Tissues are highly complicated with spatial heterogeneity in gene expression. However, the cutting-edge single-cell RNA-seq technology eliminates the spatial information of individual cells, which contributes to the characterization of cell identities. Zhejiang University researchers have developed a single-cell spatial position ...
Read More »CloneTracer – clonally resolved single-cell multi-omics
Researchers have developed a new method to distinguish between cancerous and healthy stem cells and progenitor cells from samples of patients with acute myeloid leukaemia (AML), a disease...
Read More »BEERS2 – RNA-Seq simulation through high fidelity in silico modeling
Simulation of RNA-seq reads is critical in the assessment, comparison, benchmarking, and development of bioinformatics tools. Yet the field...
Read More »HaploCoV – unsupervised classification and rapid detection of novel emerging variants of SARS-CoV-2
Accurate and timely monitoring of the evolution of SARS-CoV-2 is crucial for identifying and tracking potentially more transmissible/virulent viral variants, and implement mitigation strategies to limit their...
Read More »ZARP – an automated workflow for processing of RNA-seq data
RNA sequencing (RNA-seq) is a crucial technique for many scientific studies and multiple models, and software packages have been developed for the processing and analysis of such data. Given the plethora of available tools, choosing the most appropriate ones is ...
Read More »scANANSE – gene regulatory network and motif analysis of single-cell clusters
The recent development of single-cell techniques is essential to unravel complex biological systems. By measuring the transcriptome and the accessible...
Read More »Single-cell gene set enrichment analysis and transfer learning for functional annotation of scRNA-seq data
Although an essential step, cell functional annotation often proves particularly challenging from single-cell transcriptional data. Several methods have been developed to accomplish this task. However, in most...
Read More »IBRAP – integrated benchmarking single-cell RNA-sequencing analytical pipeline
Single-cell ribonucleic acid (RNA)-sequencing (scRNA-seq) is a powerful tool to study cellular heterogeneity. The high dimensional data...
Read More »DeepMAPS – biological network inference from scMulti-omics
Single-cell multi-omics (scMulti-omics) allows the quantification of multiple modalities simultaneously to capture the intricacy of complex molecular mechanisms and cellular heterogeneity. Existing...
Read More »A guide to gene-centric analysis using TreeSAPP
Gene-centric analysis is commonly used to chart the structure, function, and activity of microbial communities in natural and engineered environments. A common approach is to create...
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