ArticleNature communications2026
Comprehensive assessment of transcriptome assembly quality using CATS.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Comprehensive assessment of transcriptome assembly quality using CATS.Nature communications · 2026Article
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2 authors.
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Abstract
Accurate assessment of transcriptome assembly quality is critical to ensure the reliability of subsequent transcriptomic analyses. Here, we present CATS (Comprehensive Assessment of Transcript Sequences), a tool offering both reference-free (CATS-rf) and reference-based (CATS-rb) transcriptome quality evaluation pipelines. CATS-rf maps RNA-seq reads back to the assembled transcripts and computes four interpretable scoring components that capture common assembly errors. CATS-rb assesses transcriptome completeness via alignment to a reference genome, supporting both annotation-free and annotation-based scoring. We benchmarked CATS on 1056 transcriptomes from simulated and public RNA-seq data. CATS-rf outperformed existing tools in transcript-level accuracy assessment and demonstrated high sensitivity to diverse assembly error types. CATS-rb produced robust transcriptome completeness estimates even without external annotation, with its scoring metrics strongly reflecting assembly quality. These results highlight CATS as an accurate, interpretable, and broadly applicable framework for evaluating transcriptome assemblies.
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