The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Stephanie A. Christenson - One of the best experts on this subject based on the ideXlab platform.
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rop Dumpster Diving in rna sequencing to find the source of 1 trillion reads across diverse adult human tissues
Genome Biology, 2018Co-Authors: Serghei Mangul, Harry Taegyun Yang, Nicolas Strauli, Franziska Gruhl, Timothy Daley, Hagit T Porath, Kevin Hsieh, Linus Chen, Stephanie A. ChristensonAbstract:High-throughput RNA-sequencing (RNA-seq) technologies provide an unprecedented opportunity to explore the individual transcriptome. Unmapped reads are a large and often overlooked output of standard RNA-seq analyses. Here, we present Read Origin Protocol (ROP), a tool for discovering the source of all reads originating from complex RNA molecules. We apply ROP to samples across 2630 individuals from 54 diverse human tissues. Our approach can account for 99.9% of 1 trillion reads of various read length. Additionally, we use ROP to investigate the functional mechanisms underlying connections between the immune system, microbiome, and disease. ROP is freely available at https://github.com/smangul1/rop/wiki .
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Dumpster Diving in RNA-sequencing to find the source of every last read
bioRxiv, 2016Co-Authors: Serghei Mangul, Harry Taegyun Yang, Nicolas Strauli, Franziska Gruhl, Timothy Daley, Stephanie A. Christenson, Agata Wesolowska-andersen, Roberto Spreafico, Cydney Rios, Celeste EngAbstract:High throughput RNA sequencing technologies have provided invaluable research opportunities across distinct scientific domains by producing quantitative readouts of the transcriptional activity of both entire cellular populations and single cells. The majority of RNA-Seq analyses begin by mapping each experimentally produced sequence (i.e., read) to a set of annotated reference sequences for the organism of interest. For both biological and technical reasons, a significant fraction of reads remains unmapped. In this work, we develop Read Origin Protocol (ROP) to discover the source of all reads originating from complex RNA molecules, recombinant T and B cell receptors, and microbial communities. We applied ROP to 8,641 samples across 630 individuals from 54 tissues. A fraction of RNA-Seq data (n=86) was obtained in-house; the remaining data was obtained from the Genotype-Tissue Expression (GTEx v6) project. To generalize the reported number of accounted reads, we also performed ROP analysis on thousands of different, randomly selected, and publicly available RNA-Seq samples in the Sequence Read Archive (SRA). Our approach can account for 99.9% of 1 trillion reads of various read length across the merged dataset (n=10641). Using in-house RNA-Seq data, we show that immune profiles of asthmatic individuals are significantly different from the profiles of control individuals, with decreased average per sample T and B cell receptor diversity. We also show that immune diversity is inversely correlated with microbial load. Our results demonstrate the potential of ROP to exploit unmapped reads in order to better understand the functional mechanisms underlying connections between the immune system, microbiome, human gene expression, and disease etiology. ROP is freely available at https://github.com/smangul1/rop and currently supports human and mouse RNA-Seq reads.
Franziska Gruhl - One of the best experts on this subject based on the ideXlab platform.
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rop Dumpster Diving in rna sequencing to find the source of 1 trillion reads across diverse adult human tissues
Genome Biology, 2018Co-Authors: Serghei Mangul, Harry Taegyun Yang, Nicolas Strauli, Franziska Gruhl, Timothy Daley, Hagit T Porath, Kevin Hsieh, Linus Chen, Stephanie A. ChristensonAbstract:High-throughput RNA-sequencing (RNA-seq) technologies provide an unprecedented opportunity to explore the individual transcriptome. Unmapped reads are a large and often overlooked output of standard RNA-seq analyses. Here, we present Read Origin Protocol (ROP), a tool for discovering the source of all reads originating from complex RNA molecules. We apply ROP to samples across 2630 individuals from 54 diverse human tissues. Our approach can account for 99.9% of 1 trillion reads of various read length. Additionally, we use ROP to investigate the functional mechanisms underlying connections between the immune system, microbiome, and disease. ROP is freely available at https://github.com/smangul1/rop/wiki .
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Dumpster Diving in RNA-sequencing to find the source of every last read
bioRxiv, 2016Co-Authors: Serghei Mangul, Harry Taegyun Yang, Nicolas Strauli, Franziska Gruhl, Timothy Daley, Stephanie A. Christenson, Agata Wesolowska-andersen, Roberto Spreafico, Cydney Rios, Celeste EngAbstract:High throughput RNA sequencing technologies have provided invaluable research opportunities across distinct scientific domains by producing quantitative readouts of the transcriptional activity of both entire cellular populations and single cells. The majority of RNA-Seq analyses begin by mapping each experimentally produced sequence (i.e., read) to a set of annotated reference sequences for the organism of interest. For both biological and technical reasons, a significant fraction of reads remains unmapped. In this work, we develop Read Origin Protocol (ROP) to discover the source of all reads originating from complex RNA molecules, recombinant T and B cell receptors, and microbial communities. We applied ROP to 8,641 samples across 630 individuals from 54 tissues. A fraction of RNA-Seq data (n=86) was obtained in-house; the remaining data was obtained from the Genotype-Tissue Expression (GTEx v6) project. To generalize the reported number of accounted reads, we also performed ROP analysis on thousands of different, randomly selected, and publicly available RNA-Seq samples in the Sequence Read Archive (SRA). Our approach can account for 99.9% of 1 trillion reads of various read length across the merged dataset (n=10641). Using in-house RNA-Seq data, we show that immune profiles of asthmatic individuals are significantly different from the profiles of control individuals, with decreased average per sample T and B cell receptor diversity. We also show that immune diversity is inversely correlated with microbial load. Our results demonstrate the potential of ROP to exploit unmapped reads in order to better understand the functional mechanisms underlying connections between the immune system, microbiome, human gene expression, and disease etiology. ROP is freely available at https://github.com/smangul1/rop and currently supports human and mouse RNA-Seq reads.
Serghei Mangul - One of the best experts on this subject based on the ideXlab platform.
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rop Dumpster Diving in rna sequencing to find the source of 1 trillion reads across diverse adult human tissues
Genome Biology, 2018Co-Authors: Serghei Mangul, Harry Taegyun Yang, Nicolas Strauli, Franziska Gruhl, Timothy Daley, Hagit T Porath, Kevin Hsieh, Linus Chen, Stephanie A. ChristensonAbstract:High-throughput RNA-sequencing (RNA-seq) technologies provide an unprecedented opportunity to explore the individual transcriptome. Unmapped reads are a large and often overlooked output of standard RNA-seq analyses. Here, we present Read Origin Protocol (ROP), a tool for discovering the source of all reads originating from complex RNA molecules. We apply ROP to samples across 2630 individuals from 54 diverse human tissues. Our approach can account for 99.9% of 1 trillion reads of various read length. Additionally, we use ROP to investigate the functional mechanisms underlying connections between the immune system, microbiome, and disease. ROP is freely available at https://github.com/smangul1/rop/wiki .
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BCB - ROP: Dumpster Diving in RNA-sequencing to Find the Source of 1 Trillion Reads Across Diverse Adult Human Tissues
Proceedings of the 2018 ACM International Conference on Bioinformatics Computational Biology and Health Informatics, 2018Co-Authors: Serghei Mangul, Harry Yang, Noah ZaitlenAbstract:High-throughput RNA-sequencing (RNA-seq) technologies provide an unprecedented opportunity to explore the individual transcriptome. Unmapped reads are a large and often overlooked output of standard RNA-seq analyses. Here, we present Read Origin Protocol (ROP), a tool for discovering the source of all reads originating from complex RNA molecules. We apply ROP to samples across 2630 individuals from 54 diverse human tissues. Our approach can account for 99.9% of 1 trillion reads of various read length. Additionally, we use ROP to investigate the functional mechanisms underlying connections between the immune system, microbiome, and disease. ROP is freely available at https://github.com/smangul1/rop/wiki.
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Dumpster Diving in RNA-sequencing to find the source of every last read
bioRxiv, 2016Co-Authors: Serghei Mangul, Harry Taegyun Yang, Nicolas Strauli, Franziska Gruhl, Timothy Daley, Stephanie A. Christenson, Agata Wesolowska-andersen, Roberto Spreafico, Cydney Rios, Celeste EngAbstract:High throughput RNA sequencing technologies have provided invaluable research opportunities across distinct scientific domains by producing quantitative readouts of the transcriptional activity of both entire cellular populations and single cells. The majority of RNA-Seq analyses begin by mapping each experimentally produced sequence (i.e., read) to a set of annotated reference sequences for the organism of interest. For both biological and technical reasons, a significant fraction of reads remains unmapped. In this work, we develop Read Origin Protocol (ROP) to discover the source of all reads originating from complex RNA molecules, recombinant T and B cell receptors, and microbial communities. We applied ROP to 8,641 samples across 630 individuals from 54 tissues. A fraction of RNA-Seq data (n=86) was obtained in-house; the remaining data was obtained from the Genotype-Tissue Expression (GTEx v6) project. To generalize the reported number of accounted reads, we also performed ROP analysis on thousands of different, randomly selected, and publicly available RNA-Seq samples in the Sequence Read Archive (SRA). Our approach can account for 99.9% of 1 trillion reads of various read length across the merged dataset (n=10641). Using in-house RNA-Seq data, we show that immune profiles of asthmatic individuals are significantly different from the profiles of control individuals, with decreased average per sample T and B cell receptor diversity. We also show that immune diversity is inversely correlated with microbial load. Our results demonstrate the potential of ROP to exploit unmapped reads in order to better understand the functional mechanisms underlying connections between the immune system, microbiome, human gene expression, and disease etiology. ROP is freely available at https://github.com/smangul1/rop and currently supports human and mouse RNA-Seq reads.
Kubatová Marie - One of the best experts on this subject based on the ideXlab platform.
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Gleaning, trash picking, scavenging: Dumpster Diving and symbolic boundaries between clean and unclean
2014Co-Authors: Kubatová MarieAbstract:The author deals with the phenomenon of Dumpster Diving. Being focused on those divers who are used to Dumpster dive not being pressed to it by their financial situation, she concentrates on their definition of purity and their way of dealing with symbolic boundaries of clean and unclean. After summarising social-environmental and social scientific background of the phenomenon in context of the theoretical frame based on Mary Douglas and her book about purity and danger the author presents a qualitative analysis of participant observation and in- depth interviews with informants who Dumpster dive voluntarily. Based on quantitatively and representatively tested public opinion on Dumpster Diving she points both the colourful composition of Dumpster divers' motives and ideological believes and their reflection and norm- based boundaries categorization that is connected to food they are used to eat. In connection with informants' conception of food value the author argues that through inspiring power of the first Dumpster Diving experience informants' understanding and dealing with those boundaries have changed. Nevertheless, she stresses that despite being convinced their way of consumption is right and thus pure the informants tend to apply and present themselves by pattern of conduct that..
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Gleaning, trash picking, scavenging: Dumpster Diving and symbolic boundaries between clean and unclean
Univerzita Karlova Fakulta sociálních věd, 2014Co-Authors: Kubatová MarieAbstract:Autorka se v textu zabývá fenoménem Dumpster Divingu, v češtině označovanému jako kontejnerové potápění. Se zaměřením na takové potápěče, kteří vyjímají a konzumují jídlo z kontejnerů za supermarkety dobrovolně, bez finančního donucení, soustředí se na jejich definici čistoty a práci se symbolickými hranicemi mezi čistým a nečistým. Opřena o kontextuální ukotvení fenoménu v sociálně-environmentálních a sociálně vědních souvislostech a vycházejíc zejména z teoretické koncepce čistoty a nebezpečí Mary Douglas, předkládá čtenáři kvalitativní analýzu zúčastněných pozorování a hloubkových rozhovorů s dobrovolnými potápěči. Na základě ukotvení kvalitativních poznatků v kvantitativně a reprezentativně zjištěných postojích české veřejnosti k projevům kontejnerového potápění, všímá si pestrého složení potápěčů z hlediska jejich motivů a ideologických přesvědčení i jejich reflexe a kategorizace normově nastavených hranic, jimiž jsou potraviny jimi konzumované obestřeny. Prostřednictvím identifikace síly a podnětnosti první zkušenosti s Dumpster Divingem a v souvislosti s představenou hodnotou, kterou informanti přisuzují jídlu, poukazuje autorka na jejich proměnu pojetí dosud akceptovaných hranic odvíjející se od provozování Dumpster Divingu. Zdůrazňuje však, že navzdory přesvědčení o řádnosti a čistotě...The author deals with the phenomenon of Dumpster Diving. Being focused on those divers who are used to Dumpster dive not being pressed to it by their financial situation, she concentrates on their definition of purity and their way of dealing with symbolic boundaries of clean and unclean. After summarising social-environmental and social scientific background of the phenomenon in context of the theoretical frame based on Mary Douglas and her book about purity and danger the author presents a qualitative analysis of participant observation and in- depth interviews with informants who Dumpster dive voluntarily. Based on quantitatively and representatively tested public opinion on Dumpster Diving she points both the colourful composition of Dumpster divers' motives and ideological believes and their reflection and norm- based boundaries categorization that is connected to food they are used to eat. In connection with informants' conception of food value the author argues that through inspiring power of the first Dumpster Diving experience informants' understanding and dealing with those boundaries have changed. Nevertheless, she stresses that despite being convinced their way of consumption is right and thus pure the informants tend to apply and present themselves by pattern of conduct that...Department of SociologyKatedra sociologieFakulta sociálních vědFaculty of Social Science
Harry Taegyun Yang - One of the best experts on this subject based on the ideXlab platform.
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rop Dumpster Diving in rna sequencing to find the source of 1 trillion reads across diverse adult human tissues
Genome Biology, 2018Co-Authors: Serghei Mangul, Harry Taegyun Yang, Nicolas Strauli, Franziska Gruhl, Timothy Daley, Hagit T Porath, Kevin Hsieh, Linus Chen, Stephanie A. ChristensonAbstract:High-throughput RNA-sequencing (RNA-seq) technologies provide an unprecedented opportunity to explore the individual transcriptome. Unmapped reads are a large and often overlooked output of standard RNA-seq analyses. Here, we present Read Origin Protocol (ROP), a tool for discovering the source of all reads originating from complex RNA molecules. We apply ROP to samples across 2630 individuals from 54 diverse human tissues. Our approach can account for 99.9% of 1 trillion reads of various read length. Additionally, we use ROP to investigate the functional mechanisms underlying connections between the immune system, microbiome, and disease. ROP is freely available at https://github.com/smangul1/rop/wiki .
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Dumpster Diving in RNA-sequencing to find the source of every last read
bioRxiv, 2016Co-Authors: Serghei Mangul, Harry Taegyun Yang, Nicolas Strauli, Franziska Gruhl, Timothy Daley, Stephanie A. Christenson, Agata Wesolowska-andersen, Roberto Spreafico, Cydney Rios, Celeste EngAbstract:High throughput RNA sequencing technologies have provided invaluable research opportunities across distinct scientific domains by producing quantitative readouts of the transcriptional activity of both entire cellular populations and single cells. The majority of RNA-Seq analyses begin by mapping each experimentally produced sequence (i.e., read) to a set of annotated reference sequences for the organism of interest. For both biological and technical reasons, a significant fraction of reads remains unmapped. In this work, we develop Read Origin Protocol (ROP) to discover the source of all reads originating from complex RNA molecules, recombinant T and B cell receptors, and microbial communities. We applied ROP to 8,641 samples across 630 individuals from 54 tissues. A fraction of RNA-Seq data (n=86) was obtained in-house; the remaining data was obtained from the Genotype-Tissue Expression (GTEx v6) project. To generalize the reported number of accounted reads, we also performed ROP analysis on thousands of different, randomly selected, and publicly available RNA-Seq samples in the Sequence Read Archive (SRA). Our approach can account for 99.9% of 1 trillion reads of various read length across the merged dataset (n=10641). Using in-house RNA-Seq data, we show that immune profiles of asthmatic individuals are significantly different from the profiles of control individuals, with decreased average per sample T and B cell receptor diversity. We also show that immune diversity is inversely correlated with microbial load. Our results demonstrate the potential of ROP to exploit unmapped reads in order to better understand the functional mechanisms underlying connections between the immune system, microbiome, human gene expression, and disease etiology. ROP is freely available at https://github.com/smangul1/rop and currently supports human and mouse RNA-Seq reads.
