| --- |
| license: mit |
| language: |
| - en |
| tags: |
| - biology |
| - genomics |
| - yeast |
| - transcription-factors |
| - callingcards |
| - transposon |
| - binding |
| - gene-expression |
| pretty_name: "Calling Cards Transcription Factor Binding Dataset" |
|
|
| experimental_conditions: |
| temperature_celsius: room |
| media: |
| name: synthetic_complete_minus_ura_his_leu |
| carbon_source: |
| - compound: D-galactose |
| concentration_percent: 2 |
| nitrogen_source: |
| - compound: amino_acid_dropout_mix |
| concentration_percent: unspecified |
| specifications: |
| - minus_ura |
| - minus_his |
| - minus_leu |
|
|
| citation: Mateusiak, C, Erdenebaatar, Z, Jia, E, Plaggenberg, JN, Wang, Y, Shively, C, Liao, G, Mitra, RD, Brent, MR. 2026. Functional synergy partially explains why most transcription factor binding is non-functional. bioRxiv 2026. |
| doi: https://doi.org/10.64898/2026.01.19.700460 |
|
|
| features: |
| - applies_to: |
| - genome_map_meta |
| - annotated_feature_meta |
| - annotated_feature_combined_meta |
| fields: |
| - name: condition |
| dtype: |
| class_label: |
| names: [ |
| "standard", "rapa", "starvation", "glu_1_gal_1", |
| "del_MET28", "glu_1_gal_2", "del_FKH2", "del_TYE7" |
| ] |
| description: >- |
| Experimental condition of the sample, including standard growth, rapamycin treatment, |
| nutrient starvation, mixed carbon source conditions, and gene deletion strains |
| role: experimental_condition |
| definitions: |
| standard: |
| media: |
| name: synthetic_complete |
| carbon_source: |
| - compound: D-glucose |
| concentration_percent: 2 |
| rapa: |
| perturbation_method: |
| type: chemical_treatment |
| compound: rapamycin |
| description: Rapamycin treatment to inhibit TORC1 signaling |
| starvation: |
| description: "Nutrient starvation condition - specific media composition not defined in source" |
| glu_1_gal_1: |
| media: |
| carbon_source: |
| - compound: D-glucose |
| concentration_percent: 1 |
| - compound: D-galactose |
| concentration_percent: 1 |
| glu_1_gal_2: |
| media: |
| carbon_source: |
| - compound: D-glucose |
| concentration_percent: 1 |
| - compound: D-galactose |
| concentration_percent: 2 |
| del_MET28: |
| genotype: |
| deletions: |
| - gene: MET28 |
| description: MET28 deletion strain |
| del_FKH2: |
| genotype: |
| deletions: |
| - gene: FKH2 |
| description: FKH2 deletion strain |
| del_TYE7: |
| genotype: |
| deletions: |
| - gene: TYE7 |
| description: TYE7 deletion strain |
|
|
| - applies_to: |
| - annotated_feature_reprocess_intergenic |
| - annotated_feature_reprocess_intergenic_analysis |
| fields: |
| - name: ir_name |
| dtype: string |
| description: >- |
| Unique identifier of the intergenic region. See |
| yeast_genome_resources/intergenic_regions_metadata_5_1.csv for details on |
| the region (location, etc). Note that these intergenic regions are defined |
| as the region between the end of one ORF and the start of the next, and |
| are named according to the locus tags of the flanking ORFs (e.g., |
| YAL001C-YAL002W). A intergenic region is assigned to a promoter only when |
| the 5' end is continuous with the region. |
| |
| - applies_to: |
| - annotated_feature |
| - annotated_feature_meta |
| - genome_map |
| - genome_map_meta |
| - annotated_feature_reprocess_yiming |
| - annotated_feature_reprocess_mindel |
| - annotated_feature_reprocess_start_codon_500 |
| - annotated_feature_reprocess_intergenic |
| fields: |
| - name: batch |
| dtype: string |
| description: Experimental batch identifier for controlling batch effects (partition key) |
| role: experimental_condition |
|
|
| - applies_to: |
| - annotated_feature_meta |
| - annotated_feature_combined_meta |
| - genome_map_meta |
| - 2026_analysis_set |
| - annotated_feature_reprocess_mindel_analysis |
| - annotated_feature_reprocess_start_codon_500bp_analysis |
| - annotated_feature_reprocess_intergenic_analysis |
| fields: |
| - name: regulator_locus_tag |
| dtype: string |
| description: Systematic gene identifier for the transcription factor |
| role: regulator_identifier |
| - name: regulator_symbol |
| dtype: string |
| description: Standard gene symbol for the transcription factor |
| role: regulator_identifier |
|
|
| - applies_to: |
| - annotated_feature |
| - annotated_feature_combined |
| - 2026_analysis_set |
| - annotated_feature_reprocess_yiming |
| - annotated_feature_reprocess_mindel |
| - annotated_feature_reprocess_mindel_analysis |
| - annotated_feature_reprocess_start_codon_500 |
| - annotated_feature_reprocess_start_codon_500bp_analysis |
| - annotated_feature_reprocess_intergenic |
| - annotated_feature_reprocess_intergenic_analysis |
| fields: |
| - name: target_locus_tag |
| dtype: string |
| description: Systematic gene identifier for the target gene |
| role: target_identifier |
| - name: target_symbol |
| dtype: string |
| description: Standard gene symbol for the target gene |
| role: target_identifier |
|
|
| - applies_to: |
| - annotated_feature |
| - annotated_feature_combined |
| - 2026_analysis_set |
| - annotated_feature_reprocess_yiming |
| - annotated_feature_reprocess_mindel |
| - annotated_feature_reprocess_mindel_analysis |
| - annotated_feature_reprocess_start_codon_500 |
| - annotated_feature_reprocess_start_codon_500bp_analysis |
| - annotated_feature_reprocess_intergenic |
| - annotated_feature_reprocess_intergenic_analysis |
| fields: |
| - name: experiment_hops |
| dtype: float64 |
| description: Number of transposon insertion events (hops) at target locus in the experimental sample |
| role: quantitative_measure |
| - name: background_hops |
| dtype: float64 |
| description: Number of transposon insertion events (hops) at target locus in the background control |
| role: quantitative_measure |
| - name: callingcards_enrichment |
| dtype: float64 |
| description: Enrichment score calculated as ratio of normalized experimental to background hops |
| role: quantitative_measure |
| - name: poisson_pval |
| dtype: float64 |
| description: P-value from Poisson test for statistical significance of binding enrichment |
| role: quantitative_measure |
|
|
| - applies_to: |
| - annotated_feature |
| - annotated_feature_combined |
| - 2026_analysis_set |
| fields: |
| - name: background_total_hops |
| dtype: float64 |
| description: Total number of background hops across all loci in the control sample |
| role: quantitative_measure |
| - name: experiment_total_hops |
| dtype: float64 |
| description: Total number of experimental hops across all loci in the experimental sample |
| role: quantitative_measure |
|
|
| - applies_to: |
| - annotated_feature_reprocess_yiming |
| - annotated_feature_reprocess_mindel |
| - annotated_feature_reprocess_mindel_analysis |
| - annotated_feature_reprocess_start_codon_500 |
| - annotated_feature_reprocess_start_codon_500bp_analysis |
| - annotated_feature_reprocess_intergenic |
| - annotated_feature_reprocess_intergenic_analysis |
| fields: |
| - name: total_background_hops |
| dtype: float64 |
| description: Total number of background hops across all loci in the control sample |
| role: quantitative_measure |
| - name: total_experiment_hops |
| dtype: float64 |
| description: Total number of experimental hops across all loci in the experimental sample genomic (not mito) chromosomes |
| role: quantitative_measure |
| - name: log_poisson_pval |
| dtype: float64 |
| description: Log-transformed Poisson p-value. This has greater numeric resolution for significant loci |
| role: quantitative_measure |
| - name: poisson_qval |
| dtype: float64 |
| description: FDR-adjusted q-value from Poisson test (multiple testing correction) |
| role: quantitative_measure |
| - name: hypergeometric_pval |
| dtype: float64 |
| description: P-value from hypergeometric test for statistical significance of binding enrichment |
| role: quantitative_measure |
| - name: log_hypergeometric_pval |
| dtype: float64 |
| description: Log-transformed hypergeometric p-value |
| role: quantitative_measure |
| - name: hypergeometric_qval |
| dtype: float64 |
| description: FDR-adjusted q-value from hypergeometric test (multiple testing correction) |
| role: quantitative_measure |
| |
| configs: |
| - config_name: annotated_feature |
| description: >- |
| This is data that was originally processed through |
| https://github.com/cmatKhan/callingCardsTools/ and stored (including some more |
| processing) in https://github.com/cmatKhan/yeastregulatorydb. It is the data that |
| was used for the QC and filtering decisions in the 2026 modeling paper. In general, |
| unless you are trying to exactly replicate the 2026 modeling paper, you should use |
| the 2026_analysis_set for analysis that uses the published results. Or, to use data |
| that can be reproduced directly from the genome_map data, |
| `annotated_feature_reprocess_*`. The suffix indicates which promoter set was used |
| to generate the results from the genome_map data. |
| dataset_type: annotated_features |
| genome_resources: |
| region_sets: |
| Kang: |
| path: https://huggingface.co/datasets/BrentLab/yeast_genome_resources/blob/main/yiming_promoters.bed |
| join_column: target_locus_tag |
| data_files: |
| - split: train |
| path: annotated_feature/*/*.parquet |
| partitioning: |
| enabled: true |
| partition_by: ["batch"] |
| path_template: "annotated_feature/batch={batch}/*.parquet" |
| dataset_info: |
| features: |
| - name: id |
| dtype: int64 |
| description: Unique identifier for each binding measurement |
| - name: hypergeometric_pval |
| dtype: float64 |
| description: P-value from hypergeometric test for statistical significance of binding enrichment |
| role: quantitative_measure |
|
|
| - config_name: annotated_feature_meta |
| description: Metadata for the annotated_features dataset. |
| dataset_type: metadata |
| applies_to: ["annotated_feature"] |
| data_files: |
| - split: train |
| path: annotated_feature_meta.parquet |
| dataset_info: |
| features: |
| - name: id |
| dtype: float64 |
| description: Unique identifier for the metadata record |
| role: sample_id |
| - name: genome_map_id |
| dtype: float64 |
| description: >- |
| Genome map identifier linking to the genome_map and genome_map_meta dataset |
| role: secondary_sample_id |
| - name: pss_id |
| dtype: string |
| description: >- |
| Identifier from a defunct database (promoter set sig id) |
| role: secondary_sample_id |
| - name: binding_id |
| dtype: string |
| description: >- |
| Identifier from a defunct database (binding id) |
| role: secondary_sample_id |
| - name: data_usable |
| dtype: string |
| description: Indicator of whether the data is suitable for analysis |
| - name: analysis_set |
| dtype: bool |
| description: >- |
| TRUE if this record is to be used for analysis. FALSE otherwise. |
| This was determined in 2025. Replicates needed `>=`3k hops and |
| DTO `<=` 0.01 in either kemmeren or hackett |
| |
| - config_name: annotated_feature_combined |
| description: >- |
| For the 2026 modeling paper, we labeled replicates passing if it has `>=`3k hops |
| and DTO `<=` 0.01 in either kemmeren or hackett. For a TF with more than 1 passing |
| replicate, a combined sample is created by summing the hops across the passing |
| replicates. This is the data that is used for the 2026 modeling paper as predictors. |
| It is retained here for replication and transparency, but we do not recommend |
| using it for new analysis. Instead, to use the published results, use the |
| `2026_analysis_set` which includes the same combined samples, but also includes |
| the passing single replicates. Otherwise, the annotated_feature_reprocess_*_analysis |
| datasets are more directly reproducible from the genome_map data, using a specified |
| promoter set, and have combined samples using the same logic. |
| dataset_type: annotated_features |
| genome_resources: |
| region_sets: |
| Kang: |
| path: https://huggingface.co/datasets/BrentLab/yeast_genome_resources/blob/main/yiming_promoters.bed |
| join_column: target_locus_tag |
| data_files: |
| - split: train |
| path: annotated_feature_combined/*/*.parquet |
| dataset_info: |
| partitioning: |
| enabled: true |
| partition_by: ["genome_map_id_set"] |
| path_template: "annotated_feature_combined/genome_map_id_set={genome_map_id_set}/*.parquet" |
| features: |
| - name: genome_map_id_set |
| dtype: string |
| description: >- |
| Hyphen-delimited set of genome map IDs corresponding to the combined replicates for this |
| regulator (partition key) |
| - name: hypergeometric_pval |
| dtype: float64 |
| description: P-value from hypergeometric test for statistical significance of binding enrichment |
| role: quantitative_measure |
|
|
| - config_name: annotated_feature_combined_meta |
| description: Metadata for the annotated_feature_combined dataset. |
| dataset_type: metadata |
| applies_to: ["annotated_feature_combined"] |
| data_files: |
| - split: train |
| path: annotated_feature_combined_meta.parquet |
| dataset_info: |
| features: |
| - name: genome_map_id_set |
| dtype: string |
| description: Hyphen-delimited set of genome map IDs used as the partition key in annotated_feature_combined |
| - name: pss_id |
| dtype: string |
| description: Passing sample set identifier grouping replicates used in this combined analysis |
| - name: binding_id |
| dtype: string |
| description: Unique identifier for this combined binding measurement record |
| - name: analysis_set |
| dtype: bool |
| description: >- |
| For a TF with more than 1 passing replicate, a combined samples is created. |
| This is based on the QC done in 2025 for the modeling paper. See the |
| annotated_feature_meta for more details |
| |
| - config_name: 2026_analysis_set |
| description: >- |
| This dataset is the dataset that was used in the 2026 modeling paper. A passing |
| replicate has >=3000 hops had a dto empirical pvalue < 0.01 against either |
| kemmeren or hackett. Where a given regulator had multiple passing replicates, |
| those replicates were combined (see annotated_feature_combined). This dataset |
| should be used when you want to use the published results from the 2026 modeling |
| paper. If you want to use data that can be reproduced directly from the genome_map |
| data included in this repo, especially when called against different promoter |
| sets, then use the annotated_feature_reprocess_*_analysis datasets. |
| default: true |
| genome_resources: |
| region_sets: |
| Kang: |
| path: https://huggingface.co/datasets/BrentLab/yeast_genome_resources/blob/main/yiming_promoters.bed |
| join_column: target_locus_tag |
| dataset_type: annotated_features |
| metadata_fields: ["gm_id","regulator_locus_tag","regulator_symbol", "experiment_total_hops", "background_total_hops"] |
| data_files: |
| - split: train |
| path: 2026_analysis_set.parquet |
| dataset_info: |
| features: |
| - name: gm_id |
| dtype: string |
| description: >- |
| genome_map id. If the sample is a combination of multiple samples, then it is a |
| hyphen-delimited set of genome map IDs corresponding to the combined replicates for this |
| regulator. |
| |
| - config_name: genome_map |
| description: >- |
| This is the raw binding data (qbeds) from the nf-core/callingcards pipeline. It |
| can be processed into annotated_feature datasets suing the scripts/quantify_regions.R script. You can use your own promoter definitions (bed format) to do this, or those provided in BrentLab/yeast_genome_resources |
| dataset_type: genome_map |
| data_files: |
| - split: train |
| path: genome_map/*/*.parquet |
| dataset_info: |
| features: |
| - name: id |
| dtype: int64 |
| description: Unique identifier for each genomic interval |
| role: sample_id |
| - name: chr |
| dtype: string |
| description: Chromosome name (e.g., chrI, chrII, etc.) |
| - name: start |
| dtype: int64 |
| description: Start position of genomic interval |
| - name: end |
| dtype: int64 |
| description: End position of genomic interval |
| - name: depth |
| dtype: int64 |
| description: Number of transposon insertion events (read depth) in this genomic interval |
| - name: strand |
| dtype: string |
| description: Strand information (+ or -) for the genomic interval |
| partitioning: |
| enabled: true |
| partition_by: ["batch"] |
| path_template: "genome_map/batch={batch}/*.parquet" |
|
|
| - config_name: genome_map_meta |
| description: Metadata for genome map datasets including regulator information and experimental details |
| dataset_type: metadata |
| applies_to: ["genome_map", "annotated_feature_reprocess_yiming", "annotated_feature_reprocess_mindel", "annotated_feature_reprocess_start_codon_500", "annotated_feature_reprocess_intergenic"] |
| data_files: |
| - split: train |
| path: genome_map_meta.parquet |
| dataset_info: |
| features: |
| - name: id |
| dtype: float64 |
| description: Unique identifier for the metadata record |
| - name: binding_id |
| dtype: string |
| description: current django managed database identifier for the dataset to the 'binding' table |
| - name: replicate |
| dtype: float64 |
| description: Biological replicate number, within batch |
| - name: notes |
| dtype: string |
| description: Additional notes or comments about the experiment |
|
|
| - config_name: annotated_feature_reprocess_yiming |
| description: >- |
| Calling Cards annotated features reprocessed from the genome_map data |
| using scripts/quantify_regions.R against the yiming promoters in |
| BrentLab/yeast_genome_resources. This is very nearly exactly the same as |
| annotated_features, though there may be some differences around the boundaries |
| (intentional), and this includes higher numeric resolution in the most significant |
| promoters by using hte log argument in the poisson distribution function. |
| dataset_type: annotated_features |
| data_files: |
| - split: train |
| path: annotated_feature_reprocess_yiming/*/*.parquet |
| genome_resources: |
| region_sets: |
| Kang: |
| path: https://huggingface.co/datasets/BrentLab/yeast_genome_resources/blob/main/yiming_promoters.bed |
| join_column: target_locus_tag |
| partitioning: |
| enabled: true |
| partition_by: ["batch"] |
| path_template: "annotated_feature_reprocess_yiming/batch={batch}/*.parquet" |
| dataset_info: |
| features: |
| - name: id |
| dtype: int64 |
| description: >- |
| Genome map identifier linking to the genome_map and genome_map_meta dataset |
| |
| - config_name: annotated_feature_reprocess_mindel |
| description: >- |
| This is the genome_map data quantified against the Mindel promoters |
| (see BrentLab/yeast_genome_resources) using scripts/quantify_regions.R. |
| dataset_type: annotated_features |
| data_files: |
| - split: train |
| path: annotated_feature_reprocess_mindel/*/*.parquet |
| genome_resources: |
| region_sets: |
| Mindel: |
| path: https://huggingface.co/datasets/BrentLab/yeast_genome_resources/blob/main/mindel_promoters.csv.gz |
| join_column: target_locus_tag |
| partitioning: |
| enabled: true |
| partition_by: ["batch"] |
| path_template: "annotated_feature_reprocess_mindel/batch={batch}/*.parquet" |
| dataset_info: |
| features: |
| - name: genome_map_id |
| dtype: int64 |
| description: >- |
| Genome map identifier linking to the genome_map and genome_map_meta dataset |
| |
| - config_name: annotated_feature_reprocess_start_codon_500 |
| description: >- |
| This is the genome_map data quantified against the promoters defined |
| as 500bp upstream of the start codon for each gene |
| (see BrentLab/yeast_genome_resources) using |
| scripts/quantify_regions_500bp_intergenic.R. |
| dataset_type: annotated_features |
| data_files: |
| - split: train |
| path: annotated_feature_reprocess_start_codon_500/*/*.parquet |
| genome_resources: |
| region_sets: |
| start_codon_500bp: |
| path: https://huggingface.co/datasets/BrentLab/yeast_genome_resources/blob/main/start_codon_500bp_upstream_promoters.bed |
| join_column: target_locus_tag |
| partitioning: |
| enabled: true |
| partition_by: ["batch"] |
| path_template: "annotated_feature_reprocess_start_codon_500/batch={batch}/*.parquet" |
| dataset_info: |
| features: |
| - name: genome_map_id |
| dtype: int64 |
| description: >- |
| Genome map identifier linking to the genome_map and genome_map_meta dataset |
| |
| - config_name: annotated_feature_reprocess_intergenic |
| description: >- |
| This is the genome_map data quantified against the promoters defined |
| as the full intergenic region upstream of each gene (see |
| BrentLab/yeast_genome_resources) using scripts/quantify_regions_500bp_intergenic.R. |
| dataset_type: annotated_features |
| data_files: |
| - split: train |
| path: annotated_feature_reprocess_intergenic/*/*.parquet |
| genome_resources: |
| region_sets: |
| intergenic: |
| path: https://huggingface.co/datasets/BrentLab/yeast_genome_resources/blob/main/intergenic_regions_metadata_5_1.csv |
| join_column: ir_name |
| partitioning: |
| enabled: true |
| partition_by: ["batch"] |
| path_template: "annotated_feature_reprocess_intergenic/batch={batch}/*.parquet" |
| dataset_info: |
| features: |
| - name: genome_map_id |
| dtype: int64 |
| description: >- |
| Genome map identifier linking to the genome_map and genome_map_meta dataset |
| |
| - config_name: annotated_feature_reprocess_mindel_analysis |
| description: >- |
| This is the analysis set for the mindel data. It is generated using the same logic as the 2026_analysis_set, but using the results from the reprocessing against the mindel promoters. A passing replicate has >=3000 hops had a dto empirical pvalue < 0.01 against either kemmeren or hackett. Where a given regulator had multiple passing replicates, those replicates were combined (see annotated_feature_combined). This dataset should be used when you want to use data that can be reproduced directly from the genome_map data included in this repo, using the mindel promoter definitions. See scripts/quantify_regions.R as well as BrentLab/yeast_comparative_analysis/scripts for details of how this was conducted. |
| dataset_type: annotated_features |
| metadata_fields: ["combined_id","regulator_locus_tag","regulator_symbol", "total_experiment_hops", "total_background_hops"] |
| data_files: |
| - split: train |
| path: annotated_feature_reprocess_mindel_analysis.parquet |
| genome_resources: |
| region_sets: |
| Mindel: |
| path: https://huggingface.co/datasets/BrentLab/yeast_genome_resources/blob/main/mindel_promoters.csv.gz |
| join_column: target_locus_tag |
| dataset_info: |
| features: |
| - name: combined_id |
| dtype: string |
| description: >- |
| The genome map identifier of either a single passing, or multiple |
| passing replicates (hyphen-delimited) that were combined for the analysis set. replicates were combined if the DTO empirical |
| pvalue was <= 0.01 in either kemmeren or hackett. After combining, |
| if they have more than 3k hopes (single or combined), then they are |
| included in the analysis set. |
| role: sample_id |
|
|
| - config_name: annotated_feature_reprocess_start_codon_500bp_analysis |
| description: >- |
| This is the analysis set for promoters created with 500bp regions upstream |
| of the start codon. It uses the same passing replicates as the 2025_analysis_set. see R/scripts/quantify_regions_500bp_intergenic.R for details of how this was conducted. |
| dataset_type: annotated_features |
| metadata_fields: ["combined_id","regulator_locus_tag","regulator_symbol", "total_experiment_hops", "total_background_hops"] |
| data_files: |
| - split: train |
| path: annotated_feature_reprocess_start_codon_500bp_analysis.parquet |
| genome_resources: |
| region_sets: |
| start_codon_500bp: |
| path: https://huggingface.co/datasets/BrentLab/yeast_genome_resources/blob/main/start_codon_500bp_upstream_promoters.bed |
| join_column: target_locus_tag |
| dataset_info: |
| features: |
| - name: combined_id |
| dtype: string |
| description: >- |
| The genome map identifier of either a single passing, or multiple |
| passing replicates (hyphen-delimited) that were combined for the |
| 2026 analysis set. |
| role: sample_id |
|
|
| - config_name: annotated_feature_reprocess_intergenic_analysis |
| description: >- |
| This is the analysis set for promoters created with the full intergenic |
| region upstream of a given target. It uses the same passing replicates as the 2025_analysis_set. see R/scripts/quantify_regions_500bp_intergenic.R for details of how this was conducted. |
| dataset_type: annotated_features |
| metadata_fields: ["combined_id","regulator_locus_tag","regulator_symbol", "total_experiment_hops", "total_background_hops"] |
| data_files: |
| - split: train |
| path: annotated_feature_reprocess_intergenic_analysis.parquet |
| genome_resources: |
| region_sets: |
| intergenic: |
| path: https://huggingface.co/datasets/BrentLab/yeast_genome_resources/blob/main/intergenic_regions_metadata_5_1.csv |
| join_column: ir_name |
| dataset_info: |
| features: |
| - name: combined_id |
| dtype: string |
| description: >- |
| The genome map identifier of either a single passing, or multiple |
| passing replicates (hyphen-delimited) that were combined for the |
| 2026 analysis set. |
| role: sample_id |
| --- |
| # Calling Cards |
|
|
| This is data produced in both the Brent Lab and Mitra Lab at Washington University. |
|
|
| ## Accessing Data |
|
|
| The examples below require |
| [labretriever](https://github.com/cmatKhan/labretriever#installation) |
| (`pip install labretriever`) and/or the |
| [HuggingFace Hub client](https://huggingface.co/docs/huggingface_hub/installation) |
| (`pip install huggingface_hub`). |
|
|
| ### Accessing Data with labretriever |
|
|
| This repository is part of a collection configured as a unified database using |
| [labretriever.VirtualDB](https://cmatkhan.github.io/labretriever/virtual_db_configuration/). |
| Download the |
| [collection config](https://github.com/BrentLab/tfbpshiny/blob/main/tfbpshiny/brentlab_yeast_collection.yaml) |
| and use it to query the data directly in Python, or with an AI assistant using the |
| [labretriever plugin](https://cmatkhan.github.io/labretriever/mcp_server/#quick-install-claude-code-plugin). |
|
|
| ```python |
| from labretriever.virtual_db import VirtualDB |
| from labretriever.datacard import DataCard |
| |
| # Citation and metadata |
| card = DataCard("BrentLab/callingcards") |
| print([c.config_name for c in card.configs]) # list available datasets |
| |
| # print citation |
| info = card.info() |
| print(info["citation"]) |
| |
| # path to the downloaded brentlab_yeast_collection.yaml |
| vdb = VirtualDB("/path/to/brentlab_yeast_collection.yaml") |
| |
| print(vdb.get_dataset_description("callingcards")) |
| vdb.query("SELECT * FROM callingcards LIMIT 5") |
| ``` |
|
|
| ### Direct parquet access |
|
|
| The repository contains more data than what is exposed through the collection |
| configuration. Use `DataCard.info()` to inspect available files, then download |
| and query with DuckDB. |
|
|
| Some files are single parquet files (e.g. metadata files); others are |
| partitioned datasets. Download a metadata file first to identify relevant |
| partitions before fetching the full data. |
|
|
| Single parquet file example: |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| import duckdb |
| |
| repo_path = snapshot_download( |
| repo_id="BrentLab/callingcards", |
| repo_type="dataset", |
| allow_patterns="annotated_feature_meta.parquet", |
| ) |
| conn = duckdb.connect() |
| # returns a pandas DataFrame with the first 5 rows |
| conn.execute( |
| "SELECT * FROM read_parquet(?) LIMIT 5", |
| [f"{repo_path}/annotated_feature_meta.parquet"], |
| ).df() |
| ``` |
|
|
| Partitioned dataset example (the `annotated_feature` directory): |
|
|
| ```python |
| repo_path = snapshot_download( |
| repo_id="BrentLab/callingcards", |
| repo_type="dataset", |
| allow_patterns="annotated_feature/**", |
| ) |
| conn.execute( |
| "SELECT * FROM read_parquet(?) LIMIT 5", |
| [f"{repo_path}/annotated_feature/**/*.parquet"], |
| ).df() |
| ``` |
|
|
| ### Accessing using R |
|
|
| Clone the repository and read parquet files directly with |
| [arrow](https://arrow.apache.org/docs/r/): |
|
|
| ```r |
| # install.packages("arrow") |
| arrow::read_parquet("annotated_feature_meta.parquet") |
| ``` |
|
|
