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).

• binny: an automated binning algorithm to recover high-quality genomes from complex metagenomic datasets.

  PMID 36239393 · PMC9677464 · Briefings in bioinformatics · 2022 · 8 claims · 8 setups

  Has reproduction · 67

  binny outperforms or is highly competitive with commonly used and state-of-the-art binning methods (MetaBAT2, MaxBin2, CONCOCT, VAMB, SemiBin, MetaDecoder)

  cami real-world metagenomic binned genome binning mag

• Compression of structured high-throughput sequencing data.

  PMID 24260313 · PMC3832420 · PloS one · 2013 · 8 claims · 7 setups

  Has reproduction · 43

  Leveraging an explicit data schema (separate field encoding, field modeling, template compression, domain modeling) enables stronger compression of HTS alignment data than general-purpose compression of serialized bytes.

  benchmark ten rna-seq exome genome

• Hobbes: optimized gram-based methods for efficient read alignment.

  PMID 22199254 · PMC3315303 · Nucleic acids research · 2012 · 8 claims · 4 setups

  Has reproduction · 83

  Hobbes, a gram-based short-read mapper supporting Hamming and edit distance, is faster than all other read-mapping programs tested while maintaining high mapping quality.

  genome hg18 example reference read-mapping character-substitution algorithmic

• CellFishing.jl: an ultrafast and scalable cell search method for single-cell RNA sequencing.

  PMID 30744683 · PMC6371477 · Genome biology · 2019 · 8 claims · 8 setups

  Has reproduction · 97

  CellFishing.jl searches prebuilt databases for cells with similar expression patterns with high accuracy and throughput using locality-sensitive hashing.

  baron2016 shekhar2016 plass2018 tabulamuris scrna-seq benchmarking self-mapping

• 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

  Full-text index only

  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

  modeled analytic factorial power