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14810 skills availablebio-metagenomics-abundance
Reference examples tested with: Bracken 2.9+, Kraken2 2.1+, MetaPhlAn 4.1+, pandas 2.2+ Before using code patterns, veri...
bio-metabolomics-xcms-preprocessing
Reference examples tested with: MSnbase 2.28+, scanpy 1.10+, xcms 4.0+ Before using code patterns, verify installed vers...
bio-metabolomics-targeted-analysis
Reference examples tested with: ggplot2 3.5+, matplotlib 3.8+, numpy 1.26+, pandas 2.2+, scikit-learn 1.4+, scipy 1.12+,...
bio-metabolomics-statistical-analysis
Reference examples tested with: R stats (base), ggplot2 3.5+ Before using code patterns, verify installed versions match...
bio-metabolomics-normalization-qc
Reference examples tested with: xcms 4.0+ Before using code patterns, verify installed versions match. If versions diffe...
bio-metabolomics-lipidomics
Reference examples tested with: ggplot2 3.5+, numpy 1.26+, pandas 2.2+, scanpy 1.10+, xcms 4.0+ Before using code patter...
bio-machine-learning-survival-analysis
from lifelines import KaplanMeierFitter import matplotlib.pyplot as plt kmf = KaplanMeierFitter() kmf.fit(T, eventobserv...
bio-machine-learning-prediction-explanation
import shap from sklearn.ensemble import RandomForestClassifier model = RandomForestClassifier(nestimators=100, randomst...
bio-machine-learning-omics-classifiers
from sklearn.modelselection import traintestsplit from sklearn.preprocessing import StandardScaler from sklearn.pipeline...
bio-machine-learning-biomarker-discovery
Identifies all features that are significantly better than random (shadow features). from boruta import BorutaPy from sk...
bio-machine-learning-atlas-mapping
import scvi import scanpy as sc adataref = sc.readh5ad('reference.h5ad') scvi.model.SCVI.setupanndata(adataref, layer='c...
bio-longread-structural-variants
Reference examples tested with: bcftools 1.19+ Before using code patterns, verify installed versions match. If versions ...
bio-longread-qc
Reference examples tested with: BioPython 1.83+, numpy 1.26+ Before using code patterns, verify installed versions match...
bio-longitudinal-monitoring
Reference examples tested with: matplotlib 3.8+, numpy 1.26+, pandas 2.2+, scipy 1.12+ Before using code patterns, verif...
bio-long-read-sequencing-nanopore-methylation
Reference examples tested with: methylKit 1.28+, minimap2 2.26+, samtools 1.19+ Before using code patterns, verify insta...
bio-long-read-sequencing-isoseq-analysis
Reference examples tested with: minimap2 2.26+, pandas 2.2+, pysam 0.22+, samtools 1.19+ Before using code patterns, ver...
bio-immunoinformatics-tcr-epitope-binding
Reference examples tested with: MiXCR 4.6+, numpy 1.26+, pandas 2.2+, scikit-learn 1.4+, scipy 1.12+ Before using code p...
bio-immunoinformatics-neoantigen-prediction
Reference examples tested with: Ensembl VEP 111+, MHCflurry 2.1+, pVACtools 4.1+, pandas 2.2+ Before using code patterns...
bio-immunoinformatics-mhc-binding-prediction
Reference examples tested with: MHCflurry 2.1+, pandas 2.2+ Before using code patterns, verify installed versions match....
bio-immunoinformatics-immunogenicity-scoring
Reference examples tested with: MHCflurry 2.1+, numpy 1.26+, pandas 2.2+ Before using code patterns, verify installed ve...
bio-imaging-mass-cytometry-quality-metrics
Reference examples tested with: matplotlib 3.8+, numpy 1.26+, pandas 2.2+, scipy 1.12+ Before using code patterns, verif...
bio-imaging-mass-cytometry-data-preprocessing
Reference examples tested with: anndata 0.10+, numpy 1.26+, pandas 2.2+, scanpy 1.10+, scipy 1.12+, steinbock 0.16+ Befo...
bio-imaging-mass-cytometry-cell-segmentation
Reference examples tested with: Cellpose 3.0+, anndata 0.10+, matplotlib 3.8+, numpy 1.26+, pandas 2.2+, scanpy 1.10+, s...
bio-hi-c-analysis-tad-detection
Reference examples tested with: cooler 0.9+, cooltools 0.6+, matplotlib 3.8+, numpy 1.26+, pandas 2.2+ Before using code...