clonealign: statistical integration of independent single-cell RNA and DNA sequencing data from human cancers

[1]  Sarah A. Teichmann,et al.  Cardelino: Integrating whole exomes and single-cell transcriptomes to reveal phenotypic impact of somatic variants , 2018, bioRxiv.

[2]  Richard A. Moore,et al.  Resource: Scalable whole genome sequencing of 40,000 single cells identifies stochastic aneuploidies, genome replication states and clonal repertoires , 2018, bioRxiv.

[3]  L. Cantley,et al.  The Multifaceted Role of Chromosomal Instability in Cancer and Its Microenvironment , 2018, Cell.

[4]  S. Richardson,et al.  Correcting the Mean-Variance Dependency for Differential Variability Testing Using Single-Cell RNA Sequencing Data , 2018, Cell systems.

[5]  O. Stegle,et al.  Modeling Cell-Cell Interactions from Spatial Molecular Data with Spatial Variance Component Analysis , 2018, bioRxiv.

[6]  Je-Gun Joung,et al.  SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells , 2018, Genome research.

[7]  S. Dudoit,et al.  A general and flexible method for signal extraction from single-cell RNA-seq data , 2018, Nature Communications.

[8]  Hossein Farahani,et al.  E-scape: interactive visualization of single-cell phylogenetics and cancer evolution , 2017, Nature Methods.

[9]  Sydney M. Shaffer,et al.  Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance , 2017, Nature.

[10]  Edda Klipp,et al.  Estimation of immune cell content in tumour tissue using single-cell RNA-seq data , 2017, Nature Communications.

[11]  Samuel Aparicio,et al.  Scalable whole-genome single-cell library preparation without preamplification , 2017, Nature Methods.

[12]  M. Schaub,et al.  SC3 - consensus clustering of single-cell RNA-Seq data , 2016, Nature Methods.

[13]  M. Heymann,et al.  Tumour Heterogeneity: The Key Advantages of Single-Cell Analysis , 2016, International journal of molecular sciences.

[14]  Davis J. McCarthy,et al.  A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor , 2016, F1000Research.

[15]  Grace X. Y. Zheng,et al.  Massively parallel digital transcriptional profiling of single cells , 2016, Nature Communications.

[16]  Alexey Sergushichev,et al.  An algorithm for fast preranked gene set enrichment analysis using cumulative statistic calculation , 2016 .

[17]  N. Beerenwinkel,et al.  Tree inference for single-cell data , 2016, bioRxiv.

[18]  F. Garrido,et al.  The urgent need to recover MHC class I in cancers for effective immunotherapy , 2016, Current opinion in immunology.

[19]  David M. Blei,et al.  Variational Inference: A Review for Statisticians , 2016, ArXiv.

[20]  Sarah A Teichmann,et al.  Computational assignment of cell-cycle stage from single-cell transcriptome data. , 2015, Methods.

[21]  C. Ponting,et al.  G&T-seq: parallel sequencing of single-cell genomes and transcriptomes , 2015, Nature Methods.

[22]  J. Marioni,et al.  High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin , 2015, Nature Biotechnology.

[23]  Sohrab P. Shah,et al.  Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution , 2014, Nature.

[24]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[25]  Siddharth S. Dey,et al.  Integrated genome and transcriptome sequencing from the same cell , 2014, Nature Biotechnology.

[26]  B. Ness,et al.  Single-Cell Transcriptomics Identifies Intra-Tumor Heterogeneity in Human Myeloma Cell Lines , 2014 .

[27]  W. Huber,et al.  Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 , 2014, Genome Biology.

[28]  Sohrab P. Shah,et al.  TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data , 2014, Genome research.

[29]  Max Welling,et al.  Auto-Encoding Variational Bayes , 2013, ICLR.

[30]  Åsa K. Björklund,et al.  Full-length RNA-seq from single cells using Smart-seq2 , 2014, Nature Protocols.

[31]  Charity W. Law,et al.  voom: precision weights unlock linear model analysis tools for RNA-seq read counts , 2014, Genome Biology.

[32]  Joshua M. Stuart,et al.  The Cancer Genome Atlas Pan-Cancer analysis project , 2013, Nature Genetics.

[33]  Anne-Marie Mes-Masson,et al.  Derivation and characterization of matched cell lines from primary and recurrent serous ovarian cancer , 2012, BMC Cancer.

[34]  A. Bashashati,et al.  Integrative analysis of genome-wide loss of heterozygosity and monoallelic expression at nucleotide resolution reveals disrupted pathways in triple-negative breast cancer , 2012, Genome research.

[35]  DNA copy number changes and immunophenotype pattern in karyotypically normal acute myeloid leukemia patients from an Indian population. , 2012, Genetic testing and molecular biomarkers.

[36]  F. Markowetz,et al.  The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups , 2012, Nature.

[37]  F. Garrido,et al.  MHC class I molecules act as tumor suppressor genes regulating the cell cycle gene expression, invasion and intrinsic tumorigenicity of melanoma cells. , 2012, Carcinogenesis.

[38]  Christopher A. Miller,et al.  VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. , 2012, Genome research.

[39]  E. Letouzé,et al.  Analysis of the copy number profiles of several tumor samples from the same patient reveals the successive steps in tumorigenesis , 2010, Genome Biology.

[40]  Derek Y. Chiang,et al.  The landscape of somatic copy-number alteration across human cancers , 2010, Nature.

[41]  M. Robinson,et al.  A scaling normalization method for differential expression analysis of RNA-seq data , 2010, Genome Biology.

[42]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[43]  S. Morrison,et al.  Prospective identification of tumorigenic breast cancer cells , 2003, Proceedings of the National Academy of Sciences of the United States of America.