Bhardwaj V. and Mourragui S. (2023) sincei: A user-friendly toolkit for QC, counting, clustering and plotting of single-cell (epi)genomics data.
Installation
sincei is a command line toolkit based on python3, and can be installed using conda
Create a new conda environment and install sincei using:
conda create -n sincei -c anaconda python=3.8
conda activate sincei
(sincei): pip install git+https://github.com/vivekbhr/sincei.git@master#egg=sincei
Getting Help
For all kind of questions, suggesting changes/enhancements or to report bugs, please create an issue on our GitHub repository
Please Note that sincei is under active development. Some features might be incomplete, untested or might be removed as we move towards a stable version.
The list of tools available in sincei
Tools for a typical single-cell analysis workflow (WIP: work in progress/not available yet)
tool |
description |
|---|---|
Identify and filter cell barcodes from BAM file (for droplet-based single-cell seq) |
|
Produce per-cell statistics after filtering reads by user-defined criteria. |
|
Counts reads for each barcode on genomic bins or user-defined features. |
|
Perform quality control and filter the output of scCountReads. |
|
Concatenate/merge the counts from different samples/batches or modalities |
|
Perform dimensionality reduction and clustering on the output of scCountReads. |
|
Get pseudo-bulk coverage per group using a user-supplied cell->group mapping (output of scClusterCells). |
|
scFindMarkers |
[WIP] Find marker genes per group, given the output of scCountReads and a user-defined group. |
scFeaturePlot |
[WIP] Plot the counts for a given feature on a UMAP or on a (IGV-style) genomic-track. |