A single-cell sequencing study using more than 30,000 tumour genomes from human ovarian cancers shows that whole-genome doubling is an ongoing mutational process that drives tumour evolution and disru...

Many tumors evolve through cellular mutation and selection, where subpopulations of cells (subclones) with shared ancestry compete for dominance. Introduction of next generation sequencing enables sub...

Single-cell DNA sequencing (scDNA-seq) enables decoding somatic cancer variation. Existing methods are hampered by low throughput or cannot be combined with transcriptome sequencing in the same cell. ...

Abstract. Amorphous silica deposits found in orthoquartzite caves offer valuable analogues for understanding early life on Earth and potential biosignatures on Mars. This study presents the fully on-s...

Snakemake is a python extension for writing workflows. Genomics data processing usually requires bundling many different tools to reach a stage that is ready for downstream analysis. I have been using snakemake writing workflows for various genomic and epigenomic datasets. pyflow-ChIP-seq DNA-seq pyflow-RNA-seq pyflow-ATAC-seq pyflow-RRBSeq pyflow-cellranger pyflow-scATACseq The DNAseq Snakemake pipeline is the most complicated workflow I have written so far. I will need to think about refining it, modulizing it and adding conda env support.

Snakemake is a python extension for writing workflows. Genomics data processing usually requires bundling many different tools to reach a stage that is ready for downstream analysis. I have been using snakemake writing workflows for various genomic and epigenomic datasets. pyflow-ChIP-seq DNA-seq pyflow-RNA-seq pyflow-ATAC-seq pyflow-RRBSeq pyflow-cellranger pyflow-scATACseq The DNAseq Snakemake pipeline is the most complicated workflow I have written so far. I will need to think about refining it, modulizing it and adding conda env support.