Droplet sequencing (Drop-seq) is an emerging technology to analyze gene expression from thousands of individual cells simultaneously. Drop-seq uses microfluidics and molecular barcoding to encapsulate individual cells in droplets and analyze their mRNA transcripts. This technology can be used to create molecular atlases of gene expression or characterization of novel cell types, which has applications in cancer or immunology. Software tools are used for quality control and data analysis and representation.
Gathers items dedicated to the management of single-cell (RNA-seq) data resulting from droplet technologies. DropletUtils provides more than 10 utilities allowing users to compute barcode rank statistics or to call cells according to the number of unique molecular identifiers (UMIs) associated with each barcode. It also provides features for identification of cells from empty droplets or generate a sparse or HDF5-backed count matrix. The software includes functions that focuses on data issue from 10X Genomics technology.
Allows quality control (QC) and analysis components of parallel single cell transcriptome and epigenome data. Dr.seq is a quality control (QC) and analysis pipeline that provides both multifaceted QC reports and cell clustering results. Parallel single cell transcriptome data generated by different technologies can be transformed to the standard input with contained functions. Using relevant commands, the software can also be used to report quality measurements based on four aspects and can generate detailed analysis results for scATAC-seq and Drop-ChIP datasets.
Allows systematic exploration of Drop-seq data and quantitative assessment of basic statistics and important parameters. Dropbead is an R package that permits flexible exploration and quantitative assessment of single-cell data generated by droplet-based microfluidics. This method is adapted from the simple methanol-based fixation protocol from Stoeckius et al. and preserves cells for subsequent profiling of single-cell transcriptomes by Drop-seq.
Identifies and error-corrects barcodes by traversing the de Bruijn graph of circularized barcode k-mers. Sircel counts k-mers in circularized barcodes extracted from the reads. It assigns reads to consensus fingerprints constructed from k-mers. The tool permits to make insertion, deletion, and mismatch errors. It requires a minimal number of user-inputted parameters. Sircel can identify several cyclic paths from the barcode de Bruijn graph.