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CITE-seq dataset for bench marking countASAP: A Lightweight, Easy to Use Python Package for Processing ASAPseq Data

ABSTRACT: A recently developed technique, transposase-accessible chromatin with sequencing (ATAC) with select antigen profiling by sequencing (ASAPseq), provides a combination of chromatin accessibility assessments with measurements of cell- surface marker expression levels. While software exists for the characterization of these datasets, there currently exists no tool explicitly designed to reformat ASAP surface marker FASTQ data into a count matrix which can then be used for these downstream analyses. To address this, we created CountASAP, an easy-to-use Python package purposefully designed to transform FASTQ files from ASAP experiments into count matrices compatible with commonly-used downstream bioinformatic analysis packages. This dataset is only the CSP layer of a CITE-seq well. We use this data to benchmark our tool (countASAP) against existing tools such as Kallisto and Cell Ranger. ASAP-seq data could not be directly used for this cross platform benchmarking since the latter tools are explicitly designed to support alignment of CITE-seq feature barcodes but not those from ASAP-seq.

INSTRUMENT(S): Illumina NovaSeq 6000

ORGANISM(S): Mus musculus

SUBMITTER: Budha Chatterjee

PROVIDER: E-MTAB-15923 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Information management central to JCAHO surveys.

Hospital peer review 20001201 12

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PMID: 11188107

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