Lior S. Pachter

The paper introduces meK-Means, a method for clustering cells from multimodal sequencing data by integrating biophysical models of transcription to identify shared cellular states.

This paper uses stochastic biophysical modeling to analyze perturbation data and uncover transcriptional dynamics and kinetic responses in cells.

splitcode is a tool for parsing, interpreting, and editing sequencing reads with synthetic constructs, supporting various sequencing assays.

This paper introduces neural network approximations for solving steady-state distributions in multi-species transcriptional models, enabling efficient inference of biophysical parameters from transcriptomic data.

The paper introduces seqspec, a machine-readable specification for genomics assays to standardize preprocessing and enable tracking and comparison of assays.

The paper introduces algorithms and tools to automate cell type annotation and analysis in cell atlas projects, demonstrating their use in building a human atlas.

The paper presents a Human Commons Cell Atlas with 2.9 million cells across 27 tissues, demonstrating its use in studying OAS1 isoform cell type specificity, particularly locating the p44b isoform in testicular spermatids.

gget elm enables fast, scalable querying of Eukaryotic Linear Motifs from the ELM database using local computations.

The paper introduces a modular approach and quality control metrics for improving barcode quantification in sequence census assays.

The paper develops a mathematical framework to integrate stochasticity in RNA transcription and technical variation in single-cell RNA sequencing using generating functions, applied to simulated and biological data.

The paper describes a universal preprocessing workflow for single-cell genomics data using the cellatlas package.

The paper critiques the use of extreme dimension reduction in single-cell genomics and proposes alternative approaches for more effective biological analysis.

Geospatial exploratory statistics, including local, bivariate and multivariate spatial methods, are packaged for spatial omics behind one interface, with matched R/Bioconductor and Python implementations.

This study shows that a learned motor behavior can recover after chronic disruption of inhibitory circuits, with neuronal activity permanently altered but song recovery possible without relying on learning circuits.

Long-read sequencing of 81 human and mouse samples yields 200,000 full-length transcripts plus a triplet framework that separates promoter choice, splicing and 3' end use across tissues.

The paper identifies androgen receptor-mediated regulation of sexually dimorphic gene expression in the mouse kidney and finds limited conservation in human kidney.

gget provides a command-line tool and Python package for efficient querying of genomic reference databases like Ensembl.

The paper investigates the dynamic interaction between Opa/ZIC and Oc/OTX in regulating head development, finding that Opa and Oc compete for gene regulation in different developmental stages.

The paper introduces a method to discover associations between novel gene isoforms and phenotypes without relying on existing annotations.

This paper introduces a method to improve RNA-seq quantification by expanding the transcriptome reference to include both nascent and mature mRNA and using distinguishing flanking k-mers to enhance mapping accuracy.

The paper introduces a command-line tool called ffq for querying user-generated data and metadata from sequence databases.

The paper introduces Monod, a Python package that integrates single-cell RNA sequencing data using biophysical models of transcription to distinguish biological and technical variation and reveal regulatory processes.

The paper evaluates pseudoalignment for improving read assignment in Ultima Genomics single-cell RNA-seq data, finding it more accurate than standard alignment.

The paper introduces a normalization method for single-cell RNA-seq data that meets three criteria and outperforms existing methods on benchmarks.

The paper curates a database of spatial transcriptomics literature and analyzes trends in experimental techniques, species, tissues, and computational methods.

scvi-tools provides a Python package for probabilistic analysis of single-cell omics data, offering standardized interfaces and extensible tools for various analysis tasks.

The paper develops snATAK for preprocessing single-nucleus chromatin accessibility data and evaluates tradeoffs between multimodal assays.

The paper presents a whole-animal transcriptomic cell atlas of Clytia hemisphaerica using multiplexed scRNA-seq to study cell type plasticity under starvation.

The paper uses full-length single-cell RNA-seq to identify isoform-specific markers in mouse primary motor cortex cells, revealing isoform shifts masked at the gene level.

The paper generates a multimodal cell census and atlas of the mammalian primary motor cortex, revealing a unified molecular genetic landscape and cross-species taxonomy of cell types.