GDPx4

GDPx4 Functional Genomics Dataset: DRUG-seq chemical perturbation in engineered HEK293 cells.

Experimental Design

Experiments were performed in a 384-well format assay using engineered HEK293 cells. 406 library compounds were tested at 6 concentrations (0.03, 0.1, 0.3, 1, 3, 10 µM) using two replicates for each concentration. DMSO was used as an inert control added at matched volumes. Brefeldin A, Rigosertib, and Trichostatin A were used as transcriptional positive controls at 3 concentrations (0.1, 1, 10 µM). Staurosporine was used as a cell death control at a single concentration (10 µM). This generated a total of 14 384-well plates that were harvested for downstream transcriptomic analysis after 24 hours of exposure.

Metadata - metadata.csv

File with sample-level annotations and sample-level quality control metrics (5,264 samples).

Column	Type	Description
sequenced_id	int	Unique ID of the sample (well) prepared for sequencing
container_id	int	Unique ID of the perturbation or sequencing library plate
column_id	int	Column position in the plate
row_id	int	Row position in the plate
is_edge	boolean	Whether a sample is in a well touching the border of the plate
compound	string	Name of compound used to perturb cells
compound_clean	string	Normalized version of compound name
compound_concentration	float	Compound concentration
compound_concentration_unit	string	Compound concentration unit of measure
cell_line	string	Cell line name
timepoint	int	Time between perturbation and lysis in hours
condition	string	Combination of compound_clean and concentration, to help group replicates
percent_volume_dmso	float	Concentration of DMSO in perturbation sample, in percent volume. Compounds are dispensed dissolved in DMSO.
sample_type	string	Kind of sample, either "library" or the name of a control
is_neg_control	boolean	Whether a sample is considered a negative control
is_pos_control	boolean	Whether a sample is considered a positive control
seeded_cell_count	int	Count of cells seeded prior to perturbation
total_sequenced_reads	int	Total reads attributed to this sample
total_umi_count	int	Total Unique Molecule Identifier (UMI) count
ngenes3	int	Count of genes with at least three UMIs
n_mapped	int	Count of UMIs mapped to annotated genes
percent_mapped	float	Percent of UMIs mapped to the reference, calculated by dividing n_mapped by total_umi_count
percent_rrna_removed	float	Percent of input reads attributed to rRNA and removed
percent_mitochondrial	float	Percent of UMIs attributed to mitochondrial RNA
unassigned_multimapping	int	Number of reads that could not be uniquely assigned to a single gene due to mapping to multiple genes
unassigned_nofeatures	int	Number of reads that could not be assigned to any gene
percent_duplicated	float	Percentage of reads that are UMI duplicates

Gene Counts - gene_counts.parquet

Gene-level UMI counts for each sample were obtained following rRNA removal (bbduk), STAR alignment (STAR) against hg38, deduplication using umi-tools, and counting with featureCounts. Column headers represent sequenced sample IDs (sequenced_id in metadata table) and rows are Ensembl gene IDs. The matrix contains 78,778 genes across 5,264 samples.

Gene Metadata - gene_metadata.csv

Lookup table mapping Ensembl gene IDs to gene symbols and biotypes (78,778 genes).

Column	Type	Description
gene_id	string	Ensembl gene ID (version stripped)
gene_symbol	string	HGNC gene symbol
gene_type	string	Ensembl gene biotype (e.g., protein_coding, lncRNA, pseudogene)
ensembl_gene_version	int	Ensembl gene annotation version number

Compound Library - compound_library.csv

Additional information about the compounds tested (411 compounds: 406 library + 5 controls).

Column	Type	Description
Drug	string	Name of the compound as it appears in the experiment metadata
Type	string	"positive control", "negative control", or "library"
Category	string	Broad functional or pharmacological category of the compound
Function	string	Description of the compound's mechanism of action
Target	string	Molecular target(s) of the compound, when known
InChI	string	IUPAC International Chemical Identifier for the compound

Differential Expression - differential_expression.parquet

Differentially expressed genes were identified using DESeq2, comparing each treatment (compound at a specific concentration) to DMSO controls on the same plate. Log2 fold change shrinkage was applied using the ashr method. Each compound was analyzed independently per plate. The table contains 29,844,800 rows across 410 compounds (406 library + 4 controls).

Column	Type	Description
cell_line	string	Cell line name
gene_id	string	Ensembl gene ID
gene_symbol	string	HGNC gene symbol
compound	string	Compound name
container_id	string	Plate ID. Each compound is analyzed per-plate against plate-matched DMSO controls.
concentration	float	Compound concentration in µM
log2FoldChange	float	Shrunken log2 fold change (ashr method) comparing compound-treated samples to plate-matched DMSO controls, computed by DESeq2
log2FoldChange_raw	float	Unshrunk log2 fold change from DESeq2
pvalue	float	Wald test p-value for differential expression at this concentration vs DMSO
padj	float	Benjamini-Hochberg adjusted p-value
baseMean	float	Mean of normalized counts across compound-treated and DMSO control samples, computed by DESeq2