Biology subjects

Haugen, E.

Publications and source records attributed to Haugen, E..

7 recordsLinked to original sources

bioRxiv2026

TRaP: An Open-source, Reproducible Framework for Raman Spectral Preprocessing across Heterogeneous Systems

Raman spectroscopy offers a uniquely rich window into molecular structure and composition, making it a powerful tool across fields ranging from materials science to biology. However, the reproducibility of Raman data analysis remains a fundamental bottleneck. In practice, transforming raw spectra into meaningful results is far from standardized: workflows are often complex, fragmented, and implemented through highly customized, case-specific code. This challenge is compounded by the lack of unified open-source pipelines and the diversity of acquisition systems, each introducing its own file formats, calibration schemes, and correction requirements. Consequently, researchers must frequently rely on manual, ad hoc reconciliation of processing steps. To address this gap, we introduce TRaP (Toolbox for Reproducible Raman Processing), an open-source, GUI-based Python toolkit designed to bring reproducibility, transparency, and portability to Raman spectral analysis. TRaP unifies the entire preprocessing-to-analysis pipeline within a single, coherent framework that operates consistently across heterogeneous instrument platforms (e.g., Clinical Fiber-optic Raman System, Commercial Portable System and Commercial Raman Microscope). Central to its design is the concept of fully shareable, declarative workflows: users can encode complete processing pipelines into a single configuration file (e.g., JSON), enabling others to reproduce results instantly without reimplementing code or reverse-engineering undocumented steps. Beyond convenience, TRaP integrates configuration management, X-axis calibration, spectral response correction, interactive processing, and batch execution into a workflow-driven architecture that enforces deterministic, repeatable operations. Every transformation is explicitly recorded, making the full processing history transparent, inspectable, and reproducible. This eliminates ambiguity in how results are generated and ensures that identical protocols can be applied consistently across datasets and experimental contexts. Through representative use cases, we show that TRaP enables seamless, reproducible preprocessing of Raman spectra acquired from diverse platforms within a unified environment. We hope TRaP can empower Raman data processing as a reproducible, shareable, and systematized scientific practice, aligning it with modern standards for computational research. TRaP is released as an open-source software at https://github.com/hrlblab/TRaP

bioengineering↗

bioRxiv2022

FORGEdb: systematic analysis of candidate causal variants to uncover target genes and mechanisms in complex traits.

The majority of disease-associated variants identified through genome-wide association studies (GWAS) are located outside of protein-coding regions and are overrepresented in sequences that regulate gene expression. Prioritizing candidate regulatory variants and potential biological mechanisms for further functional experiments, such as genome editing, can be challenging, especially in regions with a high number of variants in strong linkage disequilibrium or multiple proximal gene targets. Improved annotation of the regulatory genome can help identify promising variants and target genes for functional genomics experiments. To advance this area, we developed FORGEdb (https://forge2.altiusinstitute.org/files/forgedb.html), a web-based tool that can rapidly integrate data for individual genetic variants, providing information on associated regulatory elements, transcription factor (TF) binding sites and target genes for over 37 million variants. FORGEdb uses annotations derived from data across a wide range of biological samples to delineate the regulatory context for each variant at the cell type level. Multiple data types, such as Combined Annotation Dependent Depletion (CADD) scores, expression quantitative trait loci (eQTLs), activity-by-contact (ABC) interactions, Contextual Analysis of TF Occupancy (CATO) scores, transcription factor (TF) motifs, DNase I hotspots, histone mark ChIP-seq peaks and chromatin states, are included in FORGEdb and these annotations are integrated into a FORGEdb score to guide assessment of functional importance. In summary, FORGEdb provides an expansive and unique resource of genomic annotations and an integrated score that can be used to accelerate the translation of identified genetic loci into biological insight.

genomics↗

bioRxiv2021

Differences in nanoscale organization of DNase I hypersensitive and insensitive chromatin in single human cells

Methodological advances in conformation capture techniques have fundamentally changed our understanding of chromatin architecture. However, the nanoscale organization of chromatin and its cell-to-cell variance are less studied. By using a combination of high throughput super-resolution microscopy and coarse-grained modelling we investigated properties of active and inactive chromatin in interphase nuclei. Using DNase I hypersensitivity as a criterion, we have selected prototypic active and inactive regions from ENCODE data that are representative for K-562 and more than 150 other cell types. By using oligoFISH and automated STED microscopy we systematically measured physical distances of the endpoints of 5kb DNA segments in these regions. These measurements result in high-resolution distance distributions which are right-tailed and range from very compact to almost elongated configurations of more than 200 nm length for both the active and inactive regions. Coarse-grained modeling of the respective DNA segments suggests that in regions with high DNase I hypersensitivity cell-to-cell differences in nucleosome occupancy determine the histogram shape. Simulations of the inactive region cannot sufficiently describe the compaction measured by microscopy, although internucleosomal interactions were elevated and the linker histone H1 was included in the model. These findings hint at further organizational mechanisms while the microscopy-based distance distribution indicates high cell-to-cell differences also in inactive chromatin regions. The analysis of the distance distributions suggests that direct enhancer-promoter contacts, which most models of enhancer action assume, happen for proximal regulatory elements in a probabilistic manner due to chromatin flexibility.

cell biology↗

bioRxiv2020

Atlas and developmental dynamics of mouse DNase I hypersensitive sites

Early mammalian development is orchestrated by genome-encoded regulatory elements populated by a changing complement of regulatory factors, creating a dynamic chromatin landscape. To define the spatiotemporal organization of regulatory DNA landscapes during mouse development and maturation, we generated nucleotide-resolution DNA accessibility maps from 15 tissues sampled at 9 intervals spanning post-conception day 9.5 through early adult, and integrated these with 41 adult-stage DNase-seq profiles to create a global atlas of mouse regulatory DNA. Collectively, we delineated >1.8 million DNase I hypersensitive sites (DHSs), with the vast majority displaying temporal and tissue-selective patterning. Here we show that tissue regulatory DNA compartments show sharp embryonic-to-fetal transitions characterized by wholesale turnover of DHSs and progressive domination by a diminishing number of transcription factors. We show further that aligning mouse and human fetal development on a regulatory axis exposes disease-associated variation enriched in early intervals lacking human samples. Our results provide an expansive new resource for decoding mammalian developmental regulatory programs.

genomics↗

bioRxiv2020

Global reference mapping and dynamics of human transcription factor footprints

Combinatorial binding of transcription factors to regulatory DNA underpins gene regulation in all organisms. Genetic variation in regulatory regions has been connected with diseases and diverse phenotypic traits1, yet it remains challenging to distinguish variants that impact regulatory function2. Genomic DNase I footprinting enables quantitative, nucleotide-resolution delineation of sites of transcription factor occupancy within native chromatin3-5. However, to date only a small fraction of such sites have been precisely resolved on the human genome sequence5. To enable comprehensive mapping of transcription factor footprints, we produced high-density DNase I cleavage maps from 243 human cell and tissue types and states and integrated these data to delineate at nucleotide resolution ~4.5 million compact genomic elements encoding transcription factor occupancy. We map the fine-scale structure of ~1.6 million DHS and show that the overwhelming majority is populated by well-spaced sites of single transcription factor:DNA interaction. Cell context-dependent cis-regulation is chiefly executed by wholesale actuation of accessibility at regulatory DNA versus by differential transcription factor occupancy within accessible elements. We show further that the well-described enrichment of disease- and phenotypic trait-associated genetic variants in regulatory regions1,6 is almost entirely attributable to variants localizing within footprints, and that functional variants impacting transcription factor occupancy are nearly evenly partitioned between loss- and gain-of-function alleles. Unexpectedly, we find that the global density of human genetic variation is markedly increased within transcription factor footprints, revealing an unappreciated driver of cis-regulatory evolution. Our results provide a new framework for both global and nucleotide-precision analyses of gene regulatory mechanisms and functional genetic variation.

genomics↗

bioRxiv2019

Index and biological spectrum of accessible DNA elements in the human genome

DNase I hypersensitive sites (DHSs) are generic markers of regulatory DNA and harbor disease- and phenotypic trait-associated genetic variation. We established high-precision maps of DNase I hypersensitive sites from 733 human biosamples encompassing 439 cell and tissue types and states, and integrated these to precisely delineate and numerically index ~3.6 million DHSs encoded within the human genome, providing a common coordinate system for regulatory DNA. Here we show that the expansive scale of cell and tissue states sampled exposes an unprecedented degree of stereotyped actuation of large sets of elements, signaling the operation of distinct genome-scale regulatory programs. We show further that the complex actuation patterns of individual elements can be captured comprehensively by a simple regulatory vocabulary reflecting their dominant cellular manifestation. This vocabulary, in turn, enables comprehensive and quantitative regulatory annotation of both protein-coding genes and the vast array of well-defined but poorly-characterized non-coding RNA genes. Finally, we show that the combination of high-precision DHSs and regulatory vocabularies markedly concentrate disease- and trait-associated non-coding genetic signals both along the genome and across cellular compartments. Taken together, our results provide a common and extensible coordinate system and vocabulary for human regulatory DNA, and a new global perspective on the architecture of human gene regulation.

genomics↗

bioRxiv2018

Cryptic Promoter Activation Drives POU5F1 (OCT4) Expression in Renal Cell Carcinoma

Transcriptional dysregulation drives cancer formation but the underlying mechanisms are still poorly understood. As a model system, we used renal cell carcinoma (RCC), the most common malignant kidney tumor which canonically activates the hypoxia-inducible transcription factor (HIF) pathway. We performed genome-wide chromatin accessibility and transcriptome profiling on paired tumor/normal samples and found that numerous transcription factors with a RCC-selective expression pattern also demonstrated evidence of HIF binding in the vicinity of their gene body. Some of these transcription factors influenced the tumors regulatory landscape, notably the stem cell transcription factor POU5F1 (OCT4). Unexpectedly, we discovered a HIF-pathway-responsive cryptic promoter embedded within a human-specific retroviral repeat element that drives POU5F1 expression in RCC via a novel transcript. Elevat POU5F1 expression levels were correlated with advanced tumor stage and poorer overall survival in RCC patients. Thus, integrated transcriptomic and epigenomic analysis of even a small number of primary patient samples revealed remarkably convergent shared regulatory landscapes and a novel mechanism for dysregulated expression of POU5F1 in RCC.

cancer biology↗