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 · 49
EDGE COVID-19: a web platform to generate submission-ready genomes from SARS-CoV-2 sequencing efforts.
PMID 35561186 · PMC9113274 · Bioinformatics (Oxford, England) · 2022 · 7 claims · 5 setups
EDGE COVID-19 (EC-19) is a web-based platform that automates QC, reference-based variant/consensus calling, lineage determination, and submission of SARS-CoV-2 genomes and metadata to GenBank, GISAID and INSDC for both Illumina and ONT data.
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Has reproduction · 95
MetaMap: an atlas of metatranscriptomic reads in human disease-related RNA-seq data.
PMID 29901703 · PMC6025204 · GigaScience · 2018 · 6 claims · 7 setups
A two-step 'omni' RNA-seq pipeline (MetaMap) combining STAR human alignment with CLARK-S metagenomic classification can quantify archaeal, bacterial, and viral reads from the non-human read fraction of human RNA-seq data
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Has reproduction · 80
VGEA: an RNA viral assembly toolkit.
PMID 34567846 · PMC8428259 · PeerJ · 2021 · 8 claims · 5 setups
VGEA is a Snakemake workflow that chains existing tools (fastp, BWA, SAMtools, IVA, shiver, SeqKit, QUAST, MultiQC) into an all-in-one RNA viral genome assembly pipeline
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Has reproduction · 83
Current status of use of high throughput nucleotide sequencing in rheumatology.
PMID 33408124 · PMC7789458 · RMD open · 2021 · 8 claims · 4 setups
RNA-Seq is the most represented HTS assay in rheumatology research (n=457, 65%), used for biomarker identification in blood or synovial tissue
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Has reproduction · 100
Prediction of Antimicrobial Resistance in Gram-Negative Bacteria From Whole-Genome Sequencing Data.
PMID 32528441 · PMC7262952 · Frontiers in microbiology · 2020 · 8 claims · 4 setups
WGS data enables prediction of antimicrobial resistance in Gram-negative bacteria using machine learning