Comments (2)
gianfilippo
commented on June 12, 2024
The .ntChange.Classifier.RData seems to be produced by the call to somaticseq_parallel.py, while the ada.Classifier.RData comes from a direct call to the R script, following the manual. Are the models different at the end ?
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litaifang
commented on June 12, 2024
The ada_model_builder_ntChange.R script will create extra features for nucleotide changes, i.e., G>C, G>T, etc. That's the one called by somaticseq_parallel.py.
The model name is now .ada.Classifier.RData, because I recently incorporated xgboost so this name makes sense. Older version will have .ntChange.Classifier.RData to reflect that the model has nucleotide change features in it.
from somaticseq.
Related Issues (20)
- Special setting for b37? HOT 14
- Question about simulating somatic mutations HOT 7
- Pretrained Classifier HOT 3
- Docker issue with latest version HOT 1
- SEQC2: Some high confidence SNVs and INDELs in VCF are outside of regions defined by High-Confidence_Regions_v1.2.bed HOT 2
- Somaticseq makeSomaticScripts.py running and output issues HOT 8
- Slow RNA variant calling HOT 8
- Question for the paper on establishing the reference call set HOT 3
- Where are the 10x Genomics single-cell copy number variation (CNV) analysis results? HOT 7
- Ground Truths required for training HOT 1
- somaticseq failing for same command it had previously successfully run HOT 11
- Applying internal filters to outputs before running SomaticSeq HOT 1
- Dockerized alignment workflow does not work with multiple input files HOT 5
- Error when running makeSomaticScripts with multiple threads HOT 3
- Output allele of the normal sample HOT 2
- UnboundLocalError: cannot access local variable 'normal_name' where it is not associated with a value HOT 10
- how to obtain all variants where the "FILTER" column is not labeled as "PASS" HOT 1
- Are multi-nucleotide and complex variants ignored? HOT 2
- Error when running FFPE training data from SEQ2C HOT 5
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