METAFlux – infer metabolic fluxes from bulk or single-cell transcriptomic data
Cells often alter metabolic strategies under nutrient-deprived conditions to support their survival and growth. Characterizing…
Browsing: Analysis Pipelines
MSIQ -joint modeling of multiple RNA-seq samples for accurate isoform quantification
Next-generation RNA sequencing (RNA-seq) technology has been widely used to assess full-length RNA isoform abundance…
sccomp – robust differential composition and variability analysis for single-cell data
Cellular omics such as single-cell genomics, proteomics, and microbiomics allow the characterization of tissue and…
contrastiveVI – isolating salient variations of interest in single-cell data
Single-cell datasets are routinely collected to investigate changes in cellular state between control cells and…
NanopoReaTA – a user-friendly tool for nanopore-seq real-time transcriptional analysis
Oxford Nanopore Technologies’ (ONT) sequencing platform offers an excellent opportunity to perform real-time analysis during…
Dana-Farber AI-model predicts primary source of cancer using gene sequencing data
Researchers at Dana-Farber Cancer Institute have created an AI-based tool that uses tumor gene sequencing…
Mandalorion – identifying and quantifying isoforms from accurate full-length transcriptome sequencing reads
Researchers from the University of California Santa Cruz have developed and benchmarked Mandalorion v4.1 for…
RNAseqChef – a web-based integrative transcriptome analysis to automatically detect, integrate, and visualize differentially expressed genes and their biological functions
RNA sequencing (RNA-seq) is a powerful technique for understanding cellular state and dynamics. However, comprehensive…
LRT – Integrative analysis of scRNA-seq and scTCR-seq data to investigate clonal differentiation heterogeneity
Single-cell RNA sequencing (scRNA-seq) data has been widely used for cell trajectory inference, with the…
Novel algorithm able to detect mutations in single-cell sequencing data sets
Being able to characterise somatic mutations at single-cell resolution is essential for understanding cancer evolution…