Pinned Repositories
SigProfilerExtractor
SigProfilerExtractor allows de novo extraction of mutational signatures from data generated in a matrix format. The tool identifies the number of operative mutational signatures, their activities in each sample, and the probability for each signature to cause a specific mutation type in a cancer sample. The tool makes use of SigProfilerMatrixGenerator and SigProfilerPlotting.
SigProfilerMatrixGenerator
SigProfilerMatrixGenerator creates mutational matrices for all types of somatic mutations. It allows downsizing the generated mutations only to parts for the genome (e.g., exome or a custom BED file). The tool seamlessly integrates with other SigProfiler tools.
nextflow_modules
Nextflow modules from the lab
tumourevo
Analysis pipleine to model tumour clonal evolution from WGS data (driver annotation, quality control of copy number calls, subclonal and mutational signature deconvolution)
SparseSignatures
Extracting mutational signatures via LASSO. The manuscript of the method is published on PLOS Computational Biology and available at: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009119
CLLproject
CN-aware-DGE
devilCaseStudies
Case studies of single cell RNAseq and ATACseq Differential Expression using Devil satistical tool
nf-core-evoverse
Analysis pipleine to model tumour clonal evolution from WGS data (driver annotation, quality control of copy number calls, subclonal and mutational signature deconvolution)
Stat_Rethinking
Probabilistic modelling in Stan
Katerina10-cloud's Repositories
Katerina10-cloud/devilCaseStudies
Case studies of single cell RNAseq and ATACseq Differential Expression using Devil satistical tool
Katerina10-cloud/CLLproject
Katerina10-cloud/CN-aware-DGE
Katerina10-cloud/nf-core-evoverse
Analysis pipleine to model tumour clonal evolution from WGS data (driver annotation, quality control of copy number calls, subclonal and mutational signature deconvolution)
Katerina10-cloud/Stat_Rethinking
Probabilistic modelling in Stan