scholarly journals RNAtor: an Android-based application for biologists to plan RNA sequencing experiments

2016 ◽  
Author(s):  
Shruti Kane ◽  
Himanshu Garg ◽  
Neeraja M. Krishnan ◽  
Aditya Singh ◽  
Binay Panda
Keyword(s):  
Rna Sequencing ◽  
Mobile Applications ◽  
Mobile Application ◽  
Splice Variants ◽  
Real Data ◽  
Flow Cell ◽  
Rna Seq ◽  
Amount Of Information ◽  
Novel Transcripts ◽  
Google Play

AbstractRNA sequencing (RNA-seq) is a powerful technology for identification of novel transcripts (coding, non-coding and splice variants), understanding of transcript structures and estimation of gene and/or allelic expression. There are specific challenges that biologists face in determining the number of replicates to use, total number of sequencing reads to generate for detecting marginally differentially expressed transcripts and the number of lanes in a sequencing flow cell to use for the production of right amount of information. Although past studies attempted answering some of these questions, there is a lack of accessible and biologist-friendly mobile applications to answer these questions. Keeping this in mind, we have developed RNAtor, a mobile application for Android platforms, to aid biologists in correctly designing their RNA-seq experiments. The recommendations from RNAtor are based on simulations and real data.Availability and ImplementationThe Android version of RNAtor is available on Google Play Store and the code from GitHub (https://github.com/binaypanda/RNAtor).

scholarly journals RNAtor: an Android-based application for biologists to plan RNA sequencing experiments

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 997
Author(s):  
Shruti Kane ◽  
Himanshu Garg ◽  
Neeraja M. Krishnan ◽  
Aditya Singh ◽  
Binay Panda
Keyword(s):  
Rna Sequencing ◽  
Mobile Applications ◽  
Mobile Application ◽  
Splice Variants ◽  
Real Data ◽  
Flow Cell ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Allele Expression ◽  
Novel Transcripts

RNA sequencing (RNA-seq) is a powerful technology that identifies novel transcripts (coding, non-coding and splice variants), understands transcript structures, and estimates gene/allele expression. Biologists face specific challenges while designing RNA-seq experiments. The nature of these challenges lies in determining the total number of sequenced reads and replicates required for detecting marginally differentially expressed transcripts, and in determining the adequate number of lanes to use in a sequencing flow cell. Despite previous attempts to address these challenges, easily accessible and biologist-friendly mobile applications do not exist. Thus, we developed RNAtor, a mobile application for Android platforms, to aid biologists in correctly designing their RNA-seq experiments. The recommendations from RNAtor are based on simulations and real data.

scholarly journals RNAtor: an Android-based application for biologists to plan RNA sequencing experiments

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 997
Author(s):  
Shruti Kane ◽  
Himanshu Garg ◽  
Neeraja M. Krishnan ◽  
Aditya Singh ◽  
Binay Panda
Keyword(s):  
Rna Sequencing ◽  
Mobile Applications ◽  
Mobile Application ◽  
Splice Variants ◽  
Real Data ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Sample Analysis ◽  
Allele Expression ◽  
Novel Transcripts

RNA sequencing (RNA-seq) is a powerful technology that allows one to assess the RNA levels in a sample. Analysis of these levels can help in identifying novel transcripts (coding, non-coding and splice variants), understanding transcript structures, and estimating gene/allele expression. Biologists face specific challenges while designing RNA-seq experiments. The nature of these challenges lies in determining the total number of sequenced reads and technical replicates required for detecting marginally differentially expressed transcripts. Despite previous attempts to address these challenges, easily-accessible and biologist-friendly mobile applications do not exist. Thus, we developed RNAtor, a mobile application for Android platforms, to aid biologists in correctly designing their RNA-seq experiments. The recommendations from RNAtor are based on simulations and real data.

scholarly journals A Comprehensive RNA Sequencing Analysis of the Adeno-Associated Virus (AAV) Type 2 Transcriptome Reveals Novel AAV Transcripts, Splice Variants, and Derived Proteins

2015 ◽  
Vol 90 (3) ◽  
pp. 1278-1289 ◽  
Author(s):  
Catrin Stutika ◽  
Andreas Gogol-Döring ◽  
Laura Botschen ◽  
Mario Mietzsch ◽  
Stefan Weger ◽  
...  
Keyword(s):  
Life Cycle ◽  
Fusion Protein ◽  
Rna Sequencing ◽  
Splice Variants ◽  
Productive Infection ◽  
Minus Strand ◽  
Rna Seq ◽  
Adeno Associated Virus ◽  
Divergent Transcription ◽  
Productive Replication

ABSTRACTAdeno-associated virus (AAV) is recognized for its bipartite life cycle with productive replication dependent on coinfection with adenovirus (Ad) and AAV latency being established in the absence of a helper virus. The shift from latent to Ad-dependent AAV replication is mostly regulated at the transcriptional level. The current AAV transcription map displays highly expressed transcripts as found upon coinfection with Ad. So far, AAV transcripts have only been characterized on the plus strand of the AAV single-stranded DNA genome. The AAV minus strand is assumed not to be transcribed. Here, we apply Illumina-based RNA sequencing (RNA-Seq) to characterize the entire AAV2 transcriptome in the absence or presence of Ad. We find known and identify novel AAV transcripts, including additional splice variants, the most abundant of which leads to expression of a novel 18-kDa Rep/VP fusion protein. Furthermore, we identify for the first time transcription on the AAV minus strand with clustered reads upstream of the p5 promoter, confirmed by 5ˈ rapid amplification of cDNA ends and RNase protection assays. The p5 promoter displays considerable activity in both directions, a finding indicative of divergent transcription. Upon infection with AAV alone, low-level transcription of both AAV strands is detectable and is strongly stimulated upon coinfection with Ad.IMPORTANCENext-generation sequencing (NGS) allows unbiased genome-wide analyses of transcription profiles, used here for an in depth analysis of the AAV2 transcriptome during latency and productive infection. RNA-Seq analysis led to the discovery of novel AAV transcripts and splice variants, including a derived, novel 18-kDa Rep/VP fusion protein. Unexpectedly, transcription from the AAV minus strand was discovered, indicative of divergent transcription from the p5 promoter. This finding opens the door for novel concepts of the switch between AAV latency and productive replication. In the absence of a suitable animal model to study AAVin vivo, combinedin cellulaeandin silicostudies will help to forward the understanding of the unique, bipartite AAV life cycle.

A Two-Stage Poisson Model for Testing RNA-Seq Data

2011 ◽  
Vol 10 (1) ◽  
Author(s):  
Paul L. Auer ◽  
Rebecca W Doerge
Keyword(s):  
Rna Sequencing ◽  
Statistical Approach ◽  
Poisson Model ◽  
Real Data ◽  
Rna Seq ◽  
Sequencing Data ◽  
Sequencing Technology ◽  
Two Stage ◽  
Individual Gene ◽  
Unique Nature

RNA sequencing technology is providing data of unprecedented throughput, resolution, and accuracy. Although there are many different computational tools for processing these data, there are a limited number of statistical methods for analyzing them, and even fewer that acknowledge the unique nature of individual gene transcription. We introduce a simple and powerful statistical approach, based on a two-stage Poisson model, for modeling RNA sequencing data and testing for biologically important changes in gene expression. The advantages of this approach are demonstrated through simulations and real data applications.

scholarly journals SimFuse: A Novel Fusion Simulator for RNA Sequencing (RNA-Seq) Data

2015 ◽  
Vol 2015 ◽  
pp. 1-5 ◽  
Author(s):  
Yuxiang Tan ◽  
Yann Tambouret ◽  
Stefano Monti
Keyword(s):  
Sample Size ◽  
Rna Sequencing ◽  
High Throughput Sequencing ◽  
Performance Metrics ◽  
Simulated Data ◽  
Real Data ◽  
Rna Seq ◽  
Sequencing Data ◽  
Detection Algorithms ◽  
Fusion Detection

The performance evaluation of fusion detection algorithms from high-throughput sequencing data crucially relies on the availability of data with known positive and negative cases of gene rearrangements. The use of simulated data circumvents some shortcomings of real data by generation of an unlimited number of true and false positive events, and the consequent robust estimation of accuracy measures, such as precision and recall. Although a few simulated fusion datasets from RNA Sequencing (RNA-Seq) are available, they are of limited sample size. This makes it difficult to systematically evaluate the performance of RNA-Seq based fusion-detection algorithms. Here, we present SimFuse to address this problem. SimFuse utilizes real sequencing data as the fusions’ background to closely approximate the distribution of reads from a real sequencing library and uses a reference genome as the template from which to simulate fusions’ supporting reads. To assess the supporting read-specific performance, SimFuse generates multiple datasets with various numbers of fusion supporting reads. Compared to an extant simulated dataset, SimFuse gives users control over the supporting read features and the sample size of the simulated library, based on which the performance metrics needed for the validation and comparison of alternative fusion-detection algorithms can be rigorously estimated.

scholarly journals The Use of Mobile Applications for the Diagnosis and Treatment of Tumors in Orthopaedic Oncology – a Systematic Review

2021 ◽  
Vol 45 (11) ◽  
Author(s):  
J. Berger-Groch ◽  
M. Keitsch ◽  
A. Reiter ◽  
S. Weiss ◽  
KH. Frosch ◽  
...  
Keyword(s):  
Everyday Life ◽  
Mobile Applications ◽  
Mobile Application ◽  
Trauma Surgery ◽  
Soft Tissue Tumors ◽  
Orthopaedic Oncology ◽  
Musculoskeletal Tumors ◽  
Medical Evaluation ◽  
Trauma Surgeons ◽  
Google Play

AbstractThe use of smartphone apps is an essential part of everyday life. Mobile applications offer enormous opportunities for dealing with challenges in public health, and their number increases every day. This paper aims to review the existing literature on mobile applications in orthopaedic oncology and to summarize the current mobile applications for musculoskeletal tumors. A systematic literature review was conducted regarding articles on mobile applications in orthopaedic and trauma surgery. The focus was on identifying mobile applications that can be used in the treatment of patients with musculoskeletal tumors. Two reviewers independently assessed study eligibility, extracted data, and appraised methodological quality. In addition, the Apple App Store and Google Play Store were searched for suitable mobile applications. Ninety-one articles describing a mobile application in orthopaedic and trauma surgery were identified. Three articles focused on a mobile application for musculoskeletal tumors. Additionally, seven mobile applications were available in the App/Play Stores dealing with bone or soft tissue tumors in orthopaedic oncology without corresponding scientific articles. Increasing numbers of mobile applications are being developed in orthopaedic and trauma surgery. Currently, only three scientific articles on mobile applications in orthopaedic oncology are present, yet several more applications are available without scientific medical evaluation. Since mobile applications can facilitate the everyday life of orthopaedic and trauma surgeons, it is worthwhile to be aware of new developments in this field. A regular scientific evaluation of the subject is important in order to classify the significance of these applications.

scholarly journals Splatter: simulation of single-cell RNA sequencing data

2017 ◽  
Author(s):  
Luke Zappia ◽  
Belinda Phipson ◽  
Alicia Oshlack
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Real Data ◽  
Cell Types ◽  
Rna Seq ◽  
Sequencing Data ◽  
Sequencing Technologies ◽  
Simulation Based ◽  
Single Cell Rna Sequencing ◽  
Multiple Cell

AbstractAs single-cell RNA sequencing technologies have rapidly developed, so have analysis methods. Many methods have been tested, developed and validated using simulated datasets. Unfortunately, current simulations are often poorly documented, their similarity to real data is not demonstrated, or reproducible code is not available.Here we present the Splatter Bioconductor package for simple, reproducible and well-documented simulation of single-cell RNA-seq data. Splatter provides an interface to multiple simulation methods including Splat, our own simulation, based on a gamma-Poisson distribution. Splat can simulate single populations of cells, populations with multiple cell types or differentiation paths.

scholarly journals Mobile-Assisted Pronunciation Training: The Google Play Pronunciation and Phonetics Application

2020 ◽  
Vol 5 (2) ◽  
pp. 70-88
Author(s):  
Fitria Meisarah
Keyword(s):  
Mobile Applications ◽  
Mobile Application ◽  
Video Camera ◽  
App Store ◽  
Suprasegmental Features ◽  
English Pronunciation ◽  
Android App ◽  
The University ◽  
Google Play

Background:  Several obstacles to pronunciation have been proposed and urged students to practice pronunciation deliberately. Regardless of these problematic, mobile applications can be a great assistant in pronunciation training. However, considering that Google Play is the most prominent android app store with 227,970 instructional devices, it is challenging to find and select pronunciation and phonetics applications. Students should be conscious of their needs by recognizing the proper mobile application for pronunciation learning. This study explores the pronunciation applications utilized by students for pronunciation learning in and out of the classroom. Methodology: This study administered the data with paper reports and interviews accompanying students. This study involved 41 students who were taking a pronunciation and phonetics course at the University of Kutai Kartanegara Tenggarong. Findings: Nine such applications, as reviewed in this study, are divided into two categories: English pronunciation special purpose (EPSP) application and English dictionary assisted pronunciation (EDAP) application. Noteworthy findings were not all of the applications fulfill the content and design approaches such the suprasegmental features, audio playback, and video camera recorder. Conclusion: This study endeavors to have a critical look at four applications recommended after concerning the term of Mobile Assisted Pronunciation Training (MAPT). They are AV Phonetic, English Phonetic Pronunciation, Listening Practice, English Pronunciation developed by Kepham, and U-Dictionary to assist pronunciation learning in and out of the classroom. Keywords: Pronunciation and phonetics; mobile application; MAPT

scholarly journals Detection and removal of barcode swapping in single-cell RNA-seq data

2017 ◽  
Author(s):  
Jonathan A. Griffiths ◽  
Arianne C. Richard ◽  
Karsten Bach ◽  
Aaron T.L. Lun ◽  
John C Marioni
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Flow Cell ◽  
Rna Seq ◽  
Genomic Assays ◽  
Single Cell Rna Sequencing ◽  
Sequencing Studies ◽  
Continued Use ◽  
Statistical Approaches ◽  
Transcriptomic Studies

AbstractBarcode swapping results in the mislabeling of sequencing reads between multiplexed samples on the new patterned flow cell Illumina sequencing machines. This may compromise the validity of numerous genomic assays, especially for single-cell studies where many samples are routinely multiplexed together. The severity and consequences of barcode swapping for single-cell transcriptomic studies remain poorly understood. We have used two statistical approaches to robustly quantify the fraction of swapped reads in each of two plate-based single-cell RNA sequencing datasets. We found that approximately 2.5% of reads were mislabeled between samples on the HiSeq 4000 machine, which is lower than previous reports. We observed no correlation between the swapped fraction of reads and the concentration of free barcode across plates. Furthermore, we have demonstrated that barcode swapping may generate complex but artefactual cell libraries in droplet-based single-cell RNA sequencing studies. To eliminate these artefacts, we have developed an algorithm to exclude individual molecules that have swapped between samples in 10X Genomics experiments, exploiting the combinatorial complexity present in the data. This permits the continued use of cutting-edge sequencing machines for droplet-based experiments while avoiding the confounding effects of barcode swapping.

Dark Skin Representation within Mobile Applications for Dermatology Education: an Observational Analysis (Preprint)

2021 ◽  
Author(s):  
Rhys Dore
Keyword(s):  
Health Professionals ◽  
Ethnic Diversity ◽  
Mobile Applications ◽  
Mobile Application ◽  
Application Technology ◽  
Dark Skin ◽  
Acral Lentiginous Melanoma ◽  
Keloid Scarring ◽  
Google Play

BACKGROUND Ethnic diversity in dermatology has previously been neglected within educational curricula. This has previously been demonstrated within many established dermatology textbooks. Many urban populations find their communities becoming increasingly diverse and medical education must match these changes. The increasing use and modernisation of mobile technology in health education may represent an avenue to provide increasingly diverse knowledge related to dermatology in dark skin populations. OBJECTIVE To review the representation of dark skin photography and diseases in dermatological educational resources provided via mobile application technology. METHODS Mobile applications related to ‘dermatology’ were reviewed within the Google Play Store. Only original mobile applications made for education of medical students or health professionals were analysed. Photographic depictions of dermatological conditions were categorised according to Fitzpatrick type 1-4, Fitzpatrick type 5-6, or uncertain. Additionally, mobile applications were reviewed for information regarding four conditions more common in people with darker skin: central centrifugal cicatricial alopecia, melasma, acral lentiginous melanoma, and keloid scarring. RESULTS Of 200 mobile applications reviewed, 12 were included within the analysis. In total 3755 in-app photographs were categorised into Fitzpatrick type 1-4 (3398 photographs, 90.5%), Fitzpatrick type 5-6 (245 photographs, 6.5%), or uncertain (112 photographs, 3.0%). The degree of photographs showing Fitzpatrick 5-6 ranged from 0.7% to 17.6% between the different mobile applications. This was not significantly different from results previously gained from photographic depictions in dermatology textbooks. Furthermore, the number of mobile applications presenting overt educational information regarding the four conditions reviewed varied considerably; central centrifugal cicatricial alopecia (1 application, 8.3%), melasma (5 applications, 41.7%), acral lentiginous melanoma (4 applications, 33.3%), and keloid scarring (6 applications, 50%). No mobile applications contained information for all four conditions. CONCLUSIONS There is limited depiction of dermatological conditions in darker skin tones within mobile applications aimed at educational students and professionals in dermatology.

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