Barcode identification for single cell genomics
Identifieur interne : 000683 ( Main/Exploration ); précédent : 000682; suivant : 000684Barcode identification for single cell genomics
Auteurs : Akshay Tambe [États-Unis] ; Lior Pachter [États-Unis]Source :
- BMC Bioinformatics [ 1471-2105 ] ; 2019.
Descripteurs français
- KwdFr :
- MESH :
- génétique : ADN.
- Analyse de séquence d'ADN, Génomique, Humains, Séquençage nucléotidique à haut débit.
English descriptors
- KwdEn :
- MESH :
- chemical , genetics : DNA.
- methods : Genomics, High-Throughput Nucleotide Sequencing, Sequence Analysis, DNA.
- Humans.
Abstract
Single-cell sequencing experiments use short DNA barcode ‘tags’ to identify reads that originate from the same cell. In order to recover single-cell information from such experiments, reads must be grouped based on their barcode tag, a crucial processing step that precedes other computations. However, this step can be difficult due to high rates of mismatch and deletion errors that can afflict barcodes.
Here we present an approach to identify and error-correct barcodes by traversing the de Bruijn graph of circularized barcode k-mers. Our approach is based on the observation that circularizing a barcode sequence can yield error-free k-mers even when the size of
We show that for single-cell RNA-Seq circularization improves the recovery of accurate single-cell transcriptome estimates, especially when there are a high number of errors per read. This approach is robust to the type of error (mismatch, insertion, deletion), as well as to the relative abundances of the cells. Sircel, a software package that implements this approach is described and publically available.
The online version of this article (10.1186/s12859-019-2612-0) contains supplementary material, which is available to authorized users.
Url:
DOI: 10.1186/s12859-019-2612-0
PubMed: 30654736
PubMed Central: 6337828
Affiliations:
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xml:lang="fr">États-Unis</country><placeName><region type="state">Californie</region></placeName><wicri:cityArea>116 Kerckhoff Laboratory, Pasadena</wicri:cityArea></affiliation></author><author><name sortKey="Pachter, Lior" sort="Pachter, Lior" uniqKey="Pachter L" first="Lior" last="Pachter">Lior Pachter</name><affiliation wicri:level="2"><nlm:aff id="Aff2"><institution-wrap><institution-id institution-id-type="ISNI">0000000107068890</institution-id><institution-id institution-id-type="GRID">grid.20861.3d</institution-id><institution>Departments of Biology and Computing & Mathematical Sciences,</institution><institution>California Institute of Technology,</institution></institution-wrap>116 Kerckhoff Laboratory, Pasadena, CA 91125 USA</nlm:aff><country xml:lang="fr">États-Unis</country><placeName><region type="state">Californie</region></placeName><wicri:cityArea>116 Kerckhoff Laboratory, Pasadena</wicri:cityArea></affiliation></author></analytic><series><title level="j">BMC Bioinformatics</title><idno type="eISSN">1471-2105</idno><imprint><date when="2019">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>DNA (genetics)</term><term>Genomics (methods)</term><term>High-Throughput Nucleotide Sequencing (methods)</term><term>Humans</term><term>Sequence Analysis, DNA (methods)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>ADN (génétique)</term><term>Analyse de séquence d'ADN ()</term><term>Génomique ()</term><term>Humains</term><term>Séquençage nucléotidique à haut débit ()</term></keywords><keywords scheme="MESH" type="chemical" qualifier="genetics" xml:lang="en"><term>DNA</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>ADN</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Genomics</term><term>High-Throughput Nucleotide Sequencing</term><term>Sequence Analysis, DNA</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Humans</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Analyse de séquence d'ADN</term><term>Génomique</term><term>Humains</term><term>Séquençage nucléotidique à haut débit</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p id="Par1">Single-cell sequencing experiments use short DNA barcode ‘tags’ to identify reads that originate from the same cell. In order to recover single-cell information from such experiments, reads must be grouped based on their barcode tag, a crucial processing step that precedes other computations. However, this step can be difficult due to high rates of mismatch and deletion errors that can afflict barcodes.</p></sec><sec><title>Results</title><p id="Par2">Here we present an approach to identify and error-correct barcodes by traversing the de Bruijn graph of circularized barcode k-mers. Our approach is based on the observation that circularizing a barcode sequence can yield error-free k-mers even when the size of <italic>k</italic> is large relative to the length of the barcode sequence, a regime which is typical single-cell barcoding applications. This allows for assignment of reads to consensus fingerprints constructed from k-mers.</p></sec><sec><title>Conclusion</title><p id="Par3">We show that for single-cell RNA-Seq circularization improves the recovery of accurate single-cell transcriptome estimates, especially when there are a high number of errors per read. This approach is robust to the type of error (mismatch, insertion, deletion), as well as to the relative abundances of the cells. Sircel, a software package that implements this approach is described and publically available.</p></sec><sec><title>Electronic supplementary material</title><p>The online version of this article (10.1186/s12859-019-2612-0) contains supplementary material, which is available to authorized users.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Bray, Nl" uniqKey="Bray N">NL Bray</name></author><author><name sortKey="Pimentel, H" uniqKey="Pimentel H">H Pimentel</name></author><author><name sortKey="Melsted, P" uniqKey="Melsted P">P Melsted</name></author><author><name sortKey="Pachter, L" uniqKey="Pachter L">L Pachter</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Compeau, Pec" uniqKey="Compeau P">PEC Compeau</name></author><author><name sortKey="Pevzner, Pa" uniqKey="Pevzner P">PA Pevzner</name></author><author><name sortKey="Tesler, G" uniqKey="Tesler G">G 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