Transcriptome sequencing (RNA-seq) is widely used to detect gene rearrangements and quantitate gene expression in acute lymphoblastic leukemia (ALL)...
Read More »SCExecute – cell barcode-stratified analyses of scRNA-seq data
In single-cell RNA-sequencing (scRNA-seq) data, stratification of sequencing reads by cellular barcode is necessary to study cell specific features. However, apart from gene expression, the analyses of cell...
Read More »scISR – a novel method for single-cell data imputation using subspace regression
Recent advances in biochemistry and single-cell RNA sequencing (scRNA-seq) have allowed us to monitor the biological systems at the single-cell resolution...
Read More »RiboDetector – rapid and accurate identification of ribosomal RNA sequences via deep learning
Advances in transcriptomic and translatomic techniques enable in-depth studies of RNA activity profiles and RNA-based regulatory mechanisms. Ribosomal RNA (rRNA) sequences are highly abundant among cellular RNA, but if the target sequences...
Read More »RNA-combine – a toolkit for comprehensive analyses on transcriptome data from different sequencing platforms
Understanding the transcriptome has become an essential step towards the full interpretation of the biological function of a cell, a tissue or even an organ. Many tools are available for either processing...
Read More »OperonSEQer – a set of machine-learning algorithms with threshold voting for detection of operon pairs using short-read RNA-sequencing data
Operon prediction in prokaryotes is critical not only for understanding the regulation of endogenous gene expression, but also for exogenous targeting of...
Read More »sRNARFTarget – a fast machine-learning-based approach for transcriptome-wide sRNA target prediction
Bacterial small regulatory RNAs (sRNAs) are key regulators of gene expression in many processes related to adaptive responses. A multitude of sRNAs have been identified in many bacterial species...
Read More »splatPop – simulating population scale single-cell RNA sequencing data
Population-scale single-cell RNA sequencing (scRNA-seq) is now viable, enabling finer resolution functional genomics studies and leading to a rush...
Read More »CRISPRroots – on- and off-target assessment of RNA-seq data in CRISPR–Cas9 edited cells
The CRISPR-Cas9 genome editing tool is used to study genomic variants and gene knockouts, and can be combined with transcriptomic analyses to...
Read More »A virtual reality platform to visualize and analyze single-cell RNA sequencing data
Science has the technology to measure the activity of every gene within a single individual cell, and just one experiment can generate thousands of cells...
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