scSNV: accurate dscRNA-seq SNV co-expression analysis using duplicate tag collapsing
Abstract Identifying single nucleotide variants has become common practice for droplet-based single-cell RNA-seq experiments; however, presently, a pipeline does not exist to maximize variant calling accuracy. Furthermore, molecular duplicates generated in these experiments have not been utilized to optimally detect variant co-expression. Herein, we introduce scSNV designed from the ground up to “collapse” molecular duplicates and accurately identify variants and their co-expression. We demonstrate that scSNV is fast, with a reduced false-positive variant call rate, and enables the co-detection of genetic variants and A>G RNA edits across twenty-two samples..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:22 |
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| Enthalten in: |
Genome biology - 22(2021), 1 vom: 07. Mai |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Wilson, Gavin W. [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| BKL: | |
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| Themen: |
Alignment |
| Anmerkungen: |
© The Author(s) 2021 |
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| doi: |
10.1186/s13059-021-02364-5 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Abstract Identifying single nucleotide variants has become common practice for droplet-based single-cell RNA-seq experiments; however, presently, a pipeline does not exist to maximize variant calling accuracy. Furthermore, molecular duplicates generated in these experiments have not been utilized to optimally detect variant co-expression. Herein, we introduce scSNV designed from the ground up to “collapse” molecular duplicates and accurately identify variants and their co-expression. We demonstrate that scSNV is fast, with a reduced false-positive variant call rate, and enables the co-detection of genetic variants and A>G RNA edits across twenty-two samples. | ||
| 650 | 4 | |a Single-cell RNA-seq | |
| 650 | 4 | |a Genetic variation | |
| 650 | 4 | |a Alignment | |
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| 700 | 1 | |a Darling, Gail E. |4 aut | |
| 700 | 1 | |a Yeung, Jonathan C. |4 aut | |
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