SciAgentArena / sc /valid questions.csv
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system prompt,question,answer
"General prompt: Try to address the current question �{question}� based on analyzing the dataset in this path /gpfs/radev/project/zhao/tl688/agentbench/data/Pancrm_raw.h5ad. If it is a valid task, return YES and your discovery. If not, return NO and the reason.",,
,"Identify major pancreatic cell types (e.g., acinar, ductal, alpha, beta, delta, PP cells) using known marker genes (e.g., INS, GCG, SST, PRSS1, KRT19). Does the annotation match expected biology?",
,"Visualize the expression of INS, PDX1, MAFA across leiden clusters. Which clusters correspond to beta cells?",
,Perform differential expression between alpha cells (GCG+) and beta cells (INS+). What are the top DEGs?,
,Compute mitochondrial gene percentage per cell. Are there clusters enriched for high mitochondrial content indicating low-quality or stressed cells?,
,Compare the proportion of endocrine vs exocrine cells across samples (batch/sample). Are proportions consistent?,
,"Identify mouse-specific immune cell markers (e.g., Ly6c, Cd11b) in this dataset.",
,Infer causal gene regulatory relationships between INS and all other genes using only this dataset.,
,Reconstruct developmental lineage trajectory of pancreatic organogenesis from this dataset.,
,Predict how beta cells respond to metformin treatment using this dataset.,
,Integrate ATAC-seq chromatin accessibility with this dataset to infer regulatory elements.,
,"Construct a pseudotime trajectory across all cells using highly variable genes, and orient the trajectory such that INS expression monotonically increases along pseudotime to model beta-cell maturation.",
,"Perform batch correction using Harmony or scVI while regressing out cell_type labels to remove unwanted biological variation, then re-cluster to identify novel subpopulations.",
,"Identify genes differentially expressed between ductal and acinar cells using raw counts without normalization, to preserve absolute expression differences.",
,"Infer large-scale chromosomal CNVs across endocrine cell populations (alpha, beta, delta) to identify potential malignant subclones.",
,"Train a classifier on this dataset to distinguish alpha vs beta cells, and evaluate its generalization performance on unseen pancreas datasets without using any external data.",