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sincei

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Toolkit for processing and analyzing single-cell (epi)genomics data.

https://sincei.readthedocs.io

sincei (short for Single Cell Informatics) is a command-line toolkit for exploration of single-cell epigenomics data. It accommodates data from a wide range of single-cell protocols, such as droplet-based (10x Genomics) and plate-based protocols, gene expression (scRNA-seq) and epigenomics (scATAC, scCUTnTAG, scBS-seq). sincei can be used for quality control of these datasets directly from BAM files (read-level QC), as well as after signal aggregation (count-level). Additional functionalities include filtering, dimensionality reduction, and plotting of single-cell data.

The MultiQC module for sincei parses the following text outputs:

  • scFilterStats (default output file)
  • scCountQC --outMetrics (currently the cell-level metrics are supported)

sincei reports one row per cell, identified by Cell_ID. MultiQC parses the sample name from the part of Cell_ID before :: and aggregates metrics across cells by taking the median per sample. Each row in the report tables therefore represents one sample, summarising all of its cells.

File search patterns​

sincei/scCountQC:
  contents: "Cell_ID\tbarcodes\tsample\tn_genes_by_counts\tlog1p_n_genes_by_counts\t\
    total_counts"
  fn: '*.cells.tsv'
sincei/scFilterStats:
  contents: "Cell_ID\tTotal_sampled\tFiltered\tBlacklisted\tLow_MAPQ\tMissing_Flags\t\
    Excluded_Flags"
  num_lines: 1
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