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Updated: Jan 10, 2026

3' End Sequencing Library Preparation with A-seq2

3' End Sequencing Library Preparation with A-seq2

Published on: October 10, 2017

CountASAP: a lightweight, easy to use python package for processing ASAPseq data.

Christopher T Boughter¹, Budha Chatterjee², Yuko Ohta²

¹Computational Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA.

BMC Bioinformatics

|November 28, 2025

Summary

This summary is machine-generated.

CountASAP is a new Python package that processes ASAPseq data, converting FASTQ files into count matrices for downstream analysis. This tool enhances single-cell genomics research by providing specialized processing for ASAPseq experiments.

Keywords:

ASAPseq, Multi-omics, scRNAseq, Bioinformatics, Vaccine

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Area of Science:

Single-cell multi-omics
Genomics and transcriptomics
Computational biology

Background:

Single-cell sequencing technologies are rapidly advancing, enabling detailed genomic and transcriptomic analyses.
Transposase-accessible chromatin with sequencing (ATAC) combined with select antigen profiling by sequencing (ASAPseq) allows simultaneous measurement of chromatin accessibility and cell-surface markers.
Existing software does not specifically address the reformatting of ASAPseq surface marker FASTQ data into usable count matrices.

Purpose of the Study:

To develop a dedicated software tool for processing ASAPseq data.
To create a Python package that converts ASAPseq FASTQ files into count matrices for downstream bioinformatic analyses.

Main Methods:

Developed CountASAP, a Python package for ASAPseq data processing.
Implemented parallelized matching of sequenced reads to cell identifiers and oligos.
Benchmarked CountASAP against existing tools using CITEseq data.
Validated CountASAP with a novel ASAPseq dataset.

Main Results:

CountASAP successfully transforms ASAPseq FASTQ files into count matrices.
Performance and user-friendliness were comparable to existing tools on similar data.
Generated biologically meaningful results from ASAPseq data that correlate with chromatin accessibility data.

Conclusions:

CountASAP is the first tool specifically designed for ASAPseq data processing.
The software is efficient, user-friendly, and easy to install.
CountASAP provides reliable processing for single-cell multi-omics data.