Novel methods that combine single cell RNA-seq with CRISPR screens enable high-throughput characterization of transcriptional changes caused by genetic perturbations. Dedicated software is however lacking to annotate CRISPR guide RNA (gRNA) libraries and associate them with single cell transcriptomes. Here, ...
Read More »ORFanage – investigating open reading frames in known and novel transcripts
Researchers at the Johns Hopkins University have developed ORFanage, a system designed to assign open reading frames (ORFs) to both known and novel gene transcripts while maximizing similarity to annotated proteins. The primary intended use...
Read More »CapTrap-Seq – a platform-agnostic and quantitative approach for high-fidelity full-length RNA transcript sequencing
Long-read RNA sequencing is essential to produce accurate and exhaustive annotation of eukaryotic genomes. Despite advancements in throughput and accuracy, achieving reliable end-to-end identification...
Read More »scBalance – a scalable sparse neural network framework for rare cell type annotation of single-cell transcriptome data
Automatic cell type annotation methods are increasingly used in single-cell RNA sequencing (scRNA-seq) analysis due to their fast and precise advantages. However, current methods often fail to...
Read More »scAnno – a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets
Undoubtedly, single-cell RNA sequencing (scRNA-seq) has changed the research landscape by providing insights into heterogeneous, complex and rare cell populations. Given that more such data...
Read More »transXpress – a Snakemake pipeline for streamlined de novo transcriptome assembly and annotation
RNA-seq followed by de novo transcriptome assembly has been a transformative technique in biological research of non-model organisms, but the computational processing of RNA-seq data entails...
Read More »scAnnotate – an automated cell type annotation tool for single-cell RNA-sequencing data
Single-cell RNA-sequencing (scRNA-seq) technology enables researchers to investigate a genome at the cellular level with unprecedented resolution...
Read More »DeepBIO – automated and interpretable deep-learning platform for high-throughput biological sequence functional analysis.
Shandong University researchers have developed DeepBIO, the first-of-its-kind automated and interpretable deep-learning platform for high-throughput biological sequence functional analysis. DeepBIO is a one-stop-shop web service that enables...
Read More »annotate_my_genomes – an easy-to-use pipeline to improve genome annotation and uncover neglected genes by hybrid RNA sequencing
The advancement of hybrid sequencing technologies is increasingly expanding genome assemblies that are often annotated using hybrid sequencing transcriptomics, leading to improved genome characterization..
Read More »Vaeda – computational annotation of doublets in single-cell RNA sequencing data
Single-cell RNA sequencing (scRNA-seq) continues to expand our knowledge by facilitating the study of transcriptional heterogeneity at the level of single...
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