Evidence map›Paper›PMID 40248491›Full record

ArticleNAR genomics and bioinformatics2025

Fast analysis of Spatial Transcriptomics (FaST): an ultra lightweight and fast pipeline for the analysis of high resolution spatial transcriptomics.

Valerio Fulci

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Valerio FulciDipartimento di Medicina Molecolare. Università di Roma "La Sapienza", Viale Regina Elena, 291 Rome, Italy.ORCID https://orcid.org/0000-0002-1173-585X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, several protocols repurposing the Illumina flow cells or DNA nanoballs as an RNA capture device for spatial transcriptomics have been reported. These protocols yield high volumes of sequencing data which are usually analyzed through the use of high-performance computing clusters. I report Fast analysis of Spatial Transcriptomic (FaST), a novel pipeline for the analysis of subcellular resolution spatial transcriptomics datasets based on barcoding. FaST is compatible with OpenST, seq-scope, Stereo-seq, and potentially other protocols. It allows full reconstruction of the spatially resolved transcriptome, including cell segmentation, of datasets consisting of >500 M million reads in as little as 1 h on a standard multi core workstation with 32 Gb of RAM. The FaST pipeline returns RNA segmented Spatial Transcriptomics datasets suitable for subsequent analysis through commonly used packages (e.g scanpy or seurat). Notably, the pipeline I present relies on the spateo-release package for RNA segmentation and does not require hematoxylin/eosin or any other imaging procedure to guide cell segmentation. Nevertheless, integration with other software for imaging-guided cell segmentation is still possible. FaST is publicly available on github (https://github.com/flcvlr/FaST).

Indexed as

Gene Expression ProfilingSoftwareTranscriptomeHigh-Throughput Nucleotide SequencingHumansSequence Analysis, RNA

Identifiers

PMID40248491
PMCPMC12004221

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

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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.