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).

• EGASP: the human ENCODE Genome Annotation Assessment Project.

  PMID 16925836 · PMC1810551 · Genome biology · 2006 · 8 claims · 6 setups

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  Best-performing computational gene prediction methods correctly predict at least one transcript for close to 70% of annotated genes in the ENCODE regions.

  encode computational manual rt-pcr

• Detecting natural selection by empirical comparison to random regions of the genome.

  PMID 19783549 · PMC2778377 · Human molecular genetics · 2009 · 8 claims · 5 setups

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  Comparing candidate loci to empirically matched random genomic regions (ENCODE data) avoids the strong demographic/mutation assumptions required by theoretical neutral models and provides a robust test for selection

  ceu genomic simulated long-read snp population

• What can genome-wide association studies tell us about the genetics of common disease?

  PMID 18454206 · PMC2323402 · PLoS genetics · 2008 · 8 claims · 4 setups

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  Apparent patterns of common, low-effect disease-associated alleles largely reflect statistical power of studies rather than the true underlying distribution of disease variants

  case gwa simulated literature cochran-armitage computer

• Power analysis for genome-wide association studies.

  PMID 17725844 · PMC2042984 · BMC genetics · 2007 · 8 claims · 6 setups

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  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.

  hapmap power pairwise tag

• Vertebrate gene finding from multiple-species alignments using a two-level strategy.

  PMID 16925840 · PMC1810555 · Genome biology · 2006 · 8 claims · 5 setups

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  DOGFISH cleanly separates a multi-species alignment classifier (RVM cascade) from an HMM-based structure predictor, avoiding tight coupling of alignment complexity with HMM formalism

  genomic encode entire chromosome multi-species hmm-based classifier