ArticlePLoS computational biology2022
scAmpi-A versatile pipeline for single-cell RNA-seq analysis from basics to clinics.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
- A tumor profiling resource for ovarian cancer: insights into chemotherapy-driven heterogeneity and personalized treatment strategy.Nature communications · 2026Article
- Ovarian cancer metastasis to the human omentum disrupts organ homeostasis and induces fundamental tissue reprogramming.Nature communications · 2025Article
- Single-cell landscape of innate and acquired drug resistance in acute myeloid leukemia.Nature communications · 2024Article
- Automated single-cell omics end-to-end framework with data-driven batch inference.Cell systems · 2024Article
- Automated single-cell omics end-to-end framework with data-driven batch inference.bioRxiv : the preprint server for biology · 2024Article
- Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer.Nature communications · 2023Article
- Data Mining of Microarray Datasets in Translational Neuroscience.Brain sciences · 2023Review
- Dynamic thresholding and tissue dissociation optimization for CITE-seq identifies differential surface protein abundance in metastatic melanoma.Communications biology · 2023Article
- GRACE: Graph autoencoder based single-cell clustering through ensemble similarity learning.PloS one · 2023Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful technique to decipher tissue composition at the single-cell level and to inform on disease mechanisms, tumor heterogeneity, and the state of the immune microenvironment. Although multiple methods for the computational analysis of scRNA-seq data exist, their application in a clinical setting demands standardized and reproducible workflows, targeted to extract, condense, and display the clinically relevant information. To this end, we designed scAmpi (Single Cell Analysis mRNA pipeline), a workflow that facilitates scRNA-seq analysis from raw read processing to informing on sample composition, clinically relevant gene and pathway alterations, and in silico identification of personalized candidate drug treatments. We demonstrate the value of this workflow for clinical decision making in a molecular tumor board as part of a clinical study.
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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.