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DeconRNASeq: a statistical framework for deconvolution of heterogeneous tissue samples based on mRNA-Seq data

Ting Gong, Joseph D. Szustakowski
2013 Computer applications in the biosciences : CABIOS  
In this vignette, we present an efficient pipeline and methodology: Decon-RNASeq, an R package for deconvolution of heterogeneous tissues based on mRNA-Seq data.  ...  the total number of mRNA-Seq mixing samples consisting of multiple samples.  ... 
doi:10.1093/bioinformatics/btt090 pmid:23428642 fatcat:s43jbt65zjctrm2wvjwu34lciu

An assessment of computational methods for estimating purity and clonality using genomic data derived from heterogeneous tumor tissue samples

V. K. Yadav, S. De
2014 Briefings in Bioinformatics  
Deconvolution of genomic data from heterogeneous samples provides a powerful tool to address this limitation.  ...  A majority of the cancer genomics and transcriptomics studies do not explicitly consider genetic heterogeneity and impurity, and draw inferences based on mixed populations of cells.  ...  The comparative analysis results published here are in part based upon data generated by The Cancer Genome Atlas pilot project [56] established by the NCI and NHGRI (dbGAP accession ID: phs000178.v8.  ... 
doi:10.1093/bib/bbu002 pmid:24562872 pmcid:PMC4794615 fatcat:mcg7fqdg65gbhnc7okknmpz774

Quantifying tumor-infiltrating immune cells from transcriptomics data

Francesca Finotello, Zlatko Trajanoski
2018 Cancer Immunology and Immunotherapy  
In this review, we describe state-of-the-art computational methods for the quantification of immune cells from transcriptomics data and discuss the open challenges that must be addressed to accurately  ...  quantify immune infiltrates from RNA sequencing data of human bulk tumors.  ...  Acknowledgements Open access funding provided by University of Innsbruck and Medical University of Innsbruck.  ... 
doi:10.1007/s00262-018-2150-z pmid:29541787 pmcid:PMC6006237 fatcat:iplezgpqpjbkheyrrtf4prtc4u

Endometrial receptivity revisited: endometrial transcriptome adjusted for tissue cellular heterogeneity [article]

Marina Suhorutshenko, Viktorija Kukushkina, Agne Velthut-Meikas, Signe Altmäe, Maire Peters, Reedik Mägi, Kaarel Krjutshkov, Mariann Koel, Juan Francisco Martinez-Blanch, Francisco Codoner, Felipe Vilella, Carlos Simon (+2 others)
2018 bioRxiv   pre-print
However, the other 74% (n=2,645) become statistically non-significant after adjustment for biopsy cellular composition, underlining the impact of tissue heterogeneity on differential expression analysis  ...  In one of them, computational deconvolution was applied as an intermediate step to adjust for epithelial and stromal cells' proportions in endometrial biopsy.  ...  DeconRNASeq: a statistical framework for deconvolution of 584 heterogeneous tissue samples based on mRNA-Seq data. Bioinformatics 2013;29:1083-585 1085. 586 Groen JN, Capraro D, Morris K V.  ... 
doi:10.1101/357152 fatcat:hz7g5zkg2ra4ndqj7zhbf36igy

DeconPeaker, a Deconvolution Model to Identify Cell Types Based on Chromatin Accessibility in ATAC-Seq Data of Mixture Samples

Huamei Li, Amit Sharma, Kun Luo, Zhaohui S. Qin, Xiao Sun, Hongde Liu
2020 Frontiers in Genetics  
Since chromatin accessibility patterns play a major role in human diseases, it is therefore anticipated that a deconvolution tool based on open chromatin data will provide better performance in identifying  ...  Using this tool, we simultaneously evaluated chromatin accessibility and gene expression datasets to estimate cell types and their respective proportions in a mixture of samples.  ...  (served as ground truth) on mRNA expression data. Each point represents a specific cell type in a sample.  ... 
doi:10.3389/fgene.2020.00392 pmid:32547592 pmcid:PMC7269180 fatcat:txhnlclb3vc25jwqgm5f34h2di

SCDC: Bulk Gene Expression Deconvolution by Multiple Single-Cell RNA Sequencing References [article]

Meichen Dong, Aatish Thennavan, Eugene Urrutia, Yun Li, Charles M Perou, Fei Zou, Yuchao Jiang
2019 bioRxiv   pre-print
Here, we propose SCDC, a deconvolution method for bulk RNA-seq that leverages cell-type specific gene expression profiles from multiple scRNA-seq reference datasets.  ...  RNA sequencing (RNA-seq) data.  ...  Acknowledgments This work was supported by the National Institutes of Health (NIH) grant T32  ... 
doi:10.1101/743591 fatcat:eytacfzqlngdhcbm34qqun6ee4

Transcriptional deconvolution reveals consistent functional subtypes of pancreatic cancer epithelium and stroma [article]

Jing He, H. Carlo Maurer, Sam R. Holmstrom, Tao Su, Aqeel Ahmed, Hanina Hibshoosh, John A. Chabot, Paul E. Oberstein, Antonia R. Sepulveda, Jeanine M. Genkinger, Jiapeng Zhang, Alina C. Iuga (+3 others)
2018 bioRxiv   pre-print
This led to the development of a new algorithm (ADVOCATE) that accurately predicts the compartment fractions of bulk tumor samples and can computationally purify bulk gene expression data from PDA.  ...  Bulk tumor tissues comprise intermixed populations of neoplastic cells and multiple stromal cell lineages.  ...  Giorgi and Alexander Lachmann for advice on computational methods, and Richard Moffitt for valuable critique of the manuscript.  ... 
doi:10.1101/288779 fatcat:kbc2kmntifgltgnpvz3han7c2a

ISOpureR: an R implementation of a computational purification algorithm of mixed tumour profiles

Catalina V Anghel, Gerald Quon, Syed Haider, Francis Nguyen, Amit G Deshwar, Quaid D Morris, Paul C Boutros
2015 BMC Bioinformatics  
ISOpure is the only mRNA computational purification method to date that does not require a paired tumour-normal sample, provides a personalized cancer profile for each patient, and has been tested on clinical  ...  normal cells present challenges in the development of reproducible biomarkers, as these biomarkers are based on bulk signals from mixed tumour profiles.  ...  Acknowledgements The authors thank all members of the Boutros lab for helpful suggestions. This study was conducted with the support of the Ontario Institute for Cancer  ... 
doi:10.1186/s12859-015-0597-x pmid:25972088 pmcid:PMC4429941 fatcat:7tjxyxnjuvgl7etxb5putwc4dq

De novo compartment deconvolution and weight estimation of tumor samples (DECODER) [article]

Xianlu Laura Peng, Richard A Moffitt, Robert J Torphy, Keith E Volmar, Jen Jen Yeh
2019 bioRxiv   pre-print
To this end, we developed DECODER, an integrated framework which performs de novo deconvolution, and compartment weight estimation for a single sample.  ...  We use DECODER to deconvolve 33 TCGA tumor RNA-seq datasets and show that it may be applied to other data types including ATAC-seq.  ...  This framework is not only a useful algorithm for de novo and single sample deconvolution of heterogenous samples, but also to the best of our knowledge, for the first time, provides cancer typespecific  ... 
doi:10.1101/561647 fatcat:wljkvfk5dvgzdhvalikdxqcjv4

Simultaneous Enumeration Of Cancer And Immune Cell Types From Bulk Tumor Gene Expression Data [article]

Julien Racle, Kaat de Jonge, Petra Baumgaertner, Daniel E. Speiser, David Gfeller
2017 bioRxiv   pre-print
Altogether, our work not only improves accuracy but also broadens the scope of absolute cell fraction predictions from tumor gene expression data, and provides a unique novel experimental benchmark for  ...  Our method integrates novel gene expression profiles from each major non-malignant cell type found in tumors, renormalization based on cell-type specific mRNA content, and the ability to consider uncharacterized  ...  Acknowledgements We are grateful to Hélène Maby-El Hajjami for compiling the clinical data. We thank  ... 
doi:10.1101/117788 fatcat:4y5jeljkgfegbjrygjhamfhmlm

Post-mortem molecular profiling of three psychiatric disorders [article]

Ryne C. Ramaker, Kevin M. Bowling, Brittany N. Lasseigne, Megan H. Hagenauer, Andrew A. Hardigan, Nick S. Davis, Jason Gertz, Preston M. Cartagena, David M. Walsh, Marquis P. Vawter, Alan F. Schatzberg, Jack D. Barchas (+7 others)
2016 bioRxiv   pre-print
We performed RNA sequencing on tissue from the anterior cingulate cortex, dorsolateral prefrontal cortex, and nucleus accumbens from three groups of 24 patients each diagnosed with schizophrenia, bipolar  ...  The most significant disease differences were in the anterior cingulate cortex of schizophrenia samples compared to controls.  ...  http://dx.doi.org/10.1101/061416 doi: bioRxiv preprint first posted online Jun. 29, 2016; 30 from: 1 2 ndertype=abstract 3 4 of heterogeneous tissue samples based on mRNA-Seq data.  ... 
doi:10.1101/061416 fatcat:oaoi5jat5vhmfpe7i45hdu6lc4

Review Computational characterisation of cancer molecular profiles derived using next generation sequencing

Urszula Oleksiewicz, Katarzyna Tomczak, Jakub Woropaj, Monika Markowska, Piotr Stępniak, Parantu K Shah
2015 Contemporary Oncology  
We comment on the importance of integrating these data and building infrastructure to analyse it.  ...  In this article, we outline common steps for the quality control and processing of NGS data.  ...  Comparative and integrative analysis of tumour samples One of the major achievements of the TCGA project is the generation of different types of data from the same sample for a large number of tumours.  ... 
doi:10.5114/wo.2014.47137 pmid:25691827 pmcid:PMC4322529 fatcat:mpdgbyjgjbfhxbcsxiedb47w44

Reference-based annotation of single-cell transcriptomes identifies a profibrotic macrophage niche after tissue injury [article]

Dvir Aran, Agnieszka P. Looney, Leqian Liu, Valerie Fong, Austin Hsu, Paul J. Wolters, Adam Abate, Atul J. Butte, Mallar Bhattacharya
2018 bioRxiv   pre-print
We first developed a computational framework that enables unbiased, granular cell-type annotation of scRNA-seq.  ...  Myeloid cells localize to peripheral tissues in a wide range of pathologic contexts.  ...  Deconvolution analysis inFigure 2awas performed using the DeconRNAseq package 33 using the average expression of AM samples and average expression of IM3 samples from GSE94135.  ... 
doi:10.1101/284604 fatcat:q6zcoxiktnbbppkg5sbs2ukh2u

Basal Expression of Interferon-Stimulated Genes Drives Population Differences in Monocyte Susceptibility to Influenza Infection [article]

Mary O'Neill, Helene Quach, Julien Pothlichet, Yann Aquino, Aurelie Bisiaux, Nora Zidane, Matthieu Deschamps, Valentina Libri, Milena Hasan, Shen-Ying Zhang, Qian Zhang, Daniela Matuozzo (+6 others)
2020 bioRxiv   pre-print
There is considerable inter-individual immunological and clinical variability upon influenza A virus (IAV) infection in humans; yet, the factors underlying such heterogeneity remain elusive.  ...  Finally, we identify 135 genes, including the interferon-stimulated genes IFITM3, MX1, and OAS3, for which basal mRNA expression levels associate with IAV mRNA levels post infection.  ...  DeconRNASeq: a statistical framework for deconvolution of heterogeneous tissue samples based on mRNA-Seq data. Bioinformatics 29, 1083-1085. Gounder, A.P., and Boon, A.C.M. (2019).  ... 
doi:10.1101/2020.12.07.414151 fatcat:xdxs7gsmcje57japqzb7mcgjsa

Omics-Driven Biomarkers of Psoriasis: Recent Insights, Current Challenges, and Future Prospects

Busra Aydin, Kazim Yalcin Arga, Ayse Serap Karadag
2020 Clinical, Cosmetic and Investigational Dermatology  
Furthermore, insights on the limitations and future directions of the current biomarker discovery strategies were discussed, which will continue to comprehend broader visions of psoriasis research, diagnosis  ...  , and therapy especially in the context of personalized medicine.  ...  dataset and quantify the perturbation score of healthy and diseased samples, as well. 87 DeconRNASeq (deconvolution on mRNA-seq) is another pipeline that provides deconvolution of heterogeneous tissues  ... 
doi:10.2147/ccid.s227896 pmid:32922059 pmcid:PMC7456337 fatcat:t5vxbwmxe5cpddfieteuqxcqj4
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