Bacterial Gene Screening PCR Leaping Artifact Filter with PySAM
PCR leaping artifacts cause chimeric sequence reads that distort bacterial gene screening. You will build a Python processing module using PySAM and Biopython to detect template-switching chimeras in high-throughput sequencing BAM files, removing false positive resistance gene calls with 98% specificity.
What you are building
The core problem, expected build, and operating context for this challenge.
Develop a BAM alignment artifact filtration tool using PySAM to eliminate PCR leaping chimeras in bacterial screening.
How work is evaluated
Evaluates chimera filtering precision and specificity on benchmark BAM alignment files.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
artifact_flag_check
Ensure obvious leaping chimera read is correctly flagged
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
specificity
Specificity of filtering technical PCR artifacts • target: 0.98 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Analyze BAM alignment CIGAR strings and supplementary alignments using PySAM
Identify PCR template-switching leap patterns across homologous bacterial gene segments
Filter artifactual chimeric reads from downstream antimicrobial resistance gene counts
Reference links and supporting material
Synthetic BAM dataset of 10,000 bacterial gene reads containing PCR leaping artifact benchmarks.
Challenge setup
Evaluates chimera filtering precision and specificity on benchmark BAM alignment files.
Challenge input
JSON object with read_name, cigar_string, and soft_clip_length
PySAM
Required Python interface for SAM/BAM parsing.
Evaluated output
JSON object with is_artifact boolean and chimera_score float
- Ensure obvious leaping chimera read is correctly flagged
- Specificity of filtering technical PCR artifacts • target: 0.98 • range: 0-1
- Benchmark: BAMFilter-Bench
- Specificity target: 0.98
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
View technical recipe
Configured tools
- Google Gemini · Required
- OmegaConf · Optional
- Claude 4 Sonnet · Optional
Evaluation contract
- artifact_flag_check · Weight 1
- specificity · Weight 1
Metrics
- specificity · Target 0.98
Benchmarks
- BAMFilter-Bench
- biotech
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON object with read_name, cigar_string, and soft_clip_length
Output: JSON object with is_artifact boolean and chimera_score float
Execution harness: Python
Evaluation tools
- PySAM · Sequence Alignment Toolkit
Recipe freeze marker
No recipe freeze time is recorded.