(Q30762666)

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An assessment of computational methods for estimating purity and clonality using genomic data derived from heterogeneous tumor tissue samples

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scholarly article

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Europe PubMed Central

PMC publication ID

8 September 2017

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Europe PubMed Central

An assessment of computational methods for estimating purity and clonality using genomic data derived from heterogeneous tumor tissue samples (English)

1 reference

Europe PubMed Central

PMC publication ID

8 September 2017

1

object named as

Vinod Kumar Yadav

1 reference

Europe PubMed Central

PMC publication ID

8 September 2017

2

object named as

Subhajyoti De

1 reference

Europe PubMed Central

PMC publication ID

8 September 2017

publication date

20 February 2014

1 reference

Europe PubMed Central

PMC publication ID

8 September 2017

Briefings in Bioinformatics

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Europe PubMed Central

PMC publication ID

8 September 2017

16

1 reference

Europe PubMed Central

PMC publication ID

8 September 2017

2

1 reference

Europe PubMed Central

PMC publication ID

8 September 2017

232-241

1 reference

Europe PubMed Central

PMC publication ID

8 September 2017

EXPANDS: expanding ploidy and allele frequency on nested subpopulations

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Quantitative assessment of single-cell RNA-sequencing methods.

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Mutational landscape and significance across 12 major cancer types

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Inferring tumour purity and stromal and immune cell admixture from expression data

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Tumour heterogeneity in the clinic

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The causes and consequences of genetic heterogeneity in cancer evolution

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Tumour heterogeneity and cancer cell plasticity

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Virmid: accurate detection of somatic mutations with sample impurity inference

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THetA: inferring intra-tumor heterogeneity from high-throughput DNA sequencing data

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TrAp: a tree approach for fingerprinting subclonal tumor composition

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PurBayes: estimating tumor cellularity and subclonality in next-generation sequencing data

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DeMix: deconvolution for mixed cancer transcriptomes using raw measured data

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Deconvoluting complex tissues for expression quantitative trait locus-based analyses

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DeconRNASeq: a statistical framework for deconvolution of heterogeneous tissue samples based on mRNA-Seq data

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Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples

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Advances for studying clonal evolution in cancer

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PERT: a method for expression deconvolution of human blood samples from varied microenvironmental and developmental conditions

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Data analysis considerations for detecting copy number changes in formalin-fixed, paraffin-embedded tissues

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Comprehensive molecular portraits of human breast tumours

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PurityEst: estimating purity of human tumor samples using next-generation sequencing data

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Evolutionary pathways in BRCA1-associated breast tumors

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Strelka: accurate somatic small-variant calling from sequenced tumor-normal sample pairs

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Absolute quantification of somatic DNA alterations in human cancer

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Single-cell analysis reveals that noncoding RNAs contribute to clonal heterogeneity by modulating transcription factor recruitment

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Correcting for cancer genome size and tumour cell content enables better estimation of copy number alterations from next-generation sequence data

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Semi-supervised Nonnegative Matrix Factorization for gene expression deconvolution: a case study

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Future medical applications of single-cell sequencing in cancer

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Somatic mosaicism in healthy human tissues

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Identifiers

10.1093/BIB/BBU002

1 reference

Europe PubMed Central

PMC publication ID

8 September 2017

DBLP publication ID

journals/bib/YadavD15

1 reference

DBLP Dataset 2021-01-02

28 January 2021

PMC publication ID

1 reference

Europe PubMed Central

PMC publication ID

8 September 2017

PubMed publication ID

1 reference

Europe PubMed Central

PMC publication ID

8 September 2017

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