ScRNAbox – empowering single-cell RNA sequencing on high performance computing systems
Single-cell RNA sequencing (scRNAseq) has transformed biology by allowing scientists to study the gene expression…
Browsing: Analysis Pipelines
BigSur – leveraging gene correlations in single cell transcriptomic data
Scientists are using single-cell RNA sequencing (scRNAseq) to push the boundaries of what we can…
pathlinkR – analyze and interpret RNA-Seq results
RNA sequencing (RNA-Seq) is a powerful technique that helps researchers study gene expression, giving them…
scCM – self-supervised contrastive learning method for integrating large-scale CNS scRNA-seq data
The central nervous system (CNS) is incredibly complex, made up of many different types of…
scAMF – single-cell analysis via manifold fitting – a framework for RNA clustering and beyond
Single-cell RNA sequencing (scRNA-seq) has become a vital tool in biology, allowing scientists to study…
scDist – robust identification of perturbed cell types in single-cell RNA-seq data
Single-cell transcriptomics is a powerful technique that allows scientists to study how individual cells behave…
NASC-seq2 – principles of transcription at the resolution of individual bursts
Imagine a factory where products are made in short, intense bursts rather than in a…
METI – deep profiling of tumor ecosystems by integrating cell morphology and spatial transcriptomics
In the ever-evolving field of cancer research, scientists are continuously developing new ways to study…
CDCA – community detection in RNA-seq data using centrality-based approach
When studying complex diseases like schizophrenia and bipolar disorder, understanding how genes interact with each…
scParser – sparse representation learning for scalable single-cell RNA sequencing data analysis
The field of single-cell RNA sequencing (scRNA-seq) has grown rapidly, allowing researchers to explore gene…