Experiments
Searchable full-text extractions: founding hypothesis, core claims, experimental setups, key results and statistics — pulled out of each paper as structure. Search a cell line, an assay or an entity (e.g. HUH7) and find every paper that worked with it. This corpus stands on its own: most entries carry no reproduction assessment (yet).
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A method for detecting epistasis in genome-wide studies using case-control multi-locus association analysis.
PMID 18667089 · PMC2533022 · BMC genomics · 2008 · 7 claims · 2 setups
HFCC is a method/software for genome-wide epistasis detection using case-control multi-locus association analysis, combining a fast computing algorithm with flexibility to test a variety of epistatic models.
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Incorporation of genetic model parameters for cost-effective designs of genetic association studies using DNA pooling.
PMID 17634103 · PMC1947971 · BMC genomics · 2007 · 8 claims · 4 setups
A closed-form approximation to the F-test non-centrality parameter (NCP) incorporating genetic model parameters (disease allele frequency, marker allele frequency, prevalence, genotype relative risk, sample size, genetic model, number of pools/replicates, machine variability) can be used to compute power for DNA pooling association studies
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What can genome-wide association studies tell us about the genetics of common disease?
PMID 18454206 · PMC2323402 · PLoS genetics · 2008 · 8 claims · 4 setups
Apparent patterns of common, low-effect disease-associated alleles largely reflect statistical power of studies rather than the true underlying distribution of disease variants
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A simple and efficient algorithm for genome-wide homozygosity analysis in disease.
PMID 19756043 · PMC2758715 · Molecular systems biology · 2009 · 8 claims · 4 setups
A genome-wide AH analysis (GAHA) algorithm can identify disease-associated loci by comparing frequencies of homozygous segments between cases and controls using a z-statistic proportion test
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Size matters: just how big is BIG?: Quantifying realistic sample size requirements for human genome epidemiology.
PMID 18676414 · PMC2639365 · International journal of epidemiology · 2009 · 7 claims · 2 setups
Conventional power calculations for case-control studies disregard analytic complexity (e.g. clinical assessment errors, unmeasured aetiological determinants) and can seriously underestimate true sample size requirements
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Has reproduction · 88
pwrEWAS: a user-friendly tool for comprehensive power estimation for epigenome wide association studies (EWAS).
PMID 31035919 · PMC6489300 · BMC bioinformatics · 2019 · 8 claims · 8 setups
pwrEWAS is a user-friendly tool for comprehensive power estimation for two-group EWAS comparisons using Illumina Human Methylation BeadChip data.
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Testing groups of genomic locations for enrichment in disease loci using linkage scan data: a method for hypothesis testing.
PMID 16848972 · PMC3525155 · Human genomics · 2006 · 8 claims · 2 setups
A method testing enrichment of a group of genomic locations for disease loci by comparing the average NPL score of the group to a null distribution from randomly drawn groups of equal size
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A statistical model to identify differentially expressed proteins in 2D PAGE gels.
PMID 19763172 · PMC2734266 · PLoS computational biology · 2009 · 7 claims · 5 setups
A mixture likelihood model incorporating both detected and non-detected proteins has higher statistical power to detect differential expression than standard approaches like the Student's t-test.
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Calibrating the performance of SNP arrays for whole-genome association studies.
PMID 18584036 · PMC2432039 · PLoS genetics · 2008 · 8 claims · 7 setups
Previous SNP array genetic coverage estimates are inflated due to SNP overfitting and sample overfitting, since they were evaluated on the same HapMap SNPs/individuals used to design the arrays.
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Commonality of functional annotation: a method for prioritization of candidate genes from genome-wide linkage studies.
PMID 18263617 · PMC2275105 · Nucleic acids research · 2008 · 8 claims · 7 setups
Genes correlated with a common complex trait are more likely to share GO functional annotations than genes not correlated with that trait