Microarray-Based Gene Expression Analysis for Veterinary Pathologists: A Review
| Autor: | Barbara B. Raddatz, Reiner Ulrich, Katja Matheis, Ulrich Deschl, Ingo Spitzbarth, Arno Kalkuhl, Wolfgang Baumgärtner |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Veterinary Medicine Veterinary medicine Computer science Target audience Scientific literature 03 medical and health sciences User-Computer Interface Animals Cluster Analysis Humans Biomarker discovery Cluster analysis Pathology Veterinary Oligonucleotide Array Sequence Analysis General Veterinary Microarray analysis techniques Sequence Analysis RNA Gene Expression Profiling High-Throughput Nucleotide Sequencing Gene expression profiling Pathologists 030104 developmental biology Gene chip analysis DNA microarray Transcriptome Software |
| Zdroj: | Veterinary Pathology |
| ISSN: | 1544-2217 |
| Popis: | High-throughput, genome-wide transcriptome analysis is now commonly used in all fields of life science research and is on the cusp of medical and veterinary diagnostic application. Transcriptomic methods such as microarrays and next-generation sequencing generate enormous amounts of data. The pathogenetic expertise acquired from understanding of general pathology provides veterinary pathologists with a profound background, which is essential in translating transcriptomic data into meaningful biological knowledge, thereby leading to a better understanding of underlying disease mechanisms. The scientific literature concerning high-throughput data-mining techniques usually addresses mathematicians or computer scientists as the target audience. In contrast, the present review provides the reader with a clear and systematic basis from a veterinary pathologist's perspective. Therefore, the aims are (1) to introduce the reader to the necessary methodological background; (2) to introduce the sequential steps commonly performed in a microarray analysis including quality control, annotation, normalization, selection of differentially expressed genes, clustering, gene ontology and pathway analysis, analysis of manually selected genes, and biomarker discovery; and (3) to provide references to publically available and user-friendly software suites. In summary, the data analysis methods presented within this review will enable veterinary pathologists to analyze high-throughput transcriptome data obtained from their own experiments, supplemental data that accompany scientific publications, or public repositories in order to obtain a more in-depth insight into underlying disease mechanisms. |
| Databáze: | OpenAIRE |
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