Top Tweets for #ReferenceDatasets
Methylation reference datasets from quartet DNA materials for benchmarking epigenome sequencing. #DNAmethylation #ReferenceDatasets #BenchmarkingMaterials #Epigenomics #Sequencing #Genomics @NatureComms
https://t.co/KQpY8jyTbB

Accurate somatic small variant discovery for multiple sequencing technologies with DeepSomatic. #SomaticVariants #ShortReads #LongReads #VariantCalling #Genomics #Bioinformatics #ToolsBenchmarking #ReferenceDatasets @NatureBiotech
https://t.co/a7cngfPMTM

A multi-platform reference for somatic structural variation detection. #StructuralVariants #SVs #SomaticSVtruthSet #RawSequenceDatasets #ReferenceDatasets #Benchmarking #Sequencing #Bioinformatics
https://t.co/MYvsDrnKIE @CellGenomics
Comprehensive assessment of differential ChIP-seq tools guides optimal algorithm selection. #ChiPseq #ToolsBenchmarking #ReferenceDatasets #Bioinformatics
https://t.co/ekL6nPjK2z @GenomeBiology
Whole genome and exome sequencing reference datasets from a multi-center and cross-platform benchmark study. #CancerGenomics #SEQC2 #WGS #WES #ReferenceDatasets #LibraryPreps #Sequencers #DataPipelines #Benchmarking
https://t.co/byY55AeH3b @ScientificData
Expanding the Galaxy’s reference data. #Galaxy #ReferenceDatasets #DataManagement https://t.co/57FU0wo9V5 @biorxivpreprint #bioinformatics
Tools like the one proposed by @shenxingxing1 in this tweet are important part of the mapping of new #genomics datasets to the current knowledge of the #TreeofLife . Yeasts lend themselves to #highthroughput molecular analyses that turn them into fantastic #referencedatasets
Looking for an empirical genome-scale data to evaluate performance of #phylogenetic program or to conduct analysis of #phylogenomic diagnosis? Please check a 2,408-gene, 343-taxon data matrix (1,162,805 sites) from @RokasLab @HittingerLab & many others! https://t.co/Y0ZQxCPbxF

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