Biology subjects

Eagles, N. J.

Publications and source records attributed to Eagles, N. J..

At least 19 recordsLinked to original sources

bioRxiv2026

Multi-omic spatial mapping of the human habenula defines the molecular and anatomical organization of medial and lateral subregions

The habenula (Hb) is a small epithalamic midline structure critical for reward processing and mood regulation that is implicated in many complex brain disorders, including depression and addiction. The molecular anatomy of the Hb has been well-characterized in model organisms, but little is known about its organization in the human brain, including the transcriptomic and epigenetic signatures of spatially-organized lateral (LHb) and medial (MHb) cell types. Here, we generated a high resolution spatiomolecular map of the human Hb using both multiomic single nucleus sequencing (snMultiome) and spatially-resolved transcriptomics. We measured gene expression and chromatin accessibility across 4 MHb and 5 LHb neuronal cell types as defined by transcriptomic conservation with rodents and zebrafish. We identified cell type-specific molecular specializations related to GABAergic and glutamatergic signaling as well as regulatory relationships between open chromatin regions, transcription factors, and target genes associated with depression and addiction. High resolution spatial transcriptomics identified the anatomical location of heterogeneous LHb subpopulations, including two putative inhibitory populations in the LHb. We further characterized cell-type relationships between Hb neurons and glial subtypes and predicted ligand-receptor interactions between LHb and MHb neurons. Finally, we delineated Hb cell types and spatial domains enriched in genes associated with genetic risk for psychiatric disorders, identifying the strongest enrichment in the MHb. Collectively, the generated data and analyses resolve the spatiomolecular organization of the human Hb and identify molecular-genetic associations with neuropsychiatric disease.

neuroscience↗

bioRxiv2026

Mapping spatially organized molecular and genetic signatures of schizophrenia across multiple scales in human prefrontal cortex

The dorsolateral prefrontal cortex (dlPFC) is central to cognitive dysfunction in schizophrenia (SCZ), yet how molecular changes are organized across cortex remains unclear. Here, we applied complementary spatial transcriptomic approaches spanning laminar domains, microenvironments, and cell types in postmortem human dlPFC. At the laminar level, SCZ-associated transcriptional changes were strongest in glia-enriched domains (layer 1/meninges and white matter), including down-regulation of microglia-associated genes, whereas genetic risk localized to neuronal-rich gray matter. We next analyzed SCZ-linked microenvironments including neuropil, neuronal, perineuronal net, and vascular compartments. Within these, neuronal and synaptic transcriptional changes were most prominent in neuropil, showing down-regulation of activity-dependent synaptic genes and inhibitory neuron markers. At the cellular level, these signals reflected intrinsic alterations localized to cell types. Across analyses, patterns converged on altered BDNF-TrkB signaling and inhibitory circuit dysfunction. Together, our findings highlight spatial scale as a key determinant in resolving neuronal and non-neuronal aspects of SCZ-associated biology.

neuroscience↗

bioRxiv2025

Transcriptional response to chronic long-access fentanyl self-administration in rat habenula and amygdala

Fentanyl is a potent synthetic opioid associated with overdose. However, little is known about fentanyl-induced molecular adaptations in the habenula and amygdala, two brain regions implicated in opioid use and withdrawal. We performed bulk RNA-sequencing in the rat habenula and amygdala to identify transcriptomic changes associated with fentanyl intake. Rats self-administered intravenous saline or fentanyl over 22-24 days. Ninety minutes following the final session, brains were collected for transcriptomic profiling. In Hb, we identified 453 differentially expressed genes (DEGs) between saline and fentanyl rats, with upregulated genes associated with synaptic transmission and ionic conductance. In amygdala, we identified 3,041 fentanyl-associated DEGs with upregulated genes implicated in metabolic and vesicular functions. Downregulated genes in both regions were enriched for extracellular matrix functions. Integration of DEGs with single-cell RNA-sequencing data from rodents and humans revealed that fentanyl DEGs were enriched in specific habenula and amygdala cell type markers. Furthermore, fentanyl downregulated DEGs in amygdala were enriched in genes associated with risk for substance use disorders. Together, we define how fentanyl intake alters transcriptional programs in the rat habenula and amygdala, and we link these changes to specific human cell types and risk genes for neuropsychiatric disorders and addiction.

neuroscience↗

bioRxiv2025

APOE E4 Alzheimer's Risk Converges on an Oligodendrocyte Subtype in the Human Entorhinal Cortex

The entorhinal cortex (ERC) is implicated in early progression of Alzheimers disease (AD). Here we investigated the impact of established biological risk factors for AD, including APOE genotype (E2 versus E4 alleles), sex, and ancestry, on gene expression in the human ERC. We generated paired spatially-resolved transcriptomics (SRT) and single-nucleus RNA sequencing data (snRNA-seq) in postmortem human ERC tissue from middle aged brain donors with no history of AD. APOE-dependent changes in gene expression predominantly mapped to a transcriptionally-defined oligodendrocyte subtype, which varied substantially with ancestry, and suggested differences in oligodendrocyte differentiation and myelination. Integration of SRT and snRNA-seq data identified a common gene expression signature associated with APOE genotype, which we localized to the same oligodendrocyte subtype and a white matter spatial domain. This suggests that AD risk in ERC may be associated with disrupted oligodendrocyte function, potentially contributing to future neurodegeneration. Lay SummaryAlzheimers disease (AD) is a neurodegenerative disorder that accounts for 60-80% dementia cases. Apolipoprotein E (APOE) genotype is the strongest genetic risk factor for AD, and the entorhinal cortex (ERC) is a brain region implicated in its earliest progression. Our study investigated how APOE genotype impacts gene expression in the ERC. We identified genotype-dependent effects on oligodendrocytes with different transcriptional profiles related to maturation that may help explain how APOE genotype mediates its effects on AD risk.

neuroscience↗

bioRxiv2025

Spatiomolecular mapping reveals anatomical organization of heterogeneous cell types in the human nucleus accumbens

The nucleus accumbens (NAc) is a key component of the mesolimbic dopamine system that critically regulates many behaviors related to reward and motivation. The NAc is implicated in several neuropsychiatric disorders, including major depressive disorder, schizophrenia, and substance use disorders. Rodent studies have identified spatial organization of heterogeneous medium spiny neuron (MSN) subtypes across the NAc core and shell, but the extent to which this cellular diversity and spatial organization is conserved in the human brain remains unclear. Here, we generated a spatiomolecular atlas of NAc cell types and spatial domains by integrating spatial transcriptomics and single-nucleus RNA sequencing data from postmortem NAc tissue from 10 neurotypical adult donors. We identified 20 transcriptionally unique cell populations and 8 spatial domains, including specialized D1 islands composed of distinct dopamine receptor 1 (DRD1) MSN subtypes, which were enriched for OPRM1. In contrast to a discrete core vs. shell division, we observed continuous spatial gradients of gene expression across MSN domains, suggesting a more complex organization of DRD1 and DRD2 MSNs. Cross-species comparisons demonstrated conservation of MSN subtypes and spatial features between human, rodent, and nonhuman primate NAc. Genetic enrichment analysis with stratified linkage disequilibrium score regression revealed specific spatial domains associated with risk for psychiatric and addiction-related traits. To investigate this further, we spatially mapped ligand-receptor interactions involving neuropsychiatric risk genes. Finally, we leveraged existing rodent NAc data to identify drug-responsive transcriptional programs and predict their spatial distribution in the human NAc. Collectively, we provide a spatiomolecular framework for understanding the human NAc and its relevance to neuropsychiatric disease.

neuroscience↗

bioRxiv2024

Molecular impact of nicotine and smoking exposure on the developing and adult mouse brain

Maternal smoking during pregnancy (MSDP) is associated with significant cognitive and behavioral effects on offspring. While neurodevelopmental outcomes have been studied for prenatal exposure to nicotine, the main psychoactive component of cigarette smoke, its contribution to MSDP effects has never been explored. Comparing the effects of these substances on molecular signaling in the prenatal and adult brain may provide insights into nicotinic and broader tobacco consequences that are developmental-stage specific or age-independent. Pregnant mice were administered nicotine or exposed to chronic cigarette smoke, and RNA-sequencing was performed on frontal cortices of postnatal day 0 pups born to these mice, as well as on frontal cortices and blood of the adult dams. We identified 1,010 and 4,165 differentially expressed genes (DEGs) in nicotine and smoking-exposed pup brains, respectively (FDR<0.05, Ns = 19 nicotine-exposed vs 23 vehicle-exposed; 46 smoking-exposed vs 49 controls). Prenatal nicotine exposure (PNE) alone was related to dopaminergic synapses and long-term synaptic depression, whereas MSDP was associated with the SNARE complex and vesicle transport. Both substances affected SMN-Sm protein complexes and postsynaptic endosomes. Analyses at the transcript, exon, and exon-exon junction levels supported gene level results and revealed additional smoking-affected processes. No DEGs at FDR<0.05 were found in adult mouse brain for any substance (12 nicotine-administered vs 11 vehicle-administered; 12 smoking-exposed vs 12 controls), nor in adult blood (12 smoking-exposed vs 12 controls), and only 3% and 6.41% of the DEGs in smoking-exposed pup brain replicated in smoking-exposed blood and human prenatal brain, respectively. Together, these results demonstrate variable but overlapping molecular effects of PNE and MSDP on the developing brain, and attenuated effects of both smoking and nicotine on adult versus fetal brain.

neuroscience↗

bioRxiv2024

Integrating gene expression and imaging data across Visium capture areas with visiumStitched

BackgroundVisium is a widely-used spatially-resolved transcriptomics assay available from 10x Genomics. Standard Visium capture areas (6.5mm by 6.5mm) limit the survey of larger tissue structures, but combining overlapping images and associated gene expression data allow for more complex study designs. Current software can handle nested or partial image overlaps, but is designed for merging up to two capture areas, and cannot account for some technical scenarios related to capture area alignment. ResultsWe generated Visium data from a postmortem human tissue sample such that two capture areas were partially overlapping and a third one was adjacent. We developed the R/Bioconductor package visiumStitched, which facilitates stitching the images together with Fiji (ImageJ), and constructing SpatialExperiment R objects with the stitched images and gene expression data. visiumStitched constructs an artificial hexagonal array grid which allows seamless downstream analyses such as spatially-aware clustering without discarding data from overlapping spots. Data stitched with visiumStitched can then be interactively visualized with spatialLIBD. ConclusionsvisiumStitched provides a simple, but flexible framework to handle various multi-capture area study design scenarios. Specifically, it resolves a data processing step without disrupting analysis workflows and without discarding data from overlapping spots. visiumStiched relies on affine transformations by Fiji, which have limitations and are less accurate when aligning against an atlas or other situations. visiumStiched provides an easy-to-use solution which expands possibilities for designing multi-capture area study designs.

genomics↗

bioRxiv2024

Stimulation of locus coeruleus inputs to the frontal cortex in mice induces cell type-specific expression of the Apoe gene

Deficits in attention are common across a range of neuropsychiatric disorders. A multitude of brain regions, including the frontal cortex (FC) and locus coeruleus (LC), have been implicated in attention. Regulators of these brain regions at the molecular level are not well understood, but might elucidate underlying mechanisms of disorders with attentional deficits. To probe this, we used chemogenetic stimulation of neurons in the LC with axonal projections to the FC, and subsequent bulk RNA-sequencing from the mouse FC. We found that stimulation of this circuit caused an increase in transcription of the Apoe gene. To investigate cell type-specific expression of Apoe in the FC, we used a dual-virus approach to express either the excitatory DREADD receptor hM3Dq in LC neurons with projections to the FC, or a control virus, and found that increases in Apoe expression in the FC following depolarization of LC inputs is enriched in GABAergic neurons in a sex-dependent manner. The results of these experiments yield insights into how Apoe expression affects function in cortical microcircuits that are important for attention-guided behavior, and point to interneuron-specific expression of Apoe as a potential target for the amelioration of attention symptoms in disorders such as attention-deficit hyperactivity disorder (ADHD), schizophrenia, and Alzheimers disease (AD). Significance StatementIdentifying patterns of gene expression in specific brain circuits is an important first step toward developing treatments for cognitive and behavioral symptoms that rely on those circuits. In this paper, we describe a transcriptome-scale motif in one such circuit - neurons in the LC that project to the FC. This circuit has been implicated in attention, and attentional deficits are common across many neuropsychiatric disorders, suggesting that targeting this circuit could have therapeutic potential for ameliorating attentional symptoms in these disorders. We further explored one of the top differentially expressed genes, Apoe, to identify how it is expressed in distinct cell types following stimulation of this circuit, paving the way for spatially- and genetically-specific targeting of this gene in attention.

genetics↗

bioRxiv2024

An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus

The hippocampus contains many unique cell types, which serve the structures specialized functions, including learning, memory and cognition. These cells have distinct spatial organization, morphology, physiology, and connectivity, highlighting the importance of transcriptome-wide profiling strategies that retain cytoarchitectural organization. Here, we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the anterior human hippocampus in ten adult neurotypical donors to define molecular profiles for hippocampal cell types and spatial domains. Using non-negative matrix factorization (NMF) and label transfer, we integrated these data by defining gene expression patterns within the snRNA-seq data and inferring their expression in the SRT data. We identified NMF patterns that captured transcriptional variation across neuronal cell types and indicated that the response of excitatory and inhibitory postsynaptic specializations were prioritized in different SRT spatial domains. We used the NMF and label transfer approach to leverage existing rodent datasets, identifying patterns of activity-dependent transcription and subpopulations of dentate gyrus granule cells in our SRT dataset that may be predisposed to participate in learning and memory ensembles. Finally, we characterized the spatial organization of NMF patterns corresponding to non-cornu ammonis pyramidal neurons and identified snRNA-seq clusters mapping to distinct regions of the retrohippocampus, to three subiculum layers, and to a population of presubiculum neurons. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available, including through interactive web applications.

neuroscience↗

bioRxiv2024

Benchmark of cellular deconvolution methods using a multi-assay reference dataset from postmortem human prefrontal cortex

BackgroundCellular deconvolution of bulk RNA-sequencing (RNA-seq) data using single cell or nuclei RNA-seq (sc/snRNA-seq) reference data is an important strategy for estimating cell type composition in heterogeneous tissues, such as human brain. Computational methods for deconvolution have been developed and benchmarked against simulated data, pseudobulked sc/snRNA-seq data, or immunohistochemistry reference data. A major limitation in developing improved deconvolution algorithms has been the lack of integrated datasets with orthogonal measurements of gene expression and estimates of cell type proportions on the same tissue sample. Deconvolution algorithm performance has not yet been evaluated across different RNA extraction methods (cytosolic, nuclear, or whole cell RNA), different library preparation types (mRNA enrichment vs. ribosomal RNA depletion), or with matched single cell reference datasets. ResultsA rich multi-assay dataset was generated in postmortem human dorsolateral prefrontal cortex (DLPFC) from 22 tissue blocks. Assays included spatially-resolved transcriptomics, snRNA-seq, bulk RNA-seq (across six library/extraction RNA-seq combinations), and RNAScope/Immunofluorescence (RNAScope/IF) for six broad cell types. The Mean Ratio method, implemented in the DeconvoBuddies R package, was developed for selecting cell type marker genes. Six computational deconvolution algorithms were evaluated in DLPFC and predicted cell type proportions were compared to orthogonal RNAScope/IF measurements. ConclusionsBisque and hspe were the most accurate methods, were robust to differences in RNA library types and extractions. This multi-assay dataset showed that cell size differences, marker genes differentially quantified across RNA libraries, and cell composition variability in reference snRNA-seq impact the accuracy of current deconvolution methods.

neuroscience↗

bioRxiv2023

Influence of Alzheimer's disease related neuropathology on local microenvironment gene expression in the human inferior temporal cortex

Neuropathological lesions in the brains of individuals affected with neurodegenerative disorders are hypothesized to trigger molecular and cellular processes that disturb homeostasis of local microenvironments. Here, we applied the 10x Genomics Visium Spatial Proteogenomics (Visium-SPG) platform, which measures spatial gene expression coupled with immunofluorescence protein co-detection, in post-mortem human brain tissue from individuals with late-stage Alzheimers disease (AD) to investigate changes in spatial gene expression with respect to amyloid-{beta} (A{beta}) and hyperphosphorylated tau (pTau) pathology. We identified A{beta}-associated transcriptomic signatures in the human inferior temporal cortex (ITC) during late-stage AD, which we further investigated at cellular resolution with combined immunofluorescence and single molecule fluorescent in situ hybridization (smFISH) co-detection technology. We present a workflow for analysis of Visium-SPG data and demonstrate the power of multi-omic profiling to identify spatially-localized changes in molecular dynamics that are linked to pathology in human brain disease. We provide the scientific community with web-based, interactive resources to access the datasets of the spatially resolved AD-related transcriptomes at https://research.libd.org/Visium_SPG_AD/.

neuroscience↗

bioRxiv2023

Genetic and environmental contributions to ancestry differences in gene expression in the human brain

Ancestral differences in genomic variation are determining factors in gene regulation; however, most gene expression studies have been limited to European ancestry samples or adjusted for ancestry to identify ancestry-independent associations. We instead examined the impact of genetic ancestry on gene expression and DNA methylation (DNAm) in admixed African/Black American neurotypical individuals to untangle effects of genetic and environmental factors. Ancestry-associated differentially expressed genes (DEGs), transcripts, and gene networks, while notably not implicating neurons, are enriched for genes related to immune response and vascular tissue and explain up to 26% of heritability for ischemic stroke, 27% of heritability for Parkinsons disease, and 30% of heritability for Alzhemiers disease. Ancestry-associated DEGs also show general enrichment for heritability of diverse immune-related traits but depletion for psychiatric-related traits. The cell-type enrichments and direction of effects vary by brain region. These DEGs are less evolutionarily constrained and are largely explained by genetic variations; roughly 15% are predicted by DNAm variation implicating environmental exposures. We also compared Black and White Americans, confirming most of these ancestry-associated DEGs. Our results highlight how environment and genetic background affect genetic ancestry differences in gene expression in the human brain and affect risk for brain illness. SummaryWe examine the impact of genetic ancestry on gene expression and DNA methylation of admixed African/Black Americans, highlighting how genetic and environmental background affect risk for brain illness.

genetics↗

bioRxiv2023

Integrated single cell and unsupervised spatial transcriptomic analysis defines molecular anatomy of the human dorsolateral prefrontal cortex

The molecular organization of the human neocortex has been historically studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally-defined spatial domains that move beyond classic cytoarchitecture. Here we used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex (DLPFC). Integration with paired single nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we map the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains. Finally, we provide resources for the scientific community to explore these integrated spatial and single cell datasets at research.libd.org/spatialDLPFC/. SummaryGeneration of a molecular neuroanatomical map of the human prefrontal cortex reveals novel spatial domains and cell-cell interactions relevant for psychiatric disease.

neuroscience↗

bioRxiv2023

Performant web-based interactive visualization tool for spatially-resolved transcriptomics experiments

High-resolution and multiplexed imaging techniques are giving us an increasingly detailed observation of a biological system. However, sharing, exploring, and customizing the visualization of large multidimensional images can be a challenge. Here, we introduce Samui, a performant and interactive image visualization tool that runs completely in the web browser. Samui is specifically designed for fast image visualization and annotation and enables users to browse through large images and their selected features within seconds of receiving a link. We demonstrate the broad utility of Samui with images generated with two platforms: Vizgen MERFISH and 10x Genomics Visium Spatial Gene Expression. Samui along with example datasets is available at https://samuibrowser.com.

bioinformatics↗

bioRxiv2022

BiocMAP: A Bioconductor-friendly, GPU-Accelerated Pipeline for Bisulfite-Sequencing Data

BackgroundBisulfite sequencing is a powerful tool for profiling genomic methylation, an epigenetic modification critical in the understanding of cancer, psychiatric disorders, and many other conditions. Raw data generated by whole genome bisulfite sequencing (WGBS) requires several computational steps before it is ready for statistical analysis, and particular care is required to process data in a timely and memory-efficient manner. Alignment to a reference genome is one of the most computationally demanding steps in a WGBS workflow, taking several hours or even days with commonly used WGBS-specific alignment software. This naturally motivates the creation of computational workflows that can utilize GPU-based alignment software to greatly speed up the bottleneck step. In addition, WGBS produces raw data that is large and often unwieldy; a lack of memory-efficient representation of data by existing pipelines renders WGBS impractical or impossible to many researchers. ResultsWe present BiocMAP, a Bioconductor-friendly Methylation Analysis Pipeline consisting of two modules, to address the above concerns. The first module performs computationally-intensive read alignment using Arioc, a GPU-accelerated short-read aligner. The extraction module extracts and merges DNA methylation proportions - the fractions of methylated cytosines across all cells in a sample at a given genomic site. Since GPUs are not always available on the same computing environments where traditional CPU-based analyses are convenient, BiocMAP is split into two modules, with just the alignment module requiring an available GPU. Bioconductor-based output objects in R utilize an on-disk data representation to drastically reduce required main memory and make WGBS projects computationally feasible to more researchers. ConclusionsBiocMAP is implemented using Nextflow and available at http://research.libd.org/BiocMAP/. To enable reproducible analysis across a variety of typical computing environments, BiocMAP can be containerized with Docker or Singularity, and executed locally or with the SLURM or SGE scheduling engines. By providing Bioconductor objects, BiocMAPs output can be integrated with powerful analytical open source software for analyzing methylation data.

bioinformatics↗

bioRxiv2021

Investigating trait variability of gene co-expression network architecture in brain by manipulating genomic signatures of schizophrenia risk

While the role of genomic risk for schizophrenia on brain gene co-expression networks has been described, the patterns of its manifestations are varied and complex. To acquire a deeper understanding of this issue, we implemented a novel approach to network construction by manipulating the RNA-Seq expression input to "integrate" or "remove" the "modulatory" effects of genomic risk for schizophrenia. We created co-expression networks in DLPFC from the adjusted expression input and compared them in terms of gene overlap and connectivity. We used linear regression models to remove variance explained by RNA quality, cell type proportion, age, sex and genetic ancestry. We also created co-expression networks based on the genomic profile of a normative trait, height, as a "negative control"; we also applied the same analytical approach in two independent samples: LIBD Human Brain Repository (HBR) (N=78 brains, European ancestry) and Common Mind Consortium (CMC) (N=116 brains, European ancestry). In addition to direct comparisons, we explored the biological plausibility of the differential gene clusters between co-expression networks by testing them for enrichment in relevant gene ontologies and gene sets of interest (PGC2-CLOZUK GWAS significant loci genes, height GWAS significant loci genes, genes in synaptic ontologies-SynGO and genes of the "druggable genome"). We identify several key aspects of the role of genomic risk for schizophrenia in brain co-expression networks: 1) Variability of co-expression modules with "integration" or "removal" of genomic profiles of complex traits (normal or pathological); 2) Biological plausibility of gene sets represented in the differential co-expression contrasts and potential relevance for illness etiopathogenesis; 3) Non-preferential mapping of schizophrenia GWAS loci genes to network areas apparently influenced by the genomic risk score. Overall, our study supports the notion that genomic risk for schizophrenia has an extensive and non-linear effect on brain gene co-expression networks that possibly manifests as a molecular background for gene-gene, gene-environment interactions that affect various biological pathways.

genomics↗

bioRxiv2021

Electrophysiological measures from human iPSC-derived neurons are associated with schizophrenia clinical status and predict individual cognitive performance

Neurons derived from human induced pluripotent stem cells (hiPSCs) have been used to model basic cellular aspects of neuropsychiatric disorders, but the relationship between the emergent phenotypes and the clinical characteristics of donor individuals has been unclear. We analyzed RNA expression and indices of cellular function in hiPSC-derived neural progenitors and cortical neurons generated from 13 individuals with high polygenic risk scores (PRS) for schizophrenia and a clinical diagnosis of schizophrenia, along with 15 neurotypical individuals with low PRS. We identified electrophysiological measures associated with diagnosis that implicated altered Na+ channel function and GABA-ergic neurotransmission. Importantly, electrophysiological measures predicted cardinal clinical and cognitive features found in these schizophrenia patients. The identification of basic neuronal physiological properties related to core clinical characteristics of illness is a potentially critical step in generating leads for novel therapeutics.

neuroscience↗

bioRxiv2020

SPEAQeasy: a Scalable Pipeline for Expression Analysis and Quantification for R/Bioconductor-powered RNA-seq analyses

RNA sequencing (RNA-seq) is a common and widespread biological assay, and an increasing amount of data is generated with it. In practice, there are a large number of individual steps a researcher must perform before raw RNA-seq reads yield directly valuable information, such as differential gene expression data. Existing software tools are typically specialized, only performing one step-- such as alignment of reads to a reference genome-- of a larger workflow. The demand for a more comprehensive and reproducible workflow has led to the production of a number of publicly available RNA-seq pipelines. However, we have found that most require computational expertise to set up or share among several users, are not actively maintained, or lack features we have found to be important in our own analyses. In response to these concerns, we have developed a Scalable Pipeline for Expression Analysis and Quantification (SPEAQeasy), which is easy to install and share, and provides a bridge towards R/Bioconductor downstream analysis solutions. SPEAQeasy is user-friendly and lowers the computational-domain entry barrier for biologists and clinicians to RNA-seq data processing as the main input file is a table with sample names and their corresponding FASTQ files. SPEAQeasy is portable across computational frameworks (SGE, SLURM, local, docker integration) and different configuration files are provided.

bioinformatics↗