ArticleBioinformatics (Oxford, England)2024
TKSM: highly modular, user-customizable, and scalable transcriptomic sequencing long-read simulator.
Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Oarfish: enhanced probabilistic modeling leads to improved accuracy in long read transcriptome quantification.Bioinformatics (Oxford, England) · 2025Article
- AsaruSim: a single-cell and spatial RNA-Seq Nanopore long-reads simulation workflow.Bioinformatics (Oxford, England) · 2025Article
- Simulation of nanopore sequencing signal data with tunable parameters.Genome research · 2024Article
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5 authors.
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Abstract
motivationTranscriptomic long-read (LR) sequencing is an increasingly cost-effective technology for probing various RNA features. Numerous tools have been developed to tackle various transcriptomic sequencing tasks (e.g. isoform and gene fusion detection). However, the lack of abundant gold-standard datasets hinders the benchmarking of such tools. Therefore, the simulation of LR sequencing is an important and practical alternative. While the existing LR simulators aim to imitate the sequencing machine noise and to target specific library protocols, they lack some important library preparation steps (e.g. PCR) and are difficult to modify to new and changing library preparation techniques (e.g. single-cell LRs).
resultsWe present TKSM, a modular and scalable LR simulator, designed so that each RNA modification step is targeted explicitly by a specific module. This allows the user to assemble a simulation pipeline as a combination of TKSM modules to emulate a specific sequencing design. Additionally, the input/output of all the core modules of TKSM follows the same simple format (Molecule Description Format) allowing the user to easily extend TKSM with new modules targeting new library preparation steps. AVAILABILITY AND IMPLEMENTATION: TKSM is available as an open source software at https://github.com/vpc-ccg/tksm.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.