Showing 5 of total 5 results (show query)
shixiangwang
sigminer:Extract, Analyze and Visualize Mutational Signatures for Genomic Variations
Genomic alterations including single nucleotide substitution, copy number alteration, etc. are the major force for cancer initialization and development. Due to the specificity of molecular lesions caused by genomic alterations, we can generate characteristic alteration spectra, called 'signature' (Wang, Shixiang, et al. (2021) <DOI:10.1371/journal.pgen.1009557> & Alexandrov, Ludmil B., et al. (2020) <DOI:10.1038/s41586-020-1943-3> & Steele Christopher D., et al. (2022) <DOI:10.1038/s41586-022-04738-6>). This package helps users to extract, analyze and visualize signatures from genomic alteration records, thus providing new insight into cancer study.
Maintained by Shixiang Wang. Last updated 6 months ago.
bayesian-nmfbioinformaticscancer-researchcnvcopynumber-signaturescosmic-signaturesdbseasy-to-useindelmutational-signaturesnmfnmf-extractionsbssignature-extractionsomatic-mutationssomatic-variantsvisualizationcpp
150 stars 9.48 score 123 scripts 2 dependents
bioc
cardelino:Clone Identification from Single Cell Data
Methods to infer clonal tree configuration for a population of cells using single-cell RNA-seq data (scRNA-seq), and possibly other data modalities. Methods are also provided to assign cells to inferred clones and explore differences in gene expression between clones. These methods can flexibly integrate information from imperfect clonal trees inferred based on bulk exome-seq data, and sparse variant alleles expressed in scRNA-seq data. A flexible beta-binomial error model that accounts for stochastic dropout events as well as systematic allelic imbalance is used.
Maintained by Davis McCarthy. Last updated 5 months ago.
singlecellrnaseqvisualizationtranscriptomicsgeneexpressionsequencingsoftwareexomeseqclonal-clusteringgibbs-samplingscrna-seqsingle-cellsomatic-mutations
61 stars 7.05 score 62 scriptsbioc
CaMutQC:An R Package for Comprehensive Filtration and Selection of Cancer Somatic Mutations
CaMutQC is able to filter false positive mutations generated due to technical issues, as well as to select candidate cancer mutations through a series of well-structured functions by labeling mutations with various flags. And a detailed and vivid filter report will be offered after completing a whole filtration or selection section. Also, CaMutQC integrates serveral methods and gene panels for Tumor Mutational Burden (TMB) estimation.
Maintained by Xin Wang. Last updated 5 months ago.
softwarequalitycontrolgenetargetcancer-genomicssomatic-mutations
7 stars 5.72 score 1 scriptsbioc
HiLDA:Conducting statistical inference on comparing the mutational exposures of mutational signatures by using hierarchical latent Dirichlet allocation
A package built under the Bayesian framework of applying hierarchical latent Dirichlet allocation. It statistically tests whether the mutational exposures of mutational signatures (Shiraishi-model signatures) are different between two groups. The package also provides inference and visualization.
Maintained by Zhi Yang. Last updated 5 months ago.
softwaresomaticmutationsequencingstatisticalmethodbayesianmutational-signaturesrjagssomatic-mutationscppjags
3 stars 5.56 score 7 scripts 1 dependentsbioc
selectKSigs:Selecting the number of mutational signatures using a perplexity-based measure and cross-validation
A package to suggest the number of mutational signatures in a collection of somatic mutations using calculating the cross-validated perplexity score.
Maintained by Zhi Yang. Last updated 5 months ago.
softwaresomaticmutationsequencingstatisticalmethodclusteringmutational-signaturesrjagssomatic-mutationscppjags
3 stars 4.08 score 1 scripts