ArticleBMC bioinformatics2024
CAREx: context-aware read extension of paired-end sequencing data.
Article in BMC bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Anchorage accurately assembles anchor-flanked synthetic long reads.Algorithms for molecular biology : AMB · 2025Article
- Anchorage Accurately Assembles Anchor-Flanked Synthetic Long Reads.Algorithms in bioinformatics : ... International Workshop, WABI ..., proceedings. WABI (Workshop) · 2024Article
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Authors and funding
2 authors.
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Abstract
backgroundCommonly used next generation sequencing machines typically produce large amounts of short reads of a few hundred base-pairs in length. However, many downstream applications would generally benefit from longer reads.
resultsWe present CAREx-an algorithm for the generation of pseudo-long reads from paired-end short-read Illumina data based on the concept of repeatedly computing multiple-sequence-alignments to extend a read until its partner is found. Our performance evaluation on both simulated data and real data shows that CAREx is able to connect significantly more read pairs (up to
conclusionCAREx is a new MSA-based algorithm and software for producing pseudo-long reads from paired-end short read data. It outperforms other state-of-the-art programs in terms of (i) percentage of connected read pairs, (ii) reduction of error rates of filled gaps, (iii) runtime, and (iv) downstream analysis using de novo assembly. CAREx is open-source software written in C++ (CPU version) and in CUDA/C++ (GPU version). It is licensed under GPLv3 and can be downloaded at ( https://github.com/fkallen/CAREx ).
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