Identifies subclone-specific focal copy number variation (CNV) and loss of heterozygosity (LOH) events in individual cells, using allele and expression information from Single-cell RNA-sequencing (scRNA-seq) data. HoneyBADGER can find deletion, amplifications, and copy neutral LOH events. The software is also able to detect subclonal focal alterations as small as 10 megabases. It can assist in unraveling the impact of genetic and transcriptional heterogeneity and their interplay in cancer progression.
Provides several interlocking programs that analyze mutations in genes. MutationForecaster is a system that interprets non-coding variants altering recognition of binding sites in genomic DNA (transcription factors) and mRNA (splicing, RNA binding proteins). This suite allows, among other features, to identify splicing and promoter mutations in gene panels, exomes, and genomes, to analyze coding sequence changes, or to validate splicing mutations with RNA-Seq data.
Retrieves copy number variations (CNVs) using a multiscale signal-processing framework. CaSpER builds allelic shift signal profile to quantify genome-wide loss-of-heterozygosity. It employs hidden Markov models (HMM) to integrate this profile in the multiscale analysis and assign CNVs. This tool can perform visualization and integrative analysis of focal and large-scale CNV events in multiscale resolution.
Provides a single-cell-specific variant caller that combines single-cell genotyping with reconstruction of the cell lineage tree. SCIPhI leverages the fact that somatic cells of an organism are related via a phylogenetic tree where mutations are propagated along tree branches. It can also identify single-nucleotide variants (SNVs) in single cells with low or even no variant allele support.
Harnesses genetic variation to determine the genetic identity of each droplet containing a single cell. Demuxlet can detect droplets containing two cells from different individuals (doublets). It implements a statistical model for evaluating the likelihood of observing RNA-seq reads overlapping a set of single nucleotide polymorphisms (SNPs) from each cell- containing droplet.
Provides an approach for aneuploidies calling in single-cell RNA-sequencing. scploid is an R package performing for each cell, the identification of chromosomes including genes with potentially detected deviant expression, by applying a statistical method. It aims to supplies a straightforward and easy to interpret method for stem cell and embryonic research as well as assists users in determining genes possibly associated with copy number aberrations.
A linear modeling framework that correlates genotype and phenotype information in scRNA-seq data. SSrGE uses an accumulative ranking approach to select expressed nucleotide variations linked to the expression of a particular gene. SSrGE infers a sparse linear model for each gene and keeps the non-null inferred coefficients. SSrGE can be used as a dimension reduction/feature selection procedure or as a feature ranking. In all the cancer datasets tested, effective and expressed nucleotide variations (eeSNVs) achieve better accuracies and visualization than gene expression for identifying subpopulations