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Robust principal component analysis for accurate outlier sample detection in RNA-Seq data
BACKGROUND: High throughput RNA sequencing is a powerful approach to study gene expression. Due to the complex multiple-steps protocols in data acquisition, extreme deviation of a sample from samples of the same treatment group may occur due to technical variation or true biological differences. The...
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| 出版年: | BMC Bioinformatics |
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| 主要な著者: | , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
BioMed Central
2020
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| 主題: | |
| オンライン・アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7324992/ https://ncbi.nlm.nih.gov/pubmed/32600248 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-020-03608-0 |
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