?FaST & SpatialQC??for Spatial Transcriptomics Data,???nf-core/airrflow: Immune Receptor Workflow, SMC3 in Heart Development??
Bioinformer Weekly Roundup
Stay Updated with the Latest in Bioinformatics!
Issue: 48 | Date: 2 August 2024
?? Welcome to the Bioinformer Weekly Roundup!
In this newsletter, we curate and bring you the most captivating stories, developments, and breakthroughs from the world of bioinformatics. Whether you're a seasoned researcher, a student, or simply curious about the intersection of biology and data science, we've got you covered. Subscribe now to stay ahead in the exciting realm of bioinformatics!
?? Featured Research
SPOP, a protein associated with various cancers, was studied in the context of pancreatic cancer. The research found a significant link between SPOP expression and immune function, suggesting its potential as an immunotherapy biomarker.
This article investigates the role of Notch ligands and receptors in various cancers. It reveals a correlation between these factors and different biological features, clinical stages, and patient survival. The findings suggest potential regulatory functions and synergistic effects in cancer progression.
This research focuses on identifying key biomarkers for targeted therapies in cancer treatment. It validates known drug response biomarkers and identifies new ones, emphasizing genes whose impact spans multiple cancers. The findings suggest that driver mutation patterns could tailor therapeutics for precision medicine.
The research investigates the role of SMC3, a component of the cohesin complex, in cardiac development. Findings reveal that SMC3 mutations are common in CdLS patients with CHD. The study also uncovers a novel role for SMC3 in heart development via the regulation of SE-associated genes.
The study delves into the role of the Dorsal root ganglion (DRG) in Diabetic peripheral neuropathy (DPN). Using single-cell RNA-seq, it identifies eight cell-type populations in DRG and their dynamic interactions. The findings suggest that neurons, satellite glial cells, and Schwann cells play vital roles in DPN progression.
??? Latest Tools
The study introduces a revised workflow for single-cell RNA-sequencing data analysis. It proposes a new feature selection method and a variance stabilization transformation method, both improving downstream clustering analyses. The workflow is implemented in an R package, Piccolo.
Source code is available here.
The study introduces AFProfile, a method that enhances protein complex structure prediction. It refines the input information for AlphaFold-multimer by learning a bias to the MSA representation and performing gradient descent through the AFM network, leading to enhanced predictions.
nf-core/airrflow is a workflow that simplifies the analysis of Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) data. It connects tools from Immcantation and can efficiently process large datasets. The workflow’s applicability is demonstrated through the analysis of immune responses to COVID-19 in a large cohort.
Source code is available here.
ClusterMatch aligns scRNA-seq data at the cluster level. It optimizes resolutions, aligns data in the latent space, and maintains interpretability with marker genes. It’s effective in data integration, cell type annotation, and cross-species/timepoint alignment.
The source code is available here.
FURNA is the first database for experimental RNA structures that provides comprehensive functional annotations. It includes Gene Ontology terms, Enzyme Commission numbers, ligand-binding sites, RNA families, protein-binding motifs, and more. It addresses the need for thorough functional annotations of RNA structures.
Source code is available here.
SpatialQC: automated quality control for spatial transcriptome data | Bioinformatics Oxford Academic
SpatialQC is a one-stop QC pipeline introduced for spatial transcriptomics. It generates comprehensive QC reports and produces clean data interactively. It’s a significant tool for understanding spatial heterogeneity in tissues.
Source code is available here.
Compound-SNE, a method for single-cell omics data analysis, performs a soft alignment of samples in embedding space. It aligns cell-types across samples while preserving local embedding structures, performs visual comparisons between large numbers of samples.
Source code is available here.
The Annotation Vocabulary and Annotation Transformers (AT) enhance protein embeddings and build a new numerical feature space. The model CAMP produces advanced embeddings, and a new sequence alignment-based score is suggested for comparing protein sequences.
Source code is available here.
The AssemblyQC pipeline has been developed for evaluating the quality of genome assemblies. It performs various tasks including file-format validation, contaminant checking, and contiguity measurement. It also provides a comprehensive HTML report with method descriptions, tables, and visualizations.
Source code is available here.
领英推荐
The AI-driven platform, GALILEO, introduces the Molecular-Geometric Deep Learning model, ChemPrint. It uses t-SNE data splitting and adaptive molecular embeddings to enhance predictive capabilities. ChemPrint demonstrated a 46% hit rate in a zero-shot prospective study.
Source code is available here.
The FaST pipeline is a method for analysing high-resolution spatial transcriptomics datasets. It’s compatible with OpenST, seq-scope, and other protocols. It allows full reconstruction of the spatially resolved transcriptome in a short time. It relies on the spateo-release package for RNA segmentation and doesn’t require any imaging procedure for cell segmentation.
Source code is available here.
The Microbial Chemoresistance Knowledgebase (MiCK) is introduced as a comprehensive database cataloging microbial gene sequence associated with chemo resistant cancers. MiCK contains 1.6 million sequences of 29 gene types linked to chemoresistance and drug metabolism.
Source code is available here.
This article talks about a pipeline for the analysis of scRNA-seq data with subsequent deconvolution. It estimates cell type fractions in bulk transcriptome data. It was applied on kidney and brain organoid transcriptome data, it identified relevant cells in both tissues. It could also estimate cell type fractions in other organoids.
Source code is available here.
?? Community News
This article discusses the recent advances in molecular nutrition, focusing on how dietary patterns and pharmaceutical interventions interact with the gut microbiome to manage energy balance and improve metabolic health.
Researchers developed a nanoparticle-based treatment that significantly slowed tumor growth in mice by reactivating dormant metabolic pathways and enhancing melanin production, showing promise for future cancer therapies.
This article discusses a new CRISPR system that repairs RNA breaks in human cells, highlighting its potential for temporary treatments for genetic diseases and advancing RNA biology research.
?? Upcoming Events
This course covers a selection of genomic tools and open resources for exploring plant genomes and answering biological questions. It includes omics data such as genomic, proteomic, and imaging data, and demonstrates how to find relevant data and use public tools for plant genomic data-driven discovery.
This webinar on spatially-resolved transcriptomics will cover the latest technological advances and computational approaches, helping researchers understand spatial gene expression within tissues.
?? Educational Corner
The article introduces the new “treatment_model“ function in the Dyn4cast package, which enhances the estimation of various average treatment effects from randomized controlled experiments using propensity scores.
The Docker Labs GenAI series explores AI developer tools, focusing on improving Dockerfile generation for NPM projects using generative AI and best practices. The series emphasizes open-source collaboration and real-time community engagement.
This tutorial guides you through creating a continuous delivery pipeline for a simple web application using GitHub, AWS Elastic Beanstalk, AWS CodeBuild, and AWS CodePipeline, and is divided into five short modules.
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