Merge Candidates
41 pairs of terms with high embedding similarity that may be duplicates or near-duplicates.
| Term 1 | Term 2 | Similarity | Subset | Decision |
|---|---|---|---|---|
| hotspots1 reference DataType / chromatin accessibility | hotspots2 reference DataType / chromatin accessibility | 0.9513 | chromatin accessibility | |
| maternal haplotype mapping FeatureType / haplotype | paternal haplotype mapping FeatureType / haplotype | 0.9415 | haplotype | |
| distal peaks DataType / peak set | proximal peaks DataType / peak set | 0.9362 | peak set | |
| negative control regions DataType / technical | positive control regions DataType / technical | 0.9174 | technical | |
| sparse gene count matrix DataType / count matrix | sparse transcript count matrix DataType / count matrix | 0.9171 | count matrix | |
| idat green channel DataType / technical | idat red channel DataType / technical | 0.9048 | technical | |
| haplotype-specific nuclease cleavage corrected frequency DataType / chromatin accessibility | haplotype-specific nuclease cleavage frequency DataType / chromatin accessibility | 0.8998 | chromatin accessibility | |
| transposable element TF ancestral origin percent by motif FeatureType / annotation | transposable element TF ancestral origin percent by subfamily FeatureType / annotation | 0.8820 | annotation | |
| maternal variant calls FeatureType / variant | paternal variant calls FeatureType / variant | 0.8790 | variant | |
| differential expression quantifications DataType / quantification | differential splicing quantifications DataType / quantification | 0.8752 | quantification | |
| selected regions for count sequence contribution scores DataType / deep learning | selected regions for predicted signal and sequence contribution scores DataType / deep learning | 0.8727 | deep learning | |
| sparse gRNA count matrix DataType / crispr screen | sparse transcript count matrix DataType / count matrix | 0.8635 | crispr_screen / count_matrix | |
| selected regions for predicted signal and sequence contribution scores DataType / deep learning | selected regions for profile sequence contribution scores DataType / deep learning | 0.8594 | deep learning | |
| merged transcription segment quantifications DataType / quantification | transcription segment quantifications DataType / quantification | 0.8592 | quantification | |
| methylation state at CHG FeatureType / dna methylation | methylation state at CHH FeatureType / dna methylation | 0.8527 | dna methylation | |
| selected regions for predicted bias profile DataType / deep learning | selected regions for predicted signal profile DataType / deep learning | 0.8491 | deep learning | |
| selected regions for count sequence contribution scores DataType / deep learning | selected regions for profile sequence contribution scores DataType / deep learning | 0.8457 | deep learning | |
| selected regions for bias-corrected predicted signal profile DataType / deep learning | selected regions for predicted bias profile DataType / deep learning | 0.8418 | deep learning | |
| elements reference DataType / reference | enhancers reference FeatureType / regulatory element | 0.8409 | reference / regulatory_element | |
| reference variants FeatureType / variant | variant reference FeatureType / variant | 0.8399 | variant | |
| repeats reference DataType / reference | repeat elements annotation FeatureType / annotation | 0.8382 | reference / annotation | |
| representative DNase hypersensitivity sites DataType / peak set | consensus DNase hypersensitivity sites DataType / chromatin accessibility | 0.8353 | peak_set / chromatin_accessibility | |
| spike-in alignments DataType / alignment | spike-ins DataType / technical | 0.8353 | alignment / technical | |
| element gene interactions p-value FeatureType / element gene linkage | element gene interactions signal FeatureType / element gene linkage | 0.8323 | element gene linkage | |
| selected regions for predicted signal and sequence contribution scores DataType / deep learning | selected regions for predicted signal profile DataType / deep learning | 0.8288 | deep learning | |
| sparse gRNA count matrix DataType / crispr screen | sparse gene count matrix DataType / count matrix | 0.8280 | crispr_screen / count_matrix | |
| selected regions for bias-corrected predicted signal profile DataType / deep learning | selected regions for predicted signal profile DataType / deep learning | 0.8260 | deep learning | |
| transcriptome index DataType / reference | transcriptome reference DataType / reference | 0.8223 | reference | |
| bidirectional peaks DataType / peak set | unidirectional peaks DataType / peak set | 0.8222 | peak set | |
| exon quantifications DataType / quantification | gene quantifications DataType / quantification | 0.8198 | quantification | |
| genic regions quantifications DataType / quantification | transcribed region quantifications DataType / quantification | 0.8187 | quantification | |
| DHS peaks DataType / chromatin accessibility | open chromatin regions FeatureType / chromatin accessibility | 0.8150 | chromatin accessibility | |
| peptide quantifications DataType / quantification | protein expression quantifications DataType / quantification | 0.8111 | quantification | |
| optimal IDR thresholded peaks DataType / peak set | representative IDR thresholded peaks DataType / peak set | 0.8105 | peak set | |
| enhancers reference FeatureType / regulatory element | promoters reference FeatureType / regulatory element | 0.8103 | regulatory element | |
| elements reference DataType / reference | repeats reference DataType / reference | 0.8082 | reference | |
| methylation state at CHH FeatureType / dna methylation | methylation state at CpG FeatureType / dna methylation | 0.8071 | dna methylation | |
| gene quantifications DataType / quantification | transcript quantifications DataType / quantification | 0.8042 | quantification | |
| sparse gene count matrix DataType / count matrix | sparse peak count matrix DataType / count matrix | 0.8038 | count matrix | |
| sequence motifs FeatureType / sequence motif | sequence motifs instances FeatureType / sequence motif | 0.8030 | sequence motif | |
| candidate enhancers FeatureType / regulatory element | predicted enhancers FeatureType / regulatory element | 0.8010 | regulatory element |