Nature's Method Of The Year ?? Release of gnomAD v3 ?? Gemini AI Model ?? Immune Dictionary ??
Bioinformer Weekly Roundup
Stay Updated with the Latest in Bioinformatics!
Issue: 16 | Date: 8 December 2023
?? 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
The paper presents a new method, Paired-Insertion Counting, for consistently analyzing snATAC-seq feature matrices, overcoming inconsistencies in existing approaches, and includes a probability model to infer latent insertion dynamics from these matrices, even with sparse single-cell data.
?? The first author, Laura D. Martens, has posted a Twitter thread which lays out the main findings from the research.
This study introduces a novel method using human precision-cut lung slices (hPCLS) combined with single-cell RNA sequencing to analyze fibrogenesis and regeneration in human lung tissue, demonstrating its effectiveness in mimicking in vivo conditions of pulmonary fibrosis and offering a platform for targeted antifibrotic drug testing.
?? The corresponding author, Herbert B. Schiller, has posted a Twitter thread describing the motivation and results of the study.
The study presents a new strategy for inferring the phase of rare variant pairs in genes related to recessive diseases, using data from the Genome Aggregation Database, achieving 96% accuracy and providing a public resource to aid in interpreting these variants.
?? The corresponding author, Kaitlin E. Samocha, has posted a Twitter thread diving into the results and technical details.
This research introduces 'Gnocchi', a genomic constraint map for the entire human genome, developed using the largest public genome dataset from gnomAD, which reveals how non-coding regions, despite being less constrained than protein-coding sequences, play a significant role in regulating genes related to human disorders and complex traits.
The study introduces the 'Immune Dictionary', a comprehensive collection of single-cell transcriptomic profiles of immune cells responding to 86 different cytokines, uncovering cell-type-specific responses and new immune cell states, and includes software for analyzing cytokine activities in various immune responses, such as in tumors after immune checkpoint blockade therapy.
This study provides a comprehensive analysis of human embryonic limb development using single-cell and spatial transcriptomics, revealing extensive cell diversification from multipotent progenitors and identifying two distinct waves of muscle development, with insights into muscle stem cell identity and anatomical gene expression patterns related to limb malformations. Cross-species comparison with mice shows significant homology in limb development processes.
?? The second author, Peng He, has posted a Twitter thread presenting the atlas and describing the technical approach used.
The study presents a detailed mouse brain atlas using snRNA-seq and Stereo-seq, mapping 308 cell clusters and 29,655 genes with single-cell resolution. It reveals new astrocyte clusters, region-specific gene expression, and 411 transcription factor regulons with developmental specificity, providing a comprehensive spatial transcriptomic view of the mouse brain.
This study systematically evaluates 14 computational methods for identifying spatially variable genes in spatial transcriptomics, using 60 simulated datasets and 15 real-world datasets. It finds that spatialDE2 generally outperforms others, with Moran's I also showing competitive performance, highlighting the need for more specialized algorithms in this field.
?? The first author, Zhijian Li, has posted a Twitter thread describing the benchmarking approach and discussing the results.
This research evaluates deep learning methods for predicting individual gene expression variations using data from 839 individuals in the ROSMAP study. It identifies a key limitation in current methods' ability to accurately predict the direction of variant effects, suggesting this issue arises from inadequately learned sequence motif grammar and proposes new model training strategies to enhance performance.
??? Latest Tools
Giotto Suite: a multi-scale and technology-agnostic spatial multi-omics analysis ecosystem | bioRxiv
The study introduces Giotto Suite, an open-source, modular software package for analyzing spatial omics data. It offers a flexible data framework within R for integrating various types of spatial omics data, scalable solutions for data analysis and visualization, and supports the development of custom pipelines, enhancing multi-scale, multi-omic data analysis in diverse biological research areas.
领英推荐
The Quartet Data Portal offers access to comprehensive multiomics reference materials and datasets from a unique family quartet, including identical twins, to facilitate research. It provides DNA, RNA, protein, and metabolite references, and tools for analysis and visualization of data, supporting reproducibility and quality control in multiomics research through a collaborative, iterative workflow.
The study introduces cellsnake, a user-friendly and comprehensive workflow for analyzing single-cell RNA sequencing data, designed to address common issues like installation difficulties, functionality limitations, and steep learning curves. It supports advanced features in R and Python, integrates easily into existing workflows for batch analyses, and is accessible through multiple platforms like Bioconda, PyPi, Docker, and GitHub, facilitating streamlined and insightful single-cell data analysis.
?? Community News
The expanded gnomAD database, now including 76,156 whole-genome sequences, enhances the identification of disease-related variants, particularly in non-protein-coding regions of the human genome, by providing a comprehensive resource for distinguishing between harmful and neutral mutations.
Watch Google DeepMind Research Scientist Sebastian Nowozin and Software Engineer Taylor Applebaum use Gemini to read, understand and filter 200,000 scientific papers to extract crucial scientific information.
?? Google have also published a blog post introducing Gemini, detailing its extensive capabilities.
The 2023 Nature Method of the Year highlights advancements in in vitro embryo models, which have enhanced understanding of human embryogenesis, offering insights into early developmental stages and addressing technical and ethical challenges previously limiting research in this area.
?? Educational Corner
The study revisits Mathys et al.'s Alzheimer's disease research, addressing previous limitations in data processing and quality control. By applying best practices in single-nucleus RNA-Seq, the research significantly refined the list of differentially expressed genes, reducing false discoveries in the disease's genetic study.
?? The corresponding author, Nathan G. Skene, has posted a Twitter thread describing the motivation and reasons for the contradictory results.
This paper highlights the importance of 'reanalysis' in scientific research, emphasizing that open science and the facilitation of reanalysis can enhance the reproducibility and replicability of scientific findings.
Having trouble grasping the complexities of large language models like GPT? Explore Brendan Bycroft's interactive visualization tool for a detailed, step-by-step breakdown of how these models function.
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