2, 2022: 1Per-year citation counts (last 5 years)
- References (count)
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41Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| corresponding_author_ids | https://openalex.org/A5013961861 |
| countries_distinct_count | 4 |
| institutions_distinct_count | 13 |
| corresponding_institution_ids | https://openalex.org/I192619145, https://openalex.org/I2841861 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/17 |
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| sustainable_development_goals[0].display_name | Partnerships for the goals |
| citation_normalized_percentile.value | 0.53999595 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |