Long-read sequencing transcriptome quantification with lr-kallisto.

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Tác giả: A Sina Booeshagi, Ghassan Filimban, Shimako Kawauchi, Heidi Y Liang, Rebekah K Loving, Grant MacGregor, Ali Mortazavi, Conrad Oakes, Lior Pachter, Elisabeth Rebboah, Fairlie Reese, Narges Rezaie, Jasmine Sakr, Delaney K Sullivan, Diane Trout, Brian A Williams, Barbara J Wold

Ngôn ngữ: eng

Ký hiệu phân loại: 025.348 *Sound recordings and music scores

Thông tin xuất bản: United States : bioRxiv : the preprint server for biology , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 215186

RNA abundance quantification has become routine and affordable thanks to high-throughput "short-read" technologies that provide accurate molecule counts at the gene level. Similarly accurate and affordable quantification of definitive full-length, transcript isoforms has remained a stubborn challenge, despite its obvious biological significance across a wide range of problems. "Long-read" sequencing platforms now produce data-types that can, in principle, drive routine definitive isoform quantification. However some particulars of contemporary long-read datatypes, together with isoform complexity and genetic variation, present bioinformatic challenges. We show here, using ONT data, that fast and accurate quantification of long-read data is possible and that it is improved by exome capture. To perform quantifications we developed lr-kallisto, which adapts the kallisto bulk and single-cell RNA-seq quantification methods for long-read technologies.
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