ArticleBMC genomics2025
BestopCloud: an integrated one-stop solution for single-cell RNA sequencing data analysis.
Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
11 authors.
Funding
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Abstract
Single-cell RNA sequencing (scRNA-seq) technology has emerged as a powerful tool for unveiling cellular heterogeneity, yet the high dimensionality and complexity of the data it generates pose analytical challenges for non-professional programmers. To streamline the process, we have developed BestopCloud, a functionally comprehensive and user-friendly online analysis platform. Comprising nine modules, BestopCloud supports diverse parameter settings within each module and is capable of producing high-quality chart files. Furthermore, these modules can be used independently and flexibly linked through data flow. In summary, BestopCloud provides researchers with an in-depth solution for scRNA-seq data processing, analysis, and visualization.
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Registered trials
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.