Korthauer et al., 2019 - Google Patents
A practical guide to methods controlling false discoveries in computational biologyKorthauer et al., 2019
View HTML- Document ID
- 15717958131233696242
- Author
- Korthauer K
- Kimes P
- Duvallet C
- Reyes A
- Subramanian A
- Teng M
- Shukla C
- Alm E
- Hicks S
- Publication year
- Publication venue
- Genome biology
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Snippet
Background In high-throughput studies, hundreds to millions of hypotheses are typically tested. Statistical methods that control the false discovery rate (FDR) have emerged as popular and powerful tools for error rate control. While classic FDR methods use only p …
- 230000001276 controlling effect 0 title abstract description 14
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- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/18—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for functional genomics or proteomics, e.g. genotype-phenotype associations, linkage disequilibrium, population genetics, binding site identification, mutagenesis, genotyping or genome annotation, protein-protein interactions or protein-nucleic acid interactions
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- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
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- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
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- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/22—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for sequence comparison involving nucleotides or amino acids, e.g. homology search, motif or SNP [Single-Nucleotide Polymorphism] discovery or sequence alignment
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- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/20—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for hybridisation or gene expression, e.g. microarrays, sequencing by hybridisation, normalisation, profiling, noise correction models, expression ratio estimation, probe design or probe optimisation
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