Resources

Group gitHub

Tumor heterogeneity and evolution

• Single Cell
  • Single-Cell Multiomics Analysis
    • bindSC: integrating datasets obtained from different technologies including scRNA-seq, scATAC-seq, spatial omics and CyTOF
    • SCMER: selecting most informative features/genes/proteins in a single-cell dataset.
  • Single-Cell DNA Analysis
    • Monovar: Variant detection from single-cell DNA sequencing data
    • Single cell lineage inference
      • SiFit, phylogenetic tree from somatic mutations detected in single cell DNA
      • MEDALT, phylogenetic tree from somatic copy number alterations detected in single cell DNA
  • Single-Cell RNA Analysis
    • Cell-type/signature characterization
      • SCMarker, cell-type specific marker
    • Developmental/temporal inference
      • Cyclum, latent periodic process (e.g., cell cycle, EMT, circadian rhythm) inference
  • Single-Cell Proteomics
    • CytoSpill: reduce spillover noise in CyTOF data
• Tissue deconvolution
  • Texomer, just autologous DNA/RNA-seq data analysis

Human Genomics

• Genomic Structural Variation
  • Identification of structural variants from the next generation sequencing (NGS) data
    • novoBreak (bioconda)
    • BreakDancer
    • TIGRA
    • CREST
  • Identification of structural variants from the single molecule (PacBio) sequencing data
    • HySA
  • Detection of somatic single nucleotide variants and small indels in NGS cancer genomes
    • ClinSeK
    • SomaticSniper, additional instructions
    • Detection of somatic SNVs and Indels from PCR targeted Sanger sequencing data

Transcriptomics

• Detection of gene fusions from paired end whole-transcriptome RNA-seq data
  • BreakFusion
• Integrative fusion/genomic breakpoint identification from DNA and RNA sequencing data
  • BreakTrans

Functional Genomics

• Cancer driver mutation annotation
  • CanDrA
• Multi-level Variant annotation
  • TransVar, web, forward/reverse genomic/transcriptome/proteome