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src/task_metadata.json

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+[
+  {
+    "task_id": "chipseq-peak-calling",
+    "name": "ChIP-seq Peak Calling: TAL1 Binding Site Comparison",
+    "description": "This task analyzes ChIP-seq data for the TAL1 transcription factor in two mouse hematopoietic cell types: G1E erythroid progenitor cells and megakaryocytes. Eight single-end FASTQ files (4 TAL1 ChIP samples + 4 input controls, all subset to chromosome 19) are provided along with a mm10 chr19 reference genome. The data is from Wu et al. 2014 (GEO GSE51338).",
+    "task_prompt": "Identify TAL1 transcription factor binding sites in G1E cells and Megakaryocytes from ChIP-seq data, then compare peaks between cell types to find shared and cell-type-specific binding. Steps: (1) trim/QC reads, (2) align to the mm10 chr19 reference genome in the reference/ directory, (3) call peaks for each cell type using ChIP vs input control, (4) intersect peak sets to identify shared and unique peaks. The output should be a CSV file with the following columns: 'chrom','start','end','name','score','strand','signal_value','pvalue','qvalue','peak','cell_type','status'.\n<example>chrom,start,end,name,score,strand,signal_value,pvalue,qvalue,peak,cell_type,status\nchr19,5798729,5798998,G1E_TAL1_peak_12,885,.,17.5082,91.8514,88.5255,277,G1E,shared</example>",
+    "download_urls": {
+      "data": [{"filename": "data.tar.gz", "url": "TO_BE_SET"}],
+      "reference_data": [{"filename": "reference.tar.gz", "url": "TO_BE_SET"}],
+      "results": [{"filename": "results.tar.gz", "url": "TO_BE_SET"}]
+    }
+  },
+  {
+    "task_id": "bacterial-assembly",
+    "name": "Bacterial Genome Assembly and Annotation: MRSA Characterization",
+    "description": "This task analyzes a methicillin-resistant Staphylococcus aureus (MRSA) clinical isolate from paired-end Illumina MiSeq sequencing. The goal is to assemble the genome de novo and produce a comprehensive characterization report covering assembly quality, gene content, sequence typing, and antimicrobial resistance. The data is from Hikichi et al. 2019 (BioSample SAMD00180470), estimated genome size ~2.9 Mbp.",
+    "task_prompt": "Assemble an MRSA bacterial genome from paired-end Illumina reads and produce a comprehensive characterization report. The report should include: assembly statistics (total length, contigs, N50, GC content), assembly completeness, sequence typing, predicted gene counts (CDS, tRNA, rRNA), and the number of antimicrobial resistance genes detected. The output should be a CSV file with the following columns: 'metric','value'.\n<example>metric,value\ntotal_length,2911349\nnum_contigs,44\nn50,276459\ngc_content,32.77\nlargest_contig,589438\ncompleteness,C:100.0%[S:100.0%,D:0.0%],F:0.0%,M:0.0%,n:124\nmlst_scheme,saureus\nmlst_sequence_type,764\ncds_count,2717\ntrna_count,57\nrrna_count,9</example>",
+    "download_urls": {
+      "data": [{"filename": "data.tar.gz", "url": "TO_BE_SET"}],
+      "reference_data": [],
+      "results": [{"filename": "results.tar.gz", "url": "TO_BE_SET"}]
+    }
+  },
+  {
+    "task_id": "mobile-elements",
+    "name": "Bacterial Mobile Genetic Element Characterization: MRSA Genomic Islands and AMR",
+    "description": "This task analyzes a methicillin-resistant Staphylococcus aureus (MRSA) clinical isolate from paired-end Illumina MiSeq sequencing. The goal is to assemble the genome and perform comprehensive characterization of mobile genetic elements, antimicrobial resistance determinants, and virulence factors. The report should cover assembly quality, gene content, insertion sequence elements, AMR genes identified by multiple methods, and virulence factors. The data is from Hikichi et al. 2019 (BioSample SAMD00180470), S. aureus estimated genome ~2.9 Mbp.",
+    "task_prompt": "Assemble an MRSA bacterial genome from paired-end Illumina reads and produce a comprehensive genomic characterization report. The report should cover: assembly statistics, assembly completeness, predicted gene counts, insertion sequence (IS) elements, integrons, antimicrobial resistance genes identified by both protein-homology and nucleotide-based methods with cross-validation, virulence factors, plasmid contigs, and replicon types. The output should be a CSV file with the following columns: 'metric','value'.\n<example>metric,value\ntotal_length,2911349\nnum_contigs,44\nn50,276459\ngc_content,32.77\nlargest_contig,589438\ncompleteness,C:100.0%[S:100.0%,D:0.0%],F:0.0%,M:0.0%,n:124\ncds_count,2717\ntrna_count,57\nrrna_count,9\nis_elements_found,0\nintegrons_found,0\namr_genes_protein_method,45\namr_genes_nucleotide_method,21\namr_genes_confirmed_both,2\nvirulence_factors,83\nplasmid_contigs,0\nreplicon_types,0</example>",
+    "download_urls": {
+      "data": [{"filename": "data.tar.gz", "url": "TO_BE_SET"}],
+      "reference_data": [],
+      "results": [{"filename": "results.tar.gz", "url": "TO_BE_SET"}]
+    }
+  }
+]