ArticleBioinformatics (Oxford, England)2024
Flexiplex: a versatile demultiplexer and search tool for omics data.
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 20 papers.
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Who cites it
20 citing papers in PubMed.
- Long-read sequencing-based atlas of tissue-specific expression of DNM1L transcript variants.The FEBS journal · 2026Article
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- A systematic benchmark of bioinformatics methods for single-cell and spatial RNA-seq nanopore long reads data.NAR genomics and bioinformatics · 2026Article
- Spatial isoform sequencing at single-cell resolution reveals cell-type-specific spatial isoform variability in multiple brain cell types.Nature methods · 2026Article
- Transcriptional landscape of direct reprogramming toward the hematopoietic lineage.bioRxiv : the preprint server for biology · 2026Article
- RAD: A Read-structure Agnostic Demultiplexer for Single-Cell Long-Read Sequencing and Analysis.bioRxiv : the preprint server for biology · 2026Article
- ReadChop: a high-performance demultiplexer for long-read sequencing data.Bioinformatics (Oxford, England) · 2026Article
- Barbell reveals and resolves demultiplexing and trimming issues in Nanopore data.Bioinformatics (Oxford, England) · 2026Article
- Current trends and challenges in deciphering single molecule resolution maps of single cell transcriptomes.Briefings in bioinformatics · 2026Review
- Sassy: fuzzy searching DNA sequences using SIMD.Bioinformatics (Oxford, England) · 2026Article
- Review
- Long-read sequencing transcriptome quantification with lr-kallisto.PLoS computational biology · 2025Article
- Bioinformatics frameworks for single-cell long-read sequencing: unlocking isoform-level resolution.Briefings in bioinformatics · 2025Review
- MysteryMaster: scraping the bottom of the barrel of barcoded Oxford nanopore reads.BMC bioinformatics · 2025Article
- Spatial isoform sequencing at sub-micrometer single-cell resolution reveals novel patterns of spatial isoform variability in brain cell types.bioRxiv : the preprint server for biology · 2025Article
- Accelerated Tempo of Cortical Neurogenesis in Down Syndrome.bioRxiv : the preprint server for biology · 2025Article
- Comparison of single-cell long-read and short-read transcriptome sequencing via cDNA molecule matching: quality evaluation of the MAS-ISO-seq approach.NAR genomics and bioinformatics · 2025Article
- Single-cell Rapid Capture Hybridization sequencing reliably detects isoform usage and coding mutations in targeted genes.Genome research · 2025Article
- Flexible parsing, interpretation, and editing of technical sequences with splitcode.Bioinformatics (Oxford, England) · 2024Article
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8 authors.
Funding
Abstract
motivationThe process of analyzing high throughput sequencing data often requires the identification and extraction of specific target sequences. This could include tasks, such as identifying cellular barcodes and UMIs in single-cell data, and specific genetic variants for genotyping. However, existing tools, which perform these functions are often task-specific, such as only demultiplexing barcodes for a dedicated type of experiment, or are not tolerant to noise in the sequencing data.
resultsTo overcome these limitations, we developed Flexiplex, a versatile and fast sequence searching and demultiplexing tool for omics data, which is based on the Levenshtein distance and thus allows imperfect matches. We demonstrate Flexiplex's application on three use cases, identifying cell-line-specific sequences in Illumina short-read single-cell data, and discovering and demultiplexing cellular barcodes from noisy long-read single-cell RNA-seq data. We show that Flexiplex achieves an excellent balance of accuracy and computational efficiency compared to leading task-specific tools. AVAILABILITY AND IMPLEMENTATION: Flexiplex is available at https://davidsongroup.github.io/flexiplex/.
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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.