A5029305307- Single-cell and spatial transcriptomics
- Cell Image Analysis Techniques
- Extracellular vesicles in disease
- Genomics and Phylogenetic Studies
- Gene expression and cancer classification
- Immune cells in cancer
- Biosensors and Analytical Detection
- Cancer Genomics and Diagnostics
- SARS-CoV-2 detection and testing
- Advanced biosensing and bioanalysis techniques
- Innovative Microfluidic and Catalytic Techniques Innovation
- RNA Research and Splicing
- Electrowetting and Microfluidic Technologies
- Cancer-related molecular mechanisms research
- RNA modifications and cancer
- CRISPR and Genetic Engineering
- 3D Printing in Biomedical Research
- COVID-19 Clinical Research Studies
- Microfluidic and Capillary Electrophoresis Applications
- Smart Agriculture and AI
- SARS-CoV-2 and COVID-19 Research
- Dental Research and COVID-19
- Scientific Computing and Data Management
- Gene Regulatory Network Analysis
- Data Stream Mining Techniques
University of California, Berkeley
2024
California Institute of Technology
2019-2024
Abstract Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in brain 1–3 . With proliferation multi-omics datasets, a major challenge is to validate and integrate results into biological understanding cell-type organization. Here we generated transcriptomes epigenomes from more than 500,000 individual cells mouse primary motor cortex, structure that has an evolutionarily conserved role locomotion. We developed...
Abstract Analysis of single-cell RNA-seq data begins with pre-processing sequencing reads to generate count matrices. We investigate algorithm choices for the challenges pre-processing, and describe a workflow that balances efficiency accuracy. Our is based on kallisto ( https://pachterlab.github.io/kallisto/ ) bustools https://bustools.github.io/ programs, near-optimal in speed memory. The modular, we demonstrate its flexibility by showing how it can be used RNA velocity analyses....
Abstract Full-length SMART-seq 1 single-cell RNA sequencing can be used to measure gene expression at isoform resolution, making possible the identification of specific markers for different cell types. Used in conjunction with spatial capture and gene-tagging methods, this enables inference spatially resolved Here, a comprehensive analysis 6,160 mouse primary motor cortex cells assayed SMART-seq, 280,327 MERFISH 2 94,162 10x Genomics 3 , we find examples specificity types—including shifts...
Abstract Exploratory spatial data analysis (ESDA) can be a powerful approach to understanding single-cell genomics datasets, but it is not yet part of standard workflows. In particular, geospatial analyses, which have been developed and refined for decades, fully adapted applied analysis. We introduce the Voyager platform, systematically brings ESDA tradition (spatial) -omics, with local, bivariate, multivariate methods commonly united by uniform user interface. Using Voyager, we showcase...
Summary Standard single-cell RNA-sequencing analysis (scRNA-seq) workflows consist of converting raw read data into cell-gene count matrices through sequence alignment, followed by analyses including filtering, highly variable gene selection, dimensionality reduction, clustering, and differential expression analysis. Seurat Scanpy are the most widely-used packages implementing such workflows, generally thought to implement individual steps similarly. We investigate in detail algorithms...
Understanding the structure of sequenced fragments from genomics libraries is essential for accurate read preprocessing. Currently, different assays and sequencing technologies require custom scripts programs that do not leverage common sequence elements present in libraries.
Abstract Single cell transcriptomics has transformed the characterization of brain identity by providing quantitative molecular signatures for large, unbiased samples populations. With proliferation taxonomies based on individual datasets, a major challenge is to integrate and validate results toward defining biologically meaningful types. We used battery single-cell transcriptome epigenome measurements generated BRAIN Initiative Cell Census Network (BICCN) comprehensively assess types in...
ABSTRACT The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is due to the high rates transmission by individuals who are asymptomatic at time 1, . Frequent, widespread testing population for SARS-CoV-2 essential suppress viral transmission. Despite increases in capacity, multiple challenges remain deploying traditional reverse transcription and quantitative PCR (RT-qPCR) tests scale required screening individuals. We have developed SwabSeq, a high-throughput...
Single-cell genomics analysis requires normalization of feature counts that stabilizes variance while accounting for variable cell sequencing depth. We discuss some the trade-offs present with current widely used methods, and analyze their performance on 526 single-cell RNA-seq datasets. The results lead us to recommend proportional fitting prior log transformation followed by an additional fitting.
Abstract Motivation Several genomic databases host data and metadata for an ever-growing collection of sequence datasets. While these have a shared hierarchical structure, there are no tools specifically designed to leverage it extraction. Results We present command-line tool, called ffq, querying user-generated from databases. Given accession or paper’s DOI, ffq efficiently fetches links raw in JSON format. ffq’s modularity simplicity make extensible any database exposing its programmatic...
Single-cell RNA-seq technologies have been successfully employed over the past decade to generate many high resolution cell atlases. These proved invaluable in recent efforts aimed at understanding type specificity of host genes involved SARS-CoV-2 infections. While single-cell atlases are based on well-sampled highly-expressed genes, interest for can be expressed very low levels. Common assumptions underlying standard analyses don't hold when examining low-expressed with result that...
Abstract The term “RNA-seq” refers to a collection of assays based on sequencing experiments that involve quantifying RNA species from bulk tissue, single cells, or nuclei. kallisto, bustools, and kb-python programs are free, open-source software tools for performing this analysis together can produce gene expression quantification raw reads. quantifications be individualized multiple samples, both. Additionally, these allow values classified as originating nascent mature species, making...
Abstract As the COVID-19 pandemic worsens in United States [1], colleges that have invited students back for fall are finalizing mitigation plans to lessen spread of SARS-CoV-2. Even though largely been away from campuses over summer, several outbreaks associated with already occurred [2], foreshadowing scale infection could result hundreds thousands returning college towns and cities. While many institutions released return-to-campus designed reduce viral rapidly identify should they occur,...
ABSTRACT We report the generation of a multimodal cell census and atlas mammalian primary motor cortex (MOp or M1) as initial product BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved morphological electrophysiological properties, cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance...
Abstract Understanding the structure of sequenced fragments from genomics libraries is essential for accurate read preprocessing. Currently, different assays and sequencing technologies require custom scripts programs that do not leverage common sequence elements present in libraries. We seqspec , a machine-readable specification produced by facilitates standardization preprocessing enables tracking comparison assays. The associated command line tool available at https://github.com/IGVF/seqspec .
Abstract Cell atlas projects curate representative datasets, cell types, and marker genes for tissues across an organism. Despite their ubiquity, rely on duplicated manual effort to annotate types. The size of atlases coupled with a lack data-compatible tools make reprocessing analysis data near-impossible. To overcome these challenges, we present collection data, algorithms, automate cataloging analyzing types in organism, demonstrate its utility building human atlas.
Abstract We present a command-line tool, called ffq , for querying user-generated data and metadata from sequence databases. The code can be found here: https://github.com/pachterlab/ffq .
Abstract We describe an open source Human Commons Cell Atlas comprising 2.9 million cells across 27 tissues that can be easily updated and is structured to facilitate custom analyses. To showcase the flexibility of atlas, we demonstrate it used study isoforms genes at cell resolution. In particular, type specificity OAS1, which has been shown offer SARS-CoV-2 protection in certain individuals display higher expression p46 isoform. Using our commons atlas localize OAS1 p44b isoform testis,...
Angiotensin-converting enzyme 2 ( ACE2 ) has been identified as a critical receptor for severe acute respiratory syndrome coronavirus (SARS-CoV-2). This led to extensive speculation on the role of in disease severity, and particular, whether variation its expression can explain higher mortality older individuals. We examine this question mouse lung show that 24-month old mice have significantly reduced mRNA relative 3-month mice. The differences appear be localized ciliated cells.
Barcode-based sequence census assays utilize custom or random oligonucloetide sequences to label various biological features, such as cell-surface proteins CRISPR perturbations. These all rely on barcode quantification, a task that is complicated by design and technical noise. We introduce modular approach quantifying barcodes achieves speed memory improvements over existing tools. also set of quality control metrics, accompanying tool, for validating designs.