scholarly journals Oncologists’ Use of Genomic Sequencing Data to Inform Clinical Management

2018 ◽  
pp. 1-13
Author(s):  
Michele C. Gornick ◽  
Erin Cobain ◽  
Lan Q. Le ◽  
Natalie Bartnik ◽  
Elena Stoffel ◽  
...  
Keyword(s):  
Medical Record ◽  
Medical Records ◽  
Clinical Management ◽  
Response Rate ◽  
Sequencing Data ◽  
Prospective Survey ◽  
Actual Change ◽  
Tumor Sequencing ◽  
Survey Responses ◽  
Generation Sequencing

Purpose To determine whether oncologists intended to change treatment as a result of tumor sequencing, and subsequently, whether patients experienced an alteration of clinical management or derived clinical benefit. Patients and Methods A prospective survey of oncologists referring adult patients with rare, advanced, or refractory cancer to the Michigan Oncology Sequencing program was conducted from June 2014 to March 2015 to assess the use of and intent to disclose sequencing findings. Oncologists’ responses were compared with the referred patients’ self-reported survey responses, and a content analysis of disclosure documented in the medical record was performed. Medical records were reviewed retrospectively to determine if clinical management was informed or changed by sequencing results. Results Oncologists (response rate, 93%) referring 112 consecutive patients were surveyed. Medical records of patients were reviewed for changes in clinical management on the basis of sequencing findings. Oncologists intended to change the treatment of 22% of patients (n = 24) on the basis of sequencing findings. Of these patients, 37.5% (n = 9) had an actual change in clinical management. Thirty-four patients with postsequencing survey data reported that a results disclosure discussion did not occur, despite documentation of disclosure by the physician in the medical record. Conclusions Findings demonstrate that many oncologists view next-generation sequencing results to be potentially valuable in directing subsequent therapy for their patients; however, barriers in communicating results to patients and implementing them in clinical management remain.

Perencanaan Arsitektur Sistem Informasi Rekam Medis dan Monitoring Gizi Buruk Berbasis Cloud Computing (Studi Kasus: Dinas Kesehatan Propinsi Jawa Barat)

2017 ◽  
Vol 8 (3) ◽  
Author(s):  
Ova Nurisma Putra
Keyword(s):  
Cloud Computing ◽  
Information System ◽  
Medical Record ◽  
Medical Records ◽  
Monitoring And Evaluation ◽  
Open Group ◽  
Development Method ◽  
Information System Architecture ◽  
Architecture Framework ◽  
Architecture Development

Abstract. West Java Provincial Health Office still faces difficulties in managing information, especially in medical records. Recording and reporting of malnutrition are still done in some stages starting from collecting data from village midwives, puskesmas, Regency/City Health Office then Provincial Health Office and forwarded to the the central office. It is necessary to manage information through service system by utilizing Cloud Computing based on information technology. This research uses The Open Group Architecture Framework (TOGAF) approach in Architecture Development Method (ADM), from Architecture Capability Iteration to  Architecture Development Iteration. Monitoring and Evaluation (M & E) are two integrated activities in the context of controlling a program. The results of this research are planning a medical record information system architecture and monitoring malnutrition based on Cloud Computing with the name of M2Rec (Medical Record and Monitoring) in the form of integrated recommendation and development between current information system and proposed information system architecture.Keywords: togaf adm, medical record and monitoring, cloud computing Abstrak. Perencanaan Arsitektur Sistem Informasi Rekam Medis dan Monitoring Gizi Buruk Berbasis Cloud Computing. Dinas Kesehatan Propinsi Jawa Barat masih mengalami kesulitan dalam pengelolaan informasi yang baik, terutama pada proses rekam medis, pencatatan dan pelaporan gizi buruk masih dilakukan secara bertingkat mulai pengumpulan data dari bidan desa, puskesmas, Dinas Kesehatan Kabupaten/Kota kemudian Dinas Kesehatan Propinsi dan diteruskan ke pusat. Sehingga perlu diupayakan pengelolaan informasi melalui sistem pelayanan dengan memanfaatkan teknologi informasi berbasis Cloud Computing. Penelitian ini menggunakan pendekatan framework The Open Group Architecture Framework (TOGAF) Architecture Development Method (ADM), yaitu iterasi ke satu pada Architecture Capability Iteration daniterasi ke dua pada Architecture Development Iteration. Monitoring dan Evaluasi (M&E) merupakan dua kegiatan terpadu dalam rangka pengendalian suatu program. Hasil dari penelitian ini adalah perencanaan arsitektur sistem informasi rekam medis dan monitoring gizi buruk berbasis Cloud Computing dengan nama M2Rec (Medical Record and Monitoring) yang berupa rekomendasi integrasi dan pengembangan antara sistem informasi berjalan saat ini dengan arsitektur sistem informasi yang diusulkan.Kata kunci: togaf adm, medical record and monitoring, cloud computing.

Analisis Unsur Manajemen dalam Pengolahan Rekam Medis di Rumah Sakit TNI AU Lanud Roesmin Nurjadin

2018 ◽  
Vol 1 (1) ◽  
pp. 20-25
Author(s):  
Henny Maria Ulfa
Keyword(s):  
Medical Record ◽  
Medical Records ◽  
Processing Method ◽  
Qualitative Approach ◽  
Check List ◽  
Training Material ◽  
Patient Medical Record ◽  
Qualitative Descriptive ◽  
Material Element ◽  
Descriptive Method

Hospitals must conduct a medical record activities according to Permenkes NO.269 / MENKES / PER / III / 2008 about Medical Record, to achieve the purpose of medical record processing required 5 management elements are: man, money, material, machine, and method. The medical record processing that has been implemented at the Hospital TNI AU LANUD Roesmin Nurjadin that is coding, coding only done for BPJS patients whose conducted by the officer with education background of D3 nursing, it be impacted to the storage part is wrong save and cannot found patient medical record file because are not returned. The purpose of this research is to know the element of management in the processing of medical records at the Hospital TNI AU LANUD Roesmin Nurjadin. This research is done by Qualitative descriptive method, Qualitative approach, instrument of data collection of interview guidance, observation guidance, check list register, and stationery, number of informant 6 people with inductive way data analysis. The result of this research found that Mans elements only amounts to 2 people so that officers work concurrently and have never attended training, material element and machines elements of medical record processing not yet use SIMRS and tracer, while processing method elements follow existing habits and follow the policy of hospital that is POP organization. Keywords: Management elements, medical record processing

IsoDetect: Detection of splice isoforms from third generation long reads based on short feature sequences

2020 ◽  
Vol 15 ◽  
Author(s):  
Hongdong Li ◽  
Wenjing Zhang ◽  
Yuwen Luo ◽  
Jianxin Wang
Keyword(s):  
Sequence Similarity ◽  
Detection Methods ◽  
Sequence Information ◽  
Third Generation ◽  
Sequencing Data ◽  
Splice Isoforms ◽  
Third Generation Sequencing ◽  
Long Reads ◽  
Feature Sequence ◽  
Generation Sequencing

Aims: Accurately detect isoforms from third generation sequencing data. Background: Transcriptome annotation is the basis for the analysis of gene expression and regulation. The transcriptome annotation of many organisms such as humans is far from incomplete, due partly to the challenge in the identification of isoforms that are produced from the same gene through alternative splicing. Third generation sequencing (TGS) reads provide unprecedented opportunity for detecting isoforms due to their long length that exceeds the length of most isoforms. One limitation of current TGS reads-based isoform detection methods is that they are exclusively based on sequence reads, without incorporating the sequence information of known isoforms. Objective: Develop an efficient method for isoform detection. Method: Based on annotated isoforms, we propose a splice isoform detection method called IsoDetect. First, the sequence at exon-exon junction is extracted from annotated isoforms as the “short feature sequence”, which is used to distinguish different splice isoforms. Second, we aligned these feature sequences to long reads and divided long reads into groups that contain the same set of feature sequences, thereby avoiding the pair-wise comparison among the large number of long reads. Third, clustering and consensus generation are carried out based on sequence similarity. For the long reads that do not contain any short feature sequence, clustering analysis based on sequence similarity is performed to identify isoforms. Result: Tested on two datasets from Calypte Anna and Zebra Finch, IsoDetect showed higher speed and compelling accuracy compared with four existing methods. Conclusion: IsoDetect is a promising method for isoform detection. Other: This paper was accepted by the CBC2019 conference.

scholarly journals miR-208b Reduces the Expression of Kcnj5 in a Cardiomyocyte Cell Line

Biomedicines ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 719
Author(s):  
Julia Hupfeld ◽  
Maximilian Ernst ◽  
Maria Knyrim ◽  
Stephanie Binas ◽  
Udo Kloeckner ◽  
...  
Keyword(s):  
Untranslated Region ◽  
Electrical Remodeling ◽  
Sequencing Data ◽  
Western Blots ◽  
Cardiovascular Pathology ◽  
Hypertrophic Response ◽  
Channel Dependent ◽  
Cardiac Excitation ◽  
The Impact ◽  
Generation Sequencing

MicroRNAs (miRs) contribute to different aspects of cardiovascular pathology, among them cardiac hypertrophy and atrial fibrillation. Cardiac miR expression was analyzed in a mouse model with structural and electrical remodeling. Next-generation sequencing revealed that miR-208b-3p was ~25-fold upregulated. Therefore, the aim of our study was to evaluate the impact of miR-208b on cardiac protein expression. First, an undirected approach comparing whole RNA sequencing data to miR-walk 2.0 miR-208b 3′-UTR targets revealed 58 potential targets of miR-208b being regulated. We were able to show that miR-208b mimics bind to the 3′ untranslated region (UTR) of voltage-gated calcium channel subunit alpha1 C and Kcnj5, two predicted targets of miR-208b. Additionally, we demonstrated that miR-208b mimics reduce GIRK1/4 channel-dependent thallium ion flux in HL-1 cells. In a second undirected approach we performed mass spectrometry to identify the potential targets of miR-208b. We identified 40 potential targets by comparison to miR-walk 2.0 3′-UTR, 5′-UTR and CDS targets. Among those targets, Rock2 and Ran were upregulated in Western blots of HL-1 cells by miR-208b mimics. In summary, miR-208b targets the mRNAs of proteins involved in the generation of cardiac excitation and propagation, as well as of proteins involved in RNA translocation (Ran) and cardiac hypertrophic response (Rock2).

scholarly journals NGSremix: A software tool for estimating pairwise relatedness between admixed individuals from next-generation sequencing data

2021 ◽  
Author(s):  
Anne Krogh Nøhr ◽  
Kristian Hanghøj ◽  
Genis Garcia Erill ◽  
Zilong Li ◽  
Ida Moltke ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Genetic Research ◽  
Likelihood Estimation ◽  
Software Tool ◽  
Estimation Methods ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Ngs Data ◽  
Generation Sequencing

Abstract Estimation of relatedness between pairs of individuals is important in many genetic research areas. When estimating relatedness, it is important to account for admixture if this is present. However, the methods that can account for admixture are all based on genotype data as input, which is a problem for low-depth next-generation sequencing (NGS) data from which genotypes are called with high uncertainty. Here we present a software tool, NGSremix, for maximum likelihood estimation of relatedness between pairs of admixed individuals from low-depth NGS data, which takes the uncertainty of the genotypes into account via genotype likelihoods. Using both simulated and real NGS data for admixed individuals with an average depth of 4x or below we show that our method works well and clearly outperforms all the commonly used state-of-the-art relatedness estimation methods PLINK, KING, relateAdmix, and ngsRelate that all perform quite poorly. Hence, NGSremix is a useful new tool for estimating relatedness in admixed populations from low-depth NGS data. NGSremix is implemented in C/C ++ in a multi-threaded software and is freely available on Github https://github.com/KHanghoj/NGSremix.

scholarly journals Accucopy: accurate and fast inference of allele-specific copy number alterations from low-coverage low-purity tumor sequencing data

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Xinping Fan ◽  
Guanghao Luo ◽  
Yu S. Huang
Keyword(s):  
Copy Number ◽  
Bayesian Learning ◽  
Kernel Smoothing ◽  
Gaussian Mixture ◽  
Copy Number Alterations ◽  
Sequencing Data ◽  
Copy Numbers ◽  
Allele Specific ◽  
Tumor Sequencing ◽  
Low Coverage

Abstract Background Copy number alterations (CNAs), due to their large impact on the genome, have been an important contributing factor to oncogenesis and metastasis. Detecting genomic alterations from the shallow-sequencing data of a low-purity tumor sample remains a challenging task. Results We introduce Accucopy, a method to infer total copy numbers (TCNs) and allele-specific copy numbers (ASCNs) from challenging low-purity and low-coverage tumor samples. Accucopy adopts many robust statistical techniques such as kernel smoothing of coverage differentiation information to discern signals from noise and combines ideas from time-series analysis and the signal-processing field to derive a range of estimates for the period in a histogram of coverage differentiation information. Statistical learning models such as the tiered Gaussian mixture model, the expectation–maximization algorithm, and sparse Bayesian learning were customized and built into the model. Accucopy is implemented in C++ /Rust, packaged in a docker image, and supports non-human samples, more at http://www.yfish.org/software/. Conclusions We describe Accucopy, a method that can predict both TCNs and ASCNs from low-coverage low-purity tumor sequencing data. Through comparative analyses in both simulated and real-sequencing samples, we demonstrate that Accucopy is more accurate than Sclust, ABSOLUTE, and Sequenza.

scholarly journals Automatic Placement of Genomic Research Results in Medical Records: Do Researchers Have a Duty? Should Participants Have a Choice?

2015 ◽  
Vol 43 (4) ◽  
pp. 827-842
Author(s):  
Anya E.R. Prince ◽  
John M. Conley ◽  
Arlene M. Davis ◽  
Gabriel Lázaro-Muñoz ◽  
R. Jean Cadigan
Keyword(s):  
Medical Record ◽  
Medical Records ◽  
Genomic Research ◽  
Research Results ◽  
Research Participants ◽  
Difficult Question ◽  
Automatic Placement ◽  
Study Participants ◽  
Research Studies

The growing practice of returning individual results to research participants has revealed a variety of interpretations of the multiple and sometimes conflicting duties that researchers may owe to participants. One particularly difficult question is the nature and extent of a researcher’s duty to facilitate a participant’s follow-up clinical care by placing research results in the participant’s medical record. The question is especially difficult in the context of genomic research. Some recent genomic research studies — enrolling patients as participants — boldly address the question with protocols dictating that researchers place research results directly into study participants’ existing medical records, without participant consent. Such privileging of researcher judgment over participant choice may be motivated by a desire to discharge a duty that researchers perceive themselves as owing to participants. However, the underlying ethical, professional, legal, and regulatory duties that would compel or justify this action have not been fully explored.

scholarly journals recoup: flexible and versatile signal visualization from next generation sequencing

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Panagiotis Moulos
Keyword(s):  
Next Generation Sequencing ◽  
Next Generation Sequencing Data ◽  
Special Focus ◽  
Next Generation ◽  
Sequencing Data ◽  
User Friendliness ◽  
Computational Environment ◽  
Level Data ◽  
Data Signal ◽  
Generation Sequencing

Abstract Background The relentless continuing emergence of new genomic sequencing protocols and the resulting generation of ever larger datasets continue to challenge the meaningful summarization and visualization of the underlying signal generated to answer important qualitative and quantitative biological questions. As a result, the need for novel software able to reliably produce quick, comprehensive, and easily repeatable genomic signal visualizations in a user-friendly manner is rapidly re-emerging. Results recoup is a Bioconductor package for quick, flexible, versatile, and accurate visualization of genomic coverage profiles generated from Next Generation Sequencing data. Coupled with a database of precalculated genomic regions for multiple organisms, recoup offers processing mechanisms for quick, efficient, and multi-level data interrogation with minimal effort, while at the same time creating publication-quality visualizations. Special focus is given on plot reusability, reproducibility, and real-time exploration and formatting options, operations rarely supported in similar visualization tools in a profound way. recoup was assessed using several qualitative user metrics and found to balance the tradeoff between important package features, including speed, visualization quality, overall friendliness, and the reusability of the results with minimal additional calculations. Conclusion While some existing solutions for the comprehensive visualization of NGS data signal offer satisfying results, they are often compromised regarding issues such as effortless tracking of processing and preparation steps under a common computational environment, visualization quality and user friendliness. recoup is a unique package presenting a balanced tradeoff for a combination of assessment criteria while remaining fast and friendly.

Sign in / Sign up

Export Citation Format

Share Document