scSNPdemux : a sensitive demultiplexing pipeline using single nucleotide polymorphisms for improved pooled single-cell RNA sequencing analysis
© 2023. BioMed Central Ltd., part of Springer Nature..
BACKGROUND: Here we present scSNPdemux, a sample demultiplexing pipeline for single-cell RNA sequencing data using natural genetic variations in humans. The pipeline requires alignment files from Cell Ranger (10× Genomics), a population SNP database and genotyped single nucleotide polymorphisms (SNPs) per sample. The tool works on sparse genotyping data in VCF format for sample identification.
RESULTS: The pipeline was tested on both single-cell and single-nuclei based RNA sequencing datasets and showed superior demultiplexing performance over the lipid-based CellPlex and Multi-seq sample multiplexing technique which incurs additional single cell library preparation steps. Specifically, our pipeline demonstrated superior sensitivity and specificity in cell-identity assignment over CellPlex, especially on immune cell types with low RNA content.
CONCLUSIONS: We designed a streamlined pipeline for single-cell sample demultiplexing, aiming to overcome common problems in multiplexing samples using single cell libraries which might affect data quality and can be costly.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:24 |
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| Enthalten in: |
BMC bioinformatics - 24(2023), 1 vom: 31. Aug., Seite 326 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Wong, John K L [VerfasserIn] |
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| Links: |
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| Themen: |
Journal Article |
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| Anmerkungen: |
Date Completed 04.09.2023 Date Revised 21.11.2023 published: Electronic Citation Status MEDLINE |
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| doi: |
10.1186/s12859-023-05440-8 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a © 2023. BioMed Central Ltd., part of Springer Nature. | ||
| 520 | |a BACKGROUND: Here we present scSNPdemux, a sample demultiplexing pipeline for single-cell RNA sequencing data using natural genetic variations in humans. The pipeline requires alignment files from Cell Ranger (10× Genomics), a population SNP database and genotyped single nucleotide polymorphisms (SNPs) per sample. The tool works on sparse genotyping data in VCF format for sample identification | ||
| 520 | |a RESULTS: The pipeline was tested on both single-cell and single-nuclei based RNA sequencing datasets and showed superior demultiplexing performance over the lipid-based CellPlex and Multi-seq sample multiplexing technique which incurs additional single cell library preparation steps. Specifically, our pipeline demonstrated superior sensitivity and specificity in cell-identity assignment over CellPlex, especially on immune cell types with low RNA content | ||
| 520 | |a CONCLUSIONS: We designed a streamlined pipeline for single-cell sample demultiplexing, aiming to overcome common problems in multiplexing samples using single cell libraries which might affect data quality and can be costly | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Sample demultiplexing | |
| 650 | 4 | |a Sample pooling | |
| 650 | 4 | |a Single nucleotide polymorphisms | |
| 650 | 4 | |a Single-cell | |
| 700 | 1 | |a Jassowicz, Lena |e verfasserin |4 aut | |
| 700 | 1 | |a Herold-Mende, Christel |e verfasserin |4 aut | |
| 700 | 1 | |a Seiffert, Martina |e verfasserin |4 aut | |
| 700 | 1 | |a Mallm, Jan-Philipp |e verfasserin |4 aut | |
| 700 | 1 | |a Lichter, Peter |e verfasserin |4 aut | |
| 700 | 1 | |a Zapatka, Marc |e verfasserin |4 aut | |
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