BnpC: Bayesian non-parametric clustering of single-cell mutation profiles
Sign Up to like & getrecommendations! Published in 2020 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btaa599
Abstract: Abstract Motivation The high resolution of single-cell DNA sequencing (scDNA-seq) offers great potential to resolve intratumor heterogeneity (ITH) by distinguishing clonal populations based on their mutation profiles. However, the increasing size of scDNA-seq datasets and… read more here.
Keywords: single cell; mutation profiles; scdna seq; non parametric ... See more keywords
doubletD: detecting doublets in single-cell DNA sequencing data
Sign Up to like & getrecommendations! Published in 2021 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btab266
Abstract: Abstract Motivation While single-cell DNA sequencing (scDNA-seq) has enabled the study of intratumor heterogeneity at an unprecedented resolution, current technologies are error-prone and often result in doublets where two or more cells are mistaken for… read more here.
Keywords: single cell; scdna seq; cell dna; seq data ... See more keywords
SCClone: Accurate Clustering of Tumor Single-Cell DNA Sequencing Data
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Genetics"
DOI: 10.3389/fgene.2022.823941
Abstract: Single-cell DNA sequencing (scDNA-seq) enables high-resolution profiling of genetic diversity among single cells and is especially useful for deciphering the intra-tumor heterogeneity and evolutionary history of tumor. Specific technical issues such as allele dropout, false-positive… read more here.
Keywords: tumor; dna sequencing; single cell; scclone ... See more keywords