scholarly journals Decoupling alignment strategy from feature quantification using a standard alignment incidence data structure

2021 ◽  
Author(s):  
Kwangbom Choi ◽  
Matthew J. Vincent ◽  
Gary A. Churchill
Keyword(s):  
Gene Expression ◽  
Data Structure ◽  
Genomic Feature ◽  
File Format ◽  
Read Alignment ◽  
Incidence Data ◽  
Link Type ◽  
Generic Data ◽  
Alignment Strategy ◽  
Standard Alignment

AbstractSummaryThe abundance of genomic feature such as gene expression is often estimated from observed total number of alignment incidences in the targeted genome regions. We introduce a generic data structure and associated file format for alignment incidence data so that method developers can create novel pipelines comprising models, each optimal for read alignment, post-alignment QC, and quantification across multiple sequencing modalities.Availability and Implementationalntools software is freely available at https://github.com/churchill-lab/alntools under MIT [email protected] or [email protected]

Pedigree and Pedigree Import Wizard

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 552g-553
Author(s):  
Shahrokh Khandizadeh
Keyword(s):  
Additional Data ◽  
File Format ◽  
Fruit Crops ◽  
Operating Environment ◽  
Agronomic Characteristics ◽  
Link Type ◽  
Plant Characteristics ◽  
User Friendly

Pedigree for Windows is a user-friendly program that allows the user to trace agronomic characteristics, draw pedigrees, and view images of several fruit crops, including more than 1400 apple, 800 strawberry, 800 almond, 100 blackberry, 80 blueberry, 790 pear, 200 raspberry examples. Pedigree Import Wizard®© for Windows is an add-on software for users who are interested in importing their research or breeding data records of fruit, flower, and plant characteristics and any related images into Pedigree for Windows. Pedigree for Windows and Pedigree Import Wizard have been designed so that a user familiar with the Windows operating environment should have little need to refer to the documentation provided with the program. Pedigree Import Wizard uses a comma-separated value (csv) file format under the MS Excel environment. This option allows the user to add or import additional data to the existing database that are already stored in other software such as Lotus, Excel, Access, QuattroPro, WordPerfect, and MS Word tables, etc., as long as they work under the Windows environment. A free demo version of Pedigree and Pedigree Import Wizard for Windows is available from http://www.pgris.com.

scholarly journals An open-label, pilot study of veliparib and lapatinib in patients with metastatic, triple-negative breast cancer

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Erica M. Stringer-Reasor ◽  
Jori E. May ◽  
Eva Olariu ◽  
Valerie Caterinicchia ◽  
Yufeng Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Dna Repair ◽  
Pilot Study ◽  
Expression Analysis ◽  
Triple Negative Breast Cancer ◽  
Gene Expression Analysis ◽  
Triple Negative ◽  
Egfr Inhibition ◽  
Link Type

Abstract Background Poly (ADP-ribose)-polymerase inhibitors (PARPi) have been approved for cancer patients with germline BRCA1/2 (gBRCA1/2) mutations, and efforts to expand the utility of PARPi beyond BRCA1/2 are ongoing. In preclinical models of triple-negative breast cancer (TNBC) with intact DNA repair, we have previously shown an induced synthetic lethality with combined EGFR inhibition and PARPi. Here, we report the safety and clinical activity of lapatinib and veliparib in patients with metastatic TNBC. Methods A first-in-human, pilot study of lapatinib and veliparib was conducted in metastatic TNBC (NCT02158507). The primary endpoint was safety and tolerability. Secondary endpoints were objective response rates and pharmacokinetic evaluation. Gene expression analysis of pre-treatment tumor biopsies was performed. Key eligibility included TNBC patients with measurable disease and prior anthracycline-based and taxane chemotherapy. Patients with gBRCA1/2 mutations were excluded. Results Twenty patients were enrolled, of which 17 were evaluable for response. The median number of prior therapies in the metastatic setting was 1 (range 0–2). Fifty percent of patients were Caucasian, 45% African–American, and 5% Hispanic. Of evaluable patients, 4 demonstrated a partial response and 2 had stable disease. There were no dose-limiting toxicities. Most AEs were limited to grade 1 or 2 and no drug–drug interactions noted. Exploratory gene expression analysis suggested baseline DNA repair pathway score was lower and baseline immunogenicity was higher in the responders compared to non-responders. Conclusions Lapatinib plus veliparib therapy has a manageable safety profile and promising antitumor activity in advanced TNBC. Further investigation of dual therapy with EGFR inhibition and PARP inhibition is needed. Trial registration ClinicalTrials.gov, NCT02158507. Registered on 12 September 2014

scholarly journals THU0008 DEVELOPMENT OF A NOVEL TRANSLATIONAL IN SILICO INDICATION DISCOVERY FRAMEWORK: EXEMPLIFIED BY THE CLINICAL COMPOUND CENERIMOD

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 216.2-217
Author(s):  
D. Hartl ◽  
M. Keller ◽  
A. Klenk ◽  
M. Murphy ◽  
M. Martinic ◽  
...  
Keyword(s):  
Gene Expression ◽  
Animal Models ◽  
Clinical Response ◽  
Gene Expression Data ◽  
In Silico ◽  
Drug Candidate ◽  
Expression Data ◽  
Computer Algorithms ◽  
Clinical Patient ◽  
Link Type

Background:To explore the full therapeutic spectrum of a drug it is crucial to consider its potential effectiveness in all diseases. Serendipitous clinical observations have often shown that approved drugs and those in development to be efficacious in indications different to those originally tested for. Traditional approaches to match a drug candidate with possible indications are mostly based on matching drug mechanistic knowledge with disease pathophysiology. Proof-of-concept trials or elaborate pre-clinical studies in animal models do not allow for a broad assessment due to high costs and slow progress. Gene expression changes in patients or animal models represent a good proxy to comprehensively assess both disease and drug effects. Furthermore, this data type can be integrated with a plethora of publicly available data.Objectives:Generation of a novel in silico framework to support the selection and expansion of potential indications which associate with a compound or approved drug. The framework was exemplified by the clinical compound cenerimod, a potent, selective, and orally active sphingosine-1-phosphate receptor 1 modulator (Piali et al., 2017).Methods:A total of ~13’000 public patient gene expression datasets from ~140 diseases were evaluated against cenerimod gene expression data generated in mouse disease models. To improve comparability of studies across platforms and species, computer algorithms (neural networks) were trained and employed to reduce noise within the data sets and improve signal. The predicted response to cenerimod for individual patients was contrasted against clinical patient characteristics.Results:The neural network algorithm efficiently reduced experimental noise and improved sensitivity in the gene expression data. The results predicted cenerimod to be efficacious in several auto-immune diseases foremost SLE. Additionally, focused analysis on individual patients rather than disease cohorts revealed potential determinants predictive of maximal clinical response, with the highest predicted clinical response for cenerimod in patients with severe inflammatory endotype and/or high SLE Disease Activity Index (SLEDAI).Conclusion:Combining preclinical compound data with the wealth of public disease gene expression data, provides great potential to support indication selection. The novel in silico framework identified SLE as a prime potential indication for cenerimod and supported the cenerimod phase 2b clinical trial in patients with SLE (CARE study,NCT03742037).References:[1]Piali, L., Birker-Robaczewska, M., Lescop, C., Froidevaux, S., Schmitz, N., Morrison, K., … Nayler, O. (2017). Cenerimod, a novel selective S1P1 receptor modulator with unique signaling properties. Pharmacology Research & Perspectives, 5(6), 1–12.https://doi.org/10.1002/prp2.370Disclosure of Interests:Dominik Hartl Shareholder of: Idorsia shares, Employee of: Idorsia employee, Marcel Keller Shareholder of: Idorsia options/shares, Employee of: Idorsia employee, Axel Klenk Shareholder of: Idorsia option/shares, Employee of: Idorsia employee, Mark Murphy Shareholder of: Idorsia shares and stock options, Employee of: Idorsia employee, Marianne Martinic Shareholder of: Idorsia options/shares, Employee of: Idorsia employee, Gabin Pierlot Shareholder of: Idorsia options/shares, Employee of: Idorsia employee, Peter Groenen Shareholder of: Idorsia options/shares, Employee of: Idorsia employee, Daniel Strasser Shareholder of: Idorsia options/shares, Employee of: Idorsia employee

scholarly journals EspM Is a Conserved Transcription Factor That Regulates Gene Expression in Response to the ESX-1 System

mBio ◽  
2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Kevin G. Sanchez ◽  
Micah J. Ferrell ◽  
Alexandra E. Chirakos ◽  
Kathleen R. Nicholson ◽  
Robert B. Abramovitch ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Protein Transport ◽  
Transcriptional Response ◽  
Secretion System ◽  
Pathogenic Species ◽  
Macrophage Infection ◽  
Content Type ◽  
Link Type ◽  
Phagosomal Membrane

ABSTRACT Pathogenic mycobacteria encounter multiple environments during macrophage infection. Temporally, the bacteria are engulfed into the phagosome, lyse the phagosomal membrane, and interact with the cytosol before spreading to another cell. Virulence factors secreted by the mycobacterial ESX-1 (ESAT-6-system-1) secretion system mediate the essential transition from the phagosome to the cytosol. It was recently discovered that the ESX-1 system also regulates mycobacterial gene expression in Mycobacterium marinum (R. E. Bosserman, T. T. Nguyen, K. G. Sanchez, A. E. Chirakos, et al., Proc Natl Acad Sci U S A 114:E10772–E10781, 2017, https://doi.org/10.1073/pnas.1710167114), a nontuberculous mycobacterial pathogen, and in the human-pathogenic species M. tuberculosis (A. M. Abdallah, E. M. Weerdenburg, Q. Guan, R. Ummels, et al., PLoS One 14:e0211003, 2019, https://doi.org/10.1371/journal.pone.0211003). It is not known how the ESX-1 system regulates gene expression. Here, we identify the first transcription factor required for the ESX-1-dependent transcriptional response in pathogenic mycobacteria. We demonstrate that the gene divergently transcribed from the whiB6 gene and adjacent to the ESX-1 locus in mycobacterial pathogens encodes a conserved transcription factor (MMAR_5438, Rv3863, now espM). We prove that EspM from both M. marinum and M. tuberculosis directly and specifically binds the whiB6-espM intergenic region. We show that EspM is required for ESX-1-dependent repression of whiB6 expression and for the regulation of ESX-1-associated gene expression. Finally, we demonstrate that EspM functions to fine-tune ESX-1 activity in M. marinum. Taking the data together, this report extends the esx-1 locus, defines a conserved regulator of the ESX-1 virulence pathway, and begins to elucidate how the ESX-1 system regulates gene expression. IMPORTANCE Mycobacterial pathogens use the ESX-1 system to transport protein substrates that mediate essential interactions with the host during infection. We previously demonstrated that in addition to transporting proteins, the ESX-1 secretion system regulates gene expression. Here, we identify a conserved transcription factor that regulates gene expression in response to the ESX-1 system. We demonstrate that this transcription factor is functionally conserved in M. marinum, a pathogen of ectothermic animals; M. tuberculosis, the human-pathogenic species that causes tuberculosis; and M. smegmatis, a nonpathogenic mycobacterial species. These findings provide the first mechanistic insight into how the ESX-1 system elicits a transcriptional response, a function of this protein transport system that was previously unknown.

scholarly journals Pathovar Transcriptomes

mSystems ◽  
2017 ◽  
Vol 2 (4) ◽  
Author(s):  
Amy Platenkamp ◽  
Jay L. Mellies
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Regulatory Networks ◽  
Virulence Gene ◽  
Model System ◽  
Genomic Sequences ◽  
Bacterial Strains ◽  
Content Type ◽  
Virulence Gene Expression ◽  
Link Type

ABSTRACT Archetypal pathogenic bacterial strains are often used to elucidate regulatory networks of an entire pathovar, which encompasses multiple lineages and phylogroups. With enteropathogenic Escherichia coli (EPEC) as a model system, Hazen and colleagues (mSystems 6:e00024-17, 2017, https://doi.org/10.1128/mSystems.00024-17 ) used 9 isolates representing 8 lineages and 3 phylogroups to find that isolates with similar genomic sequences exhibit similarities in global transcriptomes under conditions of growth in medium that induces virulence gene expression, and they found variation among individual isolates. Archetypal pathogenic bacterial strains are often used to elucidate regulatory networks of an entire pathovar, which encompasses multiple lineages and phylogroups. With enteropathogenic Escherichia coli (EPEC) as a model system, Hazen and colleagues (mSystems 6:e00024-17, 2017, https://doi.org/10.1128/mSystems.00024-17 ) used 9 isolates representing 8 lineages and 3 phylogroups to find that isolates with similar genomic sequences exhibit similarities in global transcriptomes under conditions of growth in medium that induces virulence gene expression. They also found variation among individual isolates. Their work illustrates the importance of moving beyond observing regulatory phenomena of a limited number of regulons in a few archetypal strains, with the possibility of correlating clinical symptoms to key transcriptional pathways across lineages and phylogroups.

scholarly journals A New Machine Learning-Based Framework for Mapping Uncertainty Analysis in RNA-Seq Read Alignment and Gene Expression Estimation

2018 ◽  
Vol 9 ◽  
Author(s):  
Adam McDermaid ◽  
Xin Chen ◽  
Yiran Zhang ◽  
Cankun Wang ◽  
Shaopeng Gu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Uncertainty Analysis ◽  
Rna Seq ◽  
Read Alignment ◽  
New Machine

scholarly journals LandScape: a web application for interactive genomic summary visualization

2019 ◽  
Author(s):  
Wenlong Jia ◽  
Hechen Li ◽  
Shiying Li ◽  
Shuaicheng Li
Keyword(s):  
Genetic Information ◽  
Web Application ◽  
Genomic Research ◽  
File Format ◽  
Data Types ◽  
Web Based ◽  
Link Type ◽  
Level Data ◽  
Real Time Visualization ◽  
Information Landscape

ABSTRACTSummaryVisualizing integrated-level data from genomic research remains a challenge, as it requires sufficient coding skills and experience. Here, we present LandScapeoviz, a web-based application for interactive and real-time visualization of summarized genetic information. LandScape utilizes a well-designed file format that is capable of handling various data types, and offers a series of built-in functions to customize the appearance, explore results, and export high-quality diagrams that are available for publication.Availability and implementationLandScape is deployed at bio.oviz.org/demo-project/analyses/landscape for online use. Documentation and demo data are freely available on this website and GitHub (github.com/Nobel-Justin/Oviz-Bio-demo)[email protected]

scholarly journals VExD: A curated resource for human gene expression following viral infection

2021 ◽  
Author(s):  
Phillip J Dexheimer ◽  
Mario Pujato ◽  
Krishna Roskin ◽  
Matthew T Weirauch
Keyword(s):  
Gene Expression ◽  
Viral Infection ◽  
Human Gene ◽  
Application Programming Interface ◽  
Gene Expression Response ◽  
Human Gene Expression ◽  
Link Type ◽  
Uniform Manner ◽  
Expression Response ◽  
Virus Expression

AbstractMotivationHuman viruses cause significant mortality, morbidity, and economic disruption worldwide. The human gene expression response to viral infection can yield important insights into the detrimental effects to the host. To date, hundreds of studies have performed genome-scale profiling of the effect of viral infection on human gene expression. However, no resource exists that aggregates human expression results across multiple studies, viruses, and tissue types.ResultsWe developed the Virus Expression Database (VExD), a comprehensive curated resource of transcriptomic studies of viral infection in human cells. We have processed all studies within VExD in a uniform manner, allowing users to easily compare human gene expression changes across conditions.Availability and ImplementationVExD is freely accessible at https://vexd.cchmc.org for all modern web browsers. An Application Programming Interface (API) for VExD is also available. The source code is available at https://github.com/pdexheimer/[email protected], [email protected]

scholarly journals Diagnostic model of combined ceRNA and DNA methylation related genes in esophageal carcinoma

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8831 ◽  
Author(s):  
Xiaojiao Guan ◽  
Yao Yao ◽  
Guangyao Bao ◽  
Yue Wang ◽  
Aimeng Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Esophageal Cancer ◽  
Esophageal Carcinoma ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Diagnostic Model ◽  
Link Type ◽  
Key Genes

Esophageal cancer is a common malignant tumor in the world, and the aim of this study was to screen key genes related to the development of esophageal cancer using a variety of bioinformatics analysis tools and analyze their biological functions. The data of esophageal squamous cell carcinoma from the Gene Expression Omnibus (GEO) were selected as the research object, processed and analyzed to screen differentially expressed microRNAs (miRNAs) and differential methylation genes. The competing endogenous RNAs (ceRNAs) interaction network of differentially expressed genes was constructed by bioinformatics tools DAVID, String, and Cytoscape. Biofunctional enrichment analysis was performed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The expression of the screened genes and the survival of the patients were verified. By analyzing GSE59973 and GSE114110, we found three down-regulated and nine up-regulated miRNAs. The gene expression matrix of GSE120356 was calculated by Pearson correlation coefficient, and the 11696 pairs of ceRNA relation were determined. In the ceRNA network, 643 lncRNAs and 147 mRNAs showed methylation difference. Functional enrichment analysis showed that these differentially expressed genes were mainly concentrated in the FoxO signaling pathway and were involved in the corresponding cascade of calcineurin. By analyzing the clinical data in The Cancer Genome Atlas (TCGA) database, it was found that four lncRNAs had an important impact on the survival and prognosis of esophageal carcinoma patients. QRT-PCR was also conducted to identify the expression of the key lncRNAs (RNF217-AS1, HCP5, ZFPM2-AS1 and HCG22) in ESCC samples. The selected key genes can provide theoretical guidance for further research on the molecular mechanism of esophageal carcinoma and the screening of molecular markers.

scholarly journals The Popgen Pipeline Platform: A Software Platform for Facilitating Population Genomic Analyses

2019 ◽  
Author(s):  
Andrew Webb ◽  
Jared Knoblauch ◽  
Nitesh Sabankar ◽  
Apeksha Sukesh Kallur ◽  
Jody Hey ◽  
...  
Keyword(s):  
Open Source ◽  
Development Time ◽  
End Users ◽  
File Format ◽  
Software Platform ◽  
Format Conversion ◽  
Link Type ◽  
Population Genomic ◽  
Genomic Analyses ◽  
File Format Conversion

AbstractHere we present the Pop-Gen Pipeline Platform (PPP), a software platform with the goal of reducing the computational expertise required for conducting population genomic analyses. The PPP was designed as a collection of scripts that facilitate common population genomic workflows in a consistent and standardized Python environment. Functions were developed to encompass entire workflows, including: input preparation, file format conversion, various population genomic analyses, output generation, and visualization. By facilitating entire workflows, the PPP offers several benefits to prospective end users - it reduces the need of redundant in-house software and scripts that would require development time and may be error-prone, or incorrect. The platform has also been developed with reproducibility and extensibility of analyses in mind. The PPP is an open-source package that is available for download and use at https://ppp.readthedocs.io/en/latest/PPP_pages/install.html

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