Offers a validated protocol to accurately identify single-nucleotide variants (SNVs) across the genome from a single cell after whole-genome amplification (WGA). SCcaller is a single-cell-variant caller that was designed to adjust allelic amplification bias when estimating the likelihoods of three possibilities—artifact, heterozygous SNV and homozygous SNV for every candidate SNV locus. It also corrects for local allelic amplification bias in SNV calling.
Estimates quality and properties of single cell whole-genome sequencing (scWGS) data. PaSD-qc is an open source program that includes functionalities for detecting sub-chromosomal with amplification abnormalities, evaluating the distribution of amplicon sizes in a sample or determining copy-altered or poorly amplified individual chromosomes. The application is suited to be incorporated into pipelines.
Can quantify cellular heterogeneity and identify novel candidate biomarkers. SinCHet is a MATLAB package with a graphical user interface (GUI) for visualization and user interaction, originally for cancer research but with the potential to be used for any single cell research. It provides unique insights into emerging or disappearing clones at different clonal resolutions between cell populations in different contexts. This method could be easily applied to compare heterogeneity between groups.
Features an efficient bin-free segmentation approach and provides the highest resolution possible for breakpoint detection and the subsequent copy number calling. SCNV is a toolkit that can auto-tune parameters based on a set of normal cells from the same batch to adjust for the technical noise level of the data, facilitating its application to data gathered from different platforms and different studies.
Identifies and excludes non-target sequences independent of database. SAG-QC calculates the probability that a sequence was derived from contaminants by comparing k-mer compositions with the no template control sequences. It can determine bins of target sequences without any existing information. The tool is designed to exclude contaminant sequences from contigs. It can predict the distribution of target sequences accurately unless the single-amplified genome (SAG) sequences are extremely contaminated.
Permits to estimate cell distance matrix. SCuPhr provides a site pair model to search for mutations. This model captures various sources of noise associated with sequencing of single cells. It was implemented in an inference algorithm based on dynamic programming. This model contains variables associated with pairs of loci, of which one is homozygous and the other heterozygous, and has the capacity to perform Bayesian probabilistic read phasing.
Calls clonal somatic mutations in genome sequencing data from single cells. Conbase identifies clonal somatic single nucleotide variants (sSNVs) with the aim of deciphering cell lineages in human beings. The software was designed with the goal to find a strategy to eliminate false variant calls in whole genome sequencing (WGS) data from amplified single cell DNA, for identifying variants that can be used to screen additional cells for the presence or absence of the somatic mutations.
Allows users to validate candidate somatic single nucleotide variation (sSNVs) occurring close to germline heterozygous SNPs (gHets). LiRA permits to determine false positive (FPs) sSNV calls from factors related to one strand of DNA, and true positive (TPs) from both strands of one chromosome. It is able to perform SNV calling in single cells.
Provides an interactive web-browser environment for the visualization of single cell genomics. SciBrow was developed to detect contamination of DNA contig scaffolds. It uses principal component analysis based on a vector matrix generated by random k-mer annotation on the DNA sequences. Each DNA sequence is then projected onto the first three vectors and each set of data is traced against the others, generating three linear graphs that can be explored interactively.
0 - 0 of 0
1 - 2 of 2