Single molecule counting and assessment of random molecular tagging errors with transposable giga-scale error-correcting barcodes
Abstract Background RNA-Seq measures gene expression by counting sequence reads belonging to unique cDNA fragments. Molecular barcodes commonly in the form of random nucleotides were recently introduced to improve gene expression measures by detecting amplification duplicates, but are susceptible to...
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| Format: | Article |
| Language: | English |
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BMC
2017-09-01
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| Series: | BMC Genomics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12864-017-4141-4 |
| _version_ | 1819095735161847808 |
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| author | Billy T. Lau Hanlee P. Ji |
| author_facet | Billy T. Lau Hanlee P. Ji |
| author_sort | Billy T. Lau |
| collection | DOAJ |
| description | Abstract Background RNA-Seq measures gene expression by counting sequence reads belonging to unique cDNA fragments. Molecular barcodes commonly in the form of random nucleotides were recently introduced to improve gene expression measures by detecting amplification duplicates, but are susceptible to errors generated during PCR and sequencing. This results in false positive counts, leading to inaccurate transcriptome quantification especially at low input and single-cell RNA amounts where the total number of molecules present is minuscule. To address this issue, we demonstrated the systematic identification of molecular species using transposable error-correcting barcodes that are exponentially expanded to tens of billions of unique labels. Results We experimentally showed random-mer molecular barcodes suffer from substantial and persistent errors that are difficult to resolve. To assess our method’s performance, we applied it to the analysis of known reference RNA standards. By including an inline random-mer molecular barcode, we systematically characterized the presence of sequence errors in random-mer molecular barcodes. We observed that such errors are extensive and become more dominant at low input amounts. Conclusions We described the first study to use transposable molecular barcodes and its use for studying random-mer molecular barcode errors. Extensive errors found in random-mer molecular barcodes may warrant the use of error correcting barcodes for transcriptome analysis as input amounts decrease. |
| first_indexed | 2024-12-21T23:48:01Z |
| format | Article |
| id | doaj.art-b57265452d08471ca6c77fb02703436c |
| institution | Directory Open Access Journal |
| issn | 1471-2164 |
| language | English |
| last_indexed | 2024-12-21T23:48:01Z |
| publishDate | 2017-09-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Genomics |
| spelling | doaj.art-b57265452d08471ca6c77fb02703436c2022-12-21T18:46:01ZengBMCBMC Genomics1471-21642017-09-0118111310.1186/s12864-017-4141-4Single molecule counting and assessment of random molecular tagging errors with transposable giga-scale error-correcting barcodesBilly T. Lau0Hanlee P. Ji1Stanford Genome Technology Center, Stanford UniversityStanford Genome Technology Center, Stanford UniversityAbstract Background RNA-Seq measures gene expression by counting sequence reads belonging to unique cDNA fragments. Molecular barcodes commonly in the form of random nucleotides were recently introduced to improve gene expression measures by detecting amplification duplicates, but are susceptible to errors generated during PCR and sequencing. This results in false positive counts, leading to inaccurate transcriptome quantification especially at low input and single-cell RNA amounts where the total number of molecules present is minuscule. To address this issue, we demonstrated the systematic identification of molecular species using transposable error-correcting barcodes that are exponentially expanded to tens of billions of unique labels. Results We experimentally showed random-mer molecular barcodes suffer from substantial and persistent errors that are difficult to resolve. To assess our method’s performance, we applied it to the analysis of known reference RNA standards. By including an inline random-mer molecular barcode, we systematically characterized the presence of sequence errors in random-mer molecular barcodes. We observed that such errors are extensive and become more dominant at low input amounts. Conclusions We described the first study to use transposable molecular barcodes and its use for studying random-mer molecular barcode errors. Extensive errors found in random-mer molecular barcodes may warrant the use of error correcting barcodes for transcriptome analysis as input amounts decrease.http://link.springer.com/article/10.1186/s12864-017-4141-4TranscriptomeRNA-SeqMolecular barcoding |
| spellingShingle | Billy T. Lau Hanlee P. Ji Single molecule counting and assessment of random molecular tagging errors with transposable giga-scale error-correcting barcodes BMC Genomics Transcriptome RNA-Seq Molecular barcoding |
| title | Single molecule counting and assessment of random molecular tagging errors with transposable giga-scale error-correcting barcodes |
| title_full | Single molecule counting and assessment of random molecular tagging errors with transposable giga-scale error-correcting barcodes |
| title_fullStr | Single molecule counting and assessment of random molecular tagging errors with transposable giga-scale error-correcting barcodes |
| title_full_unstemmed | Single molecule counting and assessment of random molecular tagging errors with transposable giga-scale error-correcting barcodes |
| title_short | Single molecule counting and assessment of random molecular tagging errors with transposable giga-scale error-correcting barcodes |
| title_sort | single molecule counting and assessment of random molecular tagging errors with transposable giga scale error correcting barcodes |
| topic | Transcriptome RNA-Seq Molecular barcoding |
| url | http://link.springer.com/article/10.1186/s12864-017-4141-4 |
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