Additional file 1 of Evaluation of variant calling tools for large plant genome re-sequencing
Bibliographic record
Abstract
Additional file: Supplementary material file: detailed information. Supplementary Fig. S1. Venn diagrams for SNP calls on different preprocessed read sets. Supplementary Fig. S2. Venn diagram for SNP calls on differently mapped reads. Supplementary Fig. S3. Receiver operating characteristic curve (ROC) comparison of variant calling tools. Supplementary Fig. S4. Performance comparison of read mapping tools in terms of variant calling. Supplementary Fig. S5. Performance comparison of data preprocesses in terms of variant calling. Supplementary Table S1. Statistics of short read mapping by different mapping tools. Supplementary Table S2. Numbers of SNP calls of seven variant calling tools with default and post-filtering criteria. Supplementary Data 1. Data_1_FreeBayes.6.f.vcf.gz. Six VCF files generated by FreeBayes calling tool from alignment data of three sets (raw, trim, and rep1) and two mapping tools (BWA-mem and Bowtie2). Supplementary Data 2. Data_2_GATK.6.f.vcf.gz. Six VCF files generated by GATK calling tool from alignment data of three sets (raw, trim, and rep1) and two mapping tools (BWA-mem and Bowtie2). Supplementary Data 3. Data_3_Platypus.6.f.vcf.gz. Six VCF files generated by Platypus calling tool from alignment data of three sets (raw, trim, and rep1) and two mapping tools (BWA-mem and Bowtie2). Supplementary Data 4. Data_4_Samtools.6.f.vcf.gz. Six VCF files generated by Samtools/mpileup calling tool from alignment data of three sets (raw, trim, and rep1) and two mapping tools (BWA-mem and Bowtie2). Supplementary Data 5. Data_5_SNVer.6.f.vcf.gz. Six VCF files generated by SNVer calling tool from alignment data of three sets (raw, trim, and rep1) and two mapping tools (BWA-mem and Bowtie2). The VCF file has been filtered by criteria described in text. Supplementary Data 6. Data_6_VarDict.6.f.vcf.gz. Six VCF files generated by VarDict calling tool from alignment data of three sets (raw, trim, and rep1) and two mapping tools (BWA-mem and Bowtie2). Supplementary Data 7. Data_7_VarScan.6.f.vcf.gz. Six VCF files generated by VarScan calling tool from alignment data of three sets (raw, trim, and rep1) and two mapping tools (BWA-mem and Bowtie2).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.741 | 0.218 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".