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Single cell RNA-seq denoising using a deep count autoencoder
[article]
2018
bioRxiv
pre-print
Single-cell RNA sequencing (scRNA-seq) has enabled researchers to study gene expression at a cellular resolution. However, noise due to amplification and dropout may obstruct analyses, so scalable denoising methods for increasingly large but sparse scRNAseq data are needed. We propose a deep count autoencoder network (DCA) to denoise scRNA-seq datasets. DCA takes the count distribution, overdispersion and sparsity of the data into account using a zero-inflated negative binomial noise model, and
doi:10.1101/300681
fatcat:vw4m5vbdirctlbf7vamlq6na5i
more »
... nonlinear gene-gene or gene-dispersion interactions are captured. Our method scales linearly with the number of cells and can therefore be applied to datasets of millions of cells. We demonstrate that DCA denoising improves a diverse set of typical scRNA-seq data analyses using simulated and real datasets. DCA outperforms existing methods for data imputation in quality and speed, enhancing biological discovery.
Single-cell multimodal profiling of proteins and chromatin accessibility using PHAGE-ATAC
[article]
2020
bioRxiv
pre-print
Multi-modal measurements of single cell profiles are a powerful tool for characterizing cell states and regulatory mechanisms. While current methods allow profiling of RNA along with either chromatin or protein levels, connecting chromatin state to protein levels remains a barrier. Here, we developed PHAGE-ATAC, a method that uses engineered camelid single-domain antibody ('nanobody')-displaying phages for simultaneous single-cell measurement of surface proteins, chromatin accessibility
doi:10.1101/2020.10.01.322420
fatcat:wt3x2ka52rfpfo7azp2t65hjw4
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... , and mtDNA-based clonal tracing through a massively parallel droplet-based assay of single-cell transposase-accessible chromatin with sequencing (ATAC-seq). We demonstrate PHAGE-ATAC for multimodal analysis in primary human immune cells and for sample multiplexing. Finally, we construct a synthetic high-complexity phage library for selection of novel antigen-specific nanobodies that bind cells of particular molecular profiles, opening a new avenue for protein detection, cell characterization and screening with single-cell genomics.
DeepWAS: Directly integrating regulatory information into GWAS using deep learning supports master regulator MEF2C as risk factor for major depressive disorder
[article]
2016
bioRxiv
pre-print
Genome-wide association studies (GWAS) identify genetic variants predictive of common diseases but this does not directly inform on molecular mechanisms. The recently developed deep learning-based method DeepSEA uses DNA sequences to predict regulatory effects for up to 1000 functional units, namely regulatory elements and chromatin features in specific cell-types from the ENCODE project. Results: We here describe "DeepWAS", a conceptually new GWAS approach that integrates these predictions to
doi:10.1101/069096
fatcat:d4x2x4wfs5c33moigcqw7frcjq
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... dentify SNP sets per functional units prior to association analysis based on multiple regression. To test the power of this approach, we use genotype data from a major depressive disorder (MDD) case/control sample (total N=1,537). DeepWAS identified 177 regulatory SNPs moderating 122 functional units. MDD regulatory SNPs were located mostly in promoters, intronic and distal intergenic regions and validated with public data. Blood regulatory SNPs were experimentally annotated with methylation quantitative trait loci (QTLs), expression quantitative trait methylation loci and expression QTLs and replicated in an independent cohort. Joint integrative analysis of regulatory SNPs and the independently identified annotations were connected through transcription factors MEF2A, MEF2C and ATF2, regulating a network of transcripts previously linked to other psychiatric disorders. In the latest GWAS for MDD, the MEF2C gene itself is within the top genome-wide significant locus. Conclusions: DeepWAS is a novel concept with the power to directly identify individual regulatory SNPs from genotypes. In a proof of concept study, MEF2C was identified as a master-regulator in major depression, a finding complementary to recent depression GWAS data, underlining the power of DeepWAS.
High-definition spatial transcriptomics for in situ tissue profiling
2019
Nature Methods
Spatial and molecular characteristics determine tissue function, yet high-resolution methods to capture both concurrently are lacking. Here, we developed high-definition spatial transcriptomics, which captures RNA from histological tissue sections on a dense, spatially barcoded bead array. Each experiment recovers several hundred thousand transcript-coupled spatial barcodes at 2-μm resolution, as demonstrated in mouse brain and primary breast cancer. This opens the way to high-resolution spatial analysis of cells and tissues.
doi:10.1038/s41592-019-0548-y
pmid:31501547
pmcid:PMC6765407
fatcat:6ykhycsyz5hmxhnhiwqe7s6kyu
Myocyte Specific Upregulation of ACE2 in Cardiovascular Disease: Implications for SARS-CoV-2 mediated myocarditis
[article]
2020
biorxiv/medrxiv
Coronavirus disease 2019 (COVID-19) is a global pandemic caused by a novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). SARS-CoV-2 infection of host cells occurs predominantly via binding of the viral surface spike protein to the human angiotensin-converting enzyme 2 (ACE2) receptor. Hypertension and pre-existing cardiovascular disease are risk factors for morbidity from COVID-19, and it remains uncertain whether the use of angiotensin converting enzyme inhibitors (ACEi) or
doi:10.1101/2020.04.09.20059204
pmid:32511660
pmcid:PMC7277016
fatcat:6pfqemhcybdavnky64wszwuct4
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... otensin receptor blockers (ARB) impacts infection and disease. Here, we aim to shed light on this question by assessing ACE2 expression in normal and diseased human myocardial samples profiled by bulk and single nucleus RNA-seq.
ECLIPSER: identifying causal cell types and genes for complex traits through single cell enrichment of e/sQTL-mapped genes in GWAS loci
[article]
2021
bioRxiv
pre-print
The application of ECLIPSER to additional complex diseases and traits and 8 snRNA-seq GTEx tissues can be found in (Eraslan et al., 2021) . Figure 1 . ...
assessing cell type-specific GWAS loci enrichment compared to a permutation-based approach (details in Supplementary Note Section D), using snRNA-seq of 8 GTEx tissues and 21 relevant complex traits (Eraslan ...
doi:10.1101/2021.11.24.469720
fatcat:3ul3dmmtmna7lm4ay54vmsremy
Single Cell, Single Nucleus and Spatial RNA Sequencing of the Human Liver Identifies Hepatic Stellate Cell and Cholangiocyte Heterogeneity
[article]
2021
bioRxiv
pre-print
The critical functions of the human liver are coordinated through the interactions of hepatic parenchymal and non-parenchymal cells. Recent advances in single cell transcriptional approaches have enabled an examination of the human liver with unprecedented resolution. However, dissociation related cell perturbation can limit the ability to fully capture the human liver's parenchymal cell fraction, which limits the ability to comprehensively profile this organ. Here, we report the
doi:10.1101/2021.03.27.436882
fatcat:bwfipihdk5bd5mj3iswkrcanzu
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... landscape of 73,295 cells from the human liver using matched single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq). The addition of snRNA-seq enabled the characterization of interzonal hepatocytes at single-cell resolution, revealed the presence of rare subtypes of hepatic stellate cells previously only seen in disease, and detection of cholangiocyte progenitors that had only been observed during in vitro differentiation experiments. However, T and B lymphocytes and NK cells were only distinguishable using scRNA-seq, highlighting the importance of applying both technologies to obtain a complete map of tissue-resident cell-types. We validated the distinct spatial distribution of the hepatocyte, cholangiocyte and stellate cell populations by an independent spatial transcriptomics dataset and immunohistochemistry. Our study provides a systematic comparison of the transcriptomes captured by scRNA-seq and snRNA-seq and delivers a high-resolution map of the parenchymal cell populations in the healthy human liver.
Single‐Cell, Single‐Nucleus, and Spatial RNA Sequencing of the Human Liver Identifies Cholangiocyte and Mesenchymal Heterogeneity
2021
Hepatology Communications
The critical functions of the human liver are coordinated through the interactions of hepatic parenchymal and non-parenchymal cells. Recent advances in single-cell transcriptional approaches have enabled an examination of the human liver with unprecedented resolution. However, dissociation-related cell perturbation can limit the ability to fully capture the human liver's parenchymal cell fraction, which limits the ability to comprehensively profile this organ. Here, we report the
doi:10.1002/hep4.1854
pmid:34792289
pmcid:PMC8948611
fatcat:t7txnec7pfbbnj5p34iowa3kou
more »
... landscape of 73,295 cells from the human liver using matched single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq). The addition of snRNA-seq enabled the characterization of interzonal hepatocytes at a single-cell resolution, revealed the presence of rare subtypes of liver mesenchymal cells, and facilitated the detection of cholangiocyte progenitors that had only been observed during in vitro differentiation experiments. However, T and B lymphocytes and natural killer cells were only distinguishable using scRNA-seq, highlighting the importance of applying both technologies to obtain a complete map of tissue-resident cell types. We validated the distinct spatial distribution of the hepatocyte, cholangiocyte, and mesenchymal cell populations by an independent spatial transcriptomics data set and immunohistochemistry. Conclusion: Our study provides a systematic comparison of the transcriptomes captured by scRNA-seq and snRNA-seq and delivers a high-resolution map of the parenchymal cell populations in the healthy human liver.
DeepWAS: Multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning
2020
PLoS Computational Biology
Genome-wide association studies (GWAS) identify genetic variants associated with traits or diseases. GWAS never directly link variants to regulatory mechanisms. Instead, the functional annotation of variants is typically inferred by post hoc analyses. A specific class of deep learning-based methods allows for the prediction of regulatory effects per variant on several cell type-specific chromatin features. We here describe "DeepWAS", a new approach that integrates these regulatory effect
doi:10.1371/journal.pcbi.1007616
pmid:32012148
pmcid:PMC7043350
fatcat:eyjwxczrarhwjij3kuygaev25y
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... ions of single variants into a multivariate GWAS setting. Thereby, single variants associated with a trait or disease are directly coupled to their impact on a chromatin feature in a cell type. Up to 61 regulatory SNPs, called dSNPs, were associated with multiple sclerosis (MS, 4,888 cases and 10,395 controls), major depressive disorder (MDD, 1,475 cases and 2,144 controls), and height (5,974 individuals). These variants were mainly non-coding and reached at least nominal significance in classical GWAS. The prediction accuracy was higher for DeepWAS than for classical GWAS models for 91% of the genome-wide significant, MS-specific dSNPs. DSNPs were enriched in public or cohort-matched expression and methylation quantitative trait loci and we demonstrated the potential of DeepWAS to generate testable functional hypotheses based on genotype data alone. DeepWAS is available at https://github.com/cellmapslab/DeepWAS.
Variably methylated regions in the newborn epigenome: environmental, genetic and combined influences
[article]
2018
bioRxiv
pre-print
Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. We examined the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs), defined as consecutive CpGs
doi:10.1101/436113
fatcat:q35ifj6rhjau7mmestam37ufpq
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... the highest variability of DNAm in 4 independent cohorts (PREDO, DCHS, UCI, MoBa, N=2,934). Results: We used Akaike's information criterion to test which factors best explained variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E) including maternal demographic, psychosocial and metabolism related phenotypes, genotypes in cis (G), or their additive (G+E) or interaction (GxE) effects. G+E and GxE models consistently best explained variability in DNAm of VMRs across the cohorts, with G explaining the remaining sites best. VMRs best explained by G, GxE or G+E, as well as their associated functional genetic variants (predicted using deep learning algorithms), were located in distinct genomic regions, with different enrichments for transcription and enhancer marks. Genetic variants of not only G and G+E models, but also of variants in GxE models were significantly enriched in genome wide association studies (GWAS) for complex disorders. Conclusion: Genetic and environmental factors in combination best explain DNAm at VMRs. The CpGs best explained by G, G+E or GxE are functionally distinct. The enrichment of GxE variants in GWAS for complex disorders supports their importance for disease risk.
Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns
2019
Nature Communications
Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts
doi:10.1038/s41467-019-10461-0
pmid:31186427
pmcid:PMC6559955
fatcat:hrrz4q6tafhghkxm4naltkxilm
more »
... l n = 2365). We use Akaike's information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk.
Bugünü Geçmişten Değerlendirebilmek İçin Bir Kitap: Türkiye'de Kitle İletişimi: Dün-Bugün-Yarın
2018
Etkileşim
Gökçen Demirel, "Demokrat Parti ve Radyo"; Muammer Aksoy, "Partizan Radyo".Kitabın 'Dün' başlıklı kısmının son dönemi ise,1960-1980 arasını kapsar. 1960 darbesinin ardından yapılan anayasa, kitle iletişim ...
; Ruhdan Uzun, "Basında Dağıtım", "Spor Basını" ve "Basında Etik"; Gül Karagöz-Kızılca, "Resmi-Özel İlanlar ve Basın İlan Kurumu"; Aslıhan Ardıç Çobaner, "Güneş'in Doğuşu ve Batışı"; Hülya Eraslan, "Türkçe ...
doi:10.32739/etkilesim.2018.1.18
fatcat:x2shdxdkejaazpvqa5w73pghfq
starfish: scalable pipelines for image-based transcriptomics
2021
Journal of Open Source Software
For direct contributions of code and documentation, we thank Olga Botvinnik, Gökçen Eraslan, Kira Evans, Marcus Kinsella, Nicholas Mei, Josh Moore, Nicholas Sofroniew, and Ola Tarkowska. ...
doi:10.21105/joss.02440
fatcat:hbs2liwjg5d5tiv4mnsndcbobq
Protein structure prediction using AI and quantum computers
[article]
2021
bioRxiv
pre-print
Eraslan, Gökcen, Žiga Avsec, Julien Gagneur, and Fabian J. Theis. "Deep learning: new computational modelling techniques for genomics." Nature Reviews Genetics 20, no. 7 (2019): 389-403. 7. ...
doi:10.1101/2021.05.22.445242
fatcat:q2ggwbnqy5eafm6tf3o4nh3t5a
Ahmed Yesevi Bibliyografyası: Türkiye'de Yesevi İle İlgili Çalışmalara Dair Değe
2016
Turkish Studies
Uslu, Mustafa, Pir-i Türkistan Hoca Ahmet Yesevi, Yozgat Gökçen Yayınları, 1997. Uslu, Recep, Selçuklu Topraklarında Müzik (Hoca Ahmed Yesevi'den Hz. ...
Kemal Eraslan, Ankara Kültür ve Turizm Bakanlığı Başbakanlık Basımevi, 1983. ...
doi:10.7827/turkishstudies.10109
fatcat:grm5j4jli5exbfyv4jljxsrtje
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