| Title: |
scDown: A Pipeline for Single-Cell RNA-Seq Downstream Analysis |
| Authors: |
Liang Sun; Qianyi Ma; Chunhui Cai; Maryam Labaf; Ashish Jain; Caroline Dias; Shira Rockowitz; Piotr Sliz |
| Source: |
International Journal of Molecular Sciences ; Volume 26 ; Issue 11 ; Pages: 5297 |
| Publisher Information: |
Multidisciplinary Digital Publishing Institute |
| Publication Year: |
2025 |
| Collection: |
MDPI Open Access Publishing |
| Subject Terms: |
single-cell transcriptomics; cell–cell communication; pseudotime analysis; trajectory analysis; cell proportion difference analysis |
| Description: |
Single-cell transcriptomics data are analyzed using two popular tools, Seurat and Scanpy. Multiple separate tools are used downstream of Seurat and Scanpy cell annotation to study cell differentiation and communication, including cell proportion difference analysis between conditions, pseudotime and trajectory analyses to study cell transition, and cell–cell communication analysis. To automate the integrative cell differentiation and communication analyses of single-cell RNA-seq data, we developed a single-cell RNA-seq downstream analysis pipeline called “scDown”. This R package includes cell proportion difference analysis, cell–cell communication analysis, pseudotime analysis, and RNA velocity analysis. Both Seurat and Scanpy annotated single-cell RNA-seq data are accepted in this pipeline. We applied scDown to a published dataset and identified a unique, previously undiscovered signature of neuronal inflammatory signaling associated with a rare genetic neurodevelopmental disorder. These findings were not identified with a simple implementation of Seurat differential gene expression analysis, illustrating the value of our pipeline in biological discovery. scDown can be broadly utilized in downstream analyses of scRNA-seq data, particularly in rare diseases. |
| Document Type: |
text |
| File Description: |
application/pdf |
| Language: |
English |
| Relation: |
Molecular Genetics and Genomics; https://dx.doi.org/10.3390/ijms26115297 |
| DOI: |
10.3390/ijms26115297 |
| Availability: |
https://doi.org/10.3390/ijms26115297 |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ |
| Accession Number: |
edsbas.54DD6E50 |
| Database: |
BASE |