DSGym/DSGym-Tasks huggingface dataset:
Context: Domain: single-cell RNA-seq; Dataset: Multi-tissue GI tract scRNA-seq enabling gene expression correlation analysis. Dataset allows examination of conserved expression patterns across anatomical regions.

Question: For TA cells, calculate Pearson correlation of mean gene expression between each tissue pair. Only consider genes with mean expression > 1.0 in all three tissues. Calculate all three pairwise correlations. What is the mean of these three correlation coefficients?
Answer guideline: Answer must be a number rounded to 3 decimal places.
Answer: 0.976
Source paper: Single-cell transcriptome analysis reveals differential nutrient absorption functions in human intestine
Context: Domain: single-cell RNA-seq; Dataset: Colon scRNA-seq with donor annotations. Dataset enables analysis of donor-to-donor variability in gene expression using variance decomposition.

Question: For Enterocyte cells in Colon, calculate donor variability for each gene. Compute ratio of between-donor variance to within-donor variance. Among genes with mean expression > 2.0, what gene symbol has the highest variability ratio?
Answer guideline: Answer must be a single gene symbol, case-sensitive.
Answer: MT1G
Source paper: Single-cell transcriptome analysis reveals differential nutrient absorption functions in human intestine
Context: Domain: single-cell RNA-seq; Dataset: Multi-tissue GI tract scRNA-seq enabling regional specificity analysis. Dataset allows identification of tissue-specific gene expression patterns using coefficient of variation.

Question: Calculate regional specificity score for each gene across all cell types. For each tissue, score = mean_expression_tissue / mean_of_all_tissues. Calculate coefficient of variation of these three scores. Among genes with total mean expression > 0.5, what are the top 5 gene symbols with highest CV?
Answer guideline: Answer must be a list of 5 gene symbols, for example: ['GENE1', 'GENE2', 'GENE3', 'GENE4', 'GENE5'], case-sensitive.
Answer: PRAC1, CYP3A4, RBP2, ALDOB, DPEP1
Source paper: Single-cell transcriptome analysis reveals differential nutrient absorption functions in human intestine