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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Has reproduction · 74
ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia.
PMID 22955991 · PMC3431496 · Genome research · 2012 · 8 claims · 8 setups
ENCODE/modENCODE define a set of working standards and guidelines for ChIP-seq covering antibody validation, experimental replication, sequencing depth, data/metadata reporting, and data quality assessment.
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JIGSAW, GeneZilla, and GlimmerHMM: puzzling out the features of human genes in the ENCODE regions.
PMID 16925843 · PMC1810558 · Genome biology · 2006 · 8 claims · 4 setups
Adding model states for specific biological features (signal peptides, CpG islands, etc.) to non-comparative GHMM gene finders did little or nothing to enhance predictive accuracy, sometimes reducing it.
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Has reproduction · 69
A comparison across non-model animals suggests an optimal sequencing depth for de novo transcriptome assembly.
PMID 23496952 · PMC3655071 · BMC genomics · 2013 · 8 claims · 8 setups
Representative de novo transcriptome assemblies are generated with as few as ~20 million reads for single-tissue samples and ~30 million reads for whole animals at the mRNA-coverage level.
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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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CONTRAST: a discriminative, phylogeny-free approach to multiple informant de novo gene prediction.
PMID 18096039 · PMC2246271 · Genome biology · 2007 · 8 claims · 5 setups
CONTRAST predicts exact coding region structures for 65% more human genes than the previous state-of-the-art de novo predictor (N-SCAN)
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Power analysis for genome-wide association studies.
PMID 17725844 · PMC2042984 · BMC genetics · 2007 · 8 claims · 6 setups
Developed a method to compute genome-wide association study power using tag SNPs and representative population genotype data (HapMap), equivalent to the cumulative r2-adjusted power of Jorgenson and Witte.