10XGenomics/cellranger

10x Genomics Single Cell Analysis

What it solves

It provides a standardized way to process raw data from 10x Genomics Chromium Single Cell platforms, turning raw sequencing reads into usable biological data like gene counts and transcript sequences.

How it works

It uses a set of analysis pipelines to perform several key tasks: sample demultiplexing, barcode processing, and counting genes for single cell 3' and 5' expressions. It also handles V(D)J transcript sequence assembly and annotation, as well as Feature Barcode analysis.

Who it’s for

Researchers and scientists working with single-cell sequencing data generated by 10x Genomics Chromium platforms.

Highlights

  • Standardized pipelines for single-cell gene counting
  • Support for V(D)J transcript sequence assembly
  • Support for Feature Barcode analysis
  • Handles both 3' and 5' gene counting

Related

  • Project
    broadinstitute/CellBender

    A software package that removes ambient RNA and barcode swapping artifacts from single-cell RNA sequencing data to improve data quality.

  • Project
    scverse/gget

    A command-line tool and Python package for efficient, single-line querying of genomic reference databases and sequence analysis.

  • Project
    usadellab/Helixer

    Helixer is a structural genome annotation tool that uses deep learning and Hidden Markov Models to perform ab initio gene calling across various species lineages.

  • Project
    OmicsML/dance

    A deep learning toolkit for single-cell gene expression analysis that provides a benchmark platform for reproducing experiments and automated preprocessing recommendations.

  • Project
    DataScienceUIBK/Rankify

    A comprehensive Python toolkit for retrieval, re-ranking, and RAG, providing a unified interface to experiment with and deploy state-of-the-art models.