Mukautuva moniulotteisten poikkeavuuksien tunnistaminen reaaliaikaisesti

Data volumes are growing at a high speed as data emerges from millions of devices. This brings an increasing need for streaming analytics, processing and analysing the data in a record-by-record manner. In this work a comprehensive literature review on streaming analytics is presented, focusing on detecting anomalous behaviour. Challenges and approaches for streaming analytics are discussed. Different ways of determining and identifying anomalies are shown and a large number of anomaly detection methods for streaming data are presented. Also, existing software platforms and solutions for streaming analytics are presented. Based on the literature survey I chose one method for further investigation, namely Lightweight on-line detector of anomalies (LODA). LODA is designed to detect anomalies in real time from even high-dimensional data. In addition, it is an adaptive method and updates the model on-line. LODA was tested both on synthetic and real data sets. This work shows how to define the parameters used with LODA. I present a couple of improvement ideas to LODA and show that three of them bring important benefits. First, I show a simple addition to handle special cases such that it allows computing an anomaly score for all data points. Second, I show cases where LODA fails due to lack of data preprocessing. I suggest preprocessing schemes for streaming data and show that using them improves the results significantly, and they require only a small subset of the data for determining preprocessing parameters. Third, since LODA only gives anomaly scores, I suggest thresholding techniques to define anomalies. This work shows that the suggested techniques work fairly well compared to theoretical best performance. This makes it possible to use LODA in real streaming analytics situations.Datan määrä kasvaa kovaa vauhtia miljoonien laitteiden tuottaessa dataa. Tämä luo kasvavan tarpeen datan prosessoinnille ja analysoinnille reaaliaikaisesti. Tässä työssä esitetään kattava kirjallisuuskatsaus reaaliaikaisesta analytiikasta keskittyen anomalioiden tunnistukseen. Työssä pohditaan reaaliaikaiseen analytiikkaan liittyviä haasteita ja lähestymistapoja. Työssä näytetään erilaisia tapoja määrittää ja tunnistaa anomalioita sekä esitetään iso joukko menetelmiä reaaliaikaiseen anomalioiden tunnistukseen. Työssä esitetään myös reaaliaika-analytiikkaan tarkoitettuja ohjelmistoalustoja ja -ratkaisuja. Kirjallisuuskatsauksen perusteella työssä on valittu yksi menetelmä lähempään tutkimukseen, nimeltään Lightweight on-line detector of anomalies (LODA). LODA on suunniteltu tunnistamaan anomalioita reaaliaikaisesti jopa korkeaulotteisesta datasta. Lisäksi se on adaptiivinen menetelmä ja päivittää mallia reaaliaikaisesti. Työssä testattiin LODAa sekä synteettisellä että oikealla datalla. Työssä näytetään, miten LODAa käytettäessä kannattaa valita mallin parametrit. Työssä esitetään muutama kehitysehdotus LODAlle ja näytetään kolmen kehitysehdotuksen merkittävä hyöty. Ensinnäkin, näytetään erikoistapauksia varten yksinkertainen lisäys, joka mahdollistaa anomaliapisteytyksen laskemisen jokaiselle datapisteelle. Toiseksi, työssä näytetään tapauksia, joissa LODA epäonnistuu, kun dataa ei ole esikäsitelty. Työssä ehdotetaan reaaliaikaisesti prosessoitavalle datalle soveltuvia esikäsittelymenetelmiä ja osoitetaan, että niiden käyttö parantaa tuloksia merkittävästi, samalla käyttäen vain pientä osaa datasta esikäsittelyparametrien määrittämiseen. Kolmanneksi, koska LODA antaa datapisteille vain anomaliapisteytyksen, työssä on ehdotettu, miten sopivat raja-arvot anomalioiden tunnistukseen voitaisiin määrittää. Työssä on osoitettu, että nämä ehdotukset toimivat melko hyvin verrattuna teoreettisesti parhaaseen mahdolliseen tulokseen. Tämä mahdollistaa LODAn käytön oikeissa reaaliaika-analytiikkatapauksissa

Diagnostic yield of genetic testing in a heterogeneous cohort of 1376 HCM patients

Background Genetic testing in hypertrophic cardiomyopathy (HCM) is a published guideline-based recommendation. The diagnostic yield of genetic testing and corresponding HCM-associated genes have been largely documented by single center studies and carefully selected patient cohorts. Our goal was to evaluate the diagnostic yield of genetic testing in a heterogeneous cohort of patients with a clinical suspicion of HCM, referred for genetic testing from multiple centers around the world. Methods A retrospective review of patients with a suspected clinical diagnosis of HCM referred for genetic testing at Blueprint Genetics was undertaken. The analysis included syndromic, myopathic and metabolic etiologies. Genetic test results and variant classifications were extracted from the database. Variants classified as pathogenic (P) or likely pathogenic (LP) were considered diagnostic. Results A total of 1376 samples were analyzed. Three hundred and sixty-nine tests were diagnostic (26.8%); 373 P or LP variants were identified. Only one copy number variant was identified. The majority of diagnostic variants involved genes encoding the sarcomere (85.0%) followed by 4.3% of diagnostic variants identified in the RASopathy genes. Two percent of diagnostic variants were in genes associated with a cardiomyopathy other than HCM or an inherited arrhythmia. Clinical variables that increased the likelihood of identifying a diagnostic variant included: an earlier age at diagnosis (p <0.0001), a higher maximum wall thickness (MWT) (p <0.0001), a positive family history (p <0.0001), the absence of hypertension (p = 0.0002), and the presence of an implantable cardioverter-defibrillator (ICD) (p = 0.0004). Conclusion The diagnostic yield of genetic testing in this heterogeneous cohort of patients with a clinical suspicion of HCM is lower than what has been reported in well-characterized patient cohorts. We report the highest yield of diagnostic variants in the RASopathy genes identified in a laboratory cohort of HCM patients to date. The spectrum of genes implicated in this unselected cohort highlights the importance of pre-and post-test counseling when offering genetic testing to the broad HCM population.Peer reviewe

GRINL1A Complex Transcription Unit Containing GCOM1, MYZAP, and POLR2M Genes Associates with Fully Penetrant Recessive Dilated Cardiomyopathy

Background: Familial dilated cardiomyopathy (DCM) is a monogenic disorder typically inherited in an autosomal dominant pattern. We have identified two Finnish families with familial cardiomyopathy that is not explained by a variant in any previously known cardiomyopathy gene. We describe the cardiac phenotype related to homozygous truncating GCOM1 variants.Methods and Results: This study included two probands and their relatives. All the participants are of Finnish ethnicity. Whole-exome sequencing was used to test the probands; bi-directional Sanger sequencing was used to identify the GCOM1 variants in probands' family members. Clinical evaluation was performed, medical records and death certificates were obtained. Immunohistochemical analysis of myocardial samples was conducted. A homozygous GCOM1 variant was identified altogether in six individuals, all considered to be affected. None of the nine heterozygous family members fulfilled any cardiomyopathy criteria. Heart failure was the leading clinical feature, and the patients may have had a tendency for atrial arrhythmias.Conclusions: This study demonstrates the significance of GCOM1 variants as a cause of human cardiomyopathy and highlights the importance of searching for new candidate genes when targeted gene panels do not yield a positive outcome.Peer reviewe

Prevalence of RPGR-Mediated Retinal Dystrophy in an Unselected Cohort of Over 5000 Patients

Purpose: Comprehensive genetic testing for inherited retinal dystrophy (IRD) is challenged by difficult-to-sequence genomic regions, which are often mutational hotspots, such as RPGR ORF15. The purpose of this study was to evaluate the diagnostic contribution of RPGR variants in an unselected IRD patient cohort referred for testing in a clinical diagnostic laboratory. Methods: A total of 5201 consecutive patients were analyzed with a clinically validated next-generation sequencing (NGS)-based assay, including the difficult-to-sequence RPGR ORF15 region. Copy number variant (CNV) detection from NGS data was included. Variant interpretation was performed per the American College of Medical Genetics and Genomics guidelines. Results: A confirmed molecular diagnosis in RPGR was found in 4.5% of patients, 24.0% of whom were females. Variants in ORF15 accounted for 74% of the diagnoses; 29% of the diagnostic variants were in the most difficult-to-sequence central region of ORF15 (c.2470-3230). Truncating variants made up the majority (91%) of the diagnostic variants. CNVs explained 2% of the diagnostic cases, of which 80% were one- or two-exon deletions outside of ORF15. Conclusions: Our findings indicate that high-throughput, clinically validated NGS-based testing covering the difficult-to-sequence region of ORF15, in combination with high-resolution CNV detection, can help to maximize the diagnostic yield for patients with IRD. Translational Relevance: These results demonstrate an accurate and scalable method for the detection of RPGR-related variants, including the difficult-to-sequence ORF15 hotspot, which is relevant given current and emerging therapeutic opportunities.Peer reviewe

Diagnostic yield of genetic testing in a multinational heterogeneous cohort of 2088 DCM patients

BackgroundFamilial dilated cardiomyopathy (DCM) causes heart failure and may lead to heart transplantation. DCM is typically a monogenic disorder with autosomal dominant inheritance. Currently disease-causing variants have been reported in over 60 genes that encode proteins in sarcomeres, nuclear lamina, desmosomes, cytoskeleton, and mitochondria. Over half of the patients undergoing comprehensive genetic testing are left without a molecular diagnosis even when patient selection follows strict DCM criteria.Methods and resultsThis study was a retrospective review of patients referred for genetic testing at Blueprint Genetics due to suspected inherited DCM. Next generation sequencing panels included 23–316 genes associated with cardiomyopathies and other monogenic cardiac diseases. Variants were considered diagnostic if classified as pathogenic (P) or likely pathogenic (LP). Of the 2,088 patients 514 (24.6%) obtained a molecular diagnosis; 534 LP/P variants were observed across 45 genes, 2.7% (14/514) had two diagnostic variants in dominant genes. Nine copy number variants were identified: two multigene and seven intragenic. Diagnostic variants were observed most often in TTN (45.3%), DSP (6.7%), LMNA (6.7%), and MYH7 (5.2%). Clinical characteristics independently associated with molecular diagnosis were: a lower age at diagnosis, family history of DCM, paroxysmal atrial fibrillation, absence of left bundle branch block, and the presence of an implantable cardioverter-defibrillator.ConclusionsPanel testing provides good diagnostic yield in patients with clinically suspected DCM. Causative variants were identified in 45 genes. In minority, two diagnostic variants were observed in dominant genes. Our results support the use of genetic panels in clinical settings in DCM patients with suspected genetic etiology

Coredynamik von HTR unter ATWS- und Stoerfallbedingungen

SIGLECopy held by FIZ Karlsruhe; available from UB/TIB Hannover / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

Opt‐in for secondary findings as part of diagnostic whole‐exome sequencing: Real‐life experience from an international diagnostic laboratory

Abstract Background Discussion about the risks and benefits of offering secondary findings as part of genome‐wide diagnostics lacks real‐life data. We studied the opt‐in decisions of patients/families referred to whole exome study (WES) in Blueprint Genetics (BpG), a genetic testing company with customers in over 70 countries to receive secondary findings. Based on the American College of Medical Genetics (ACMG) recommendations for reporting secondary findings, BpG offered testing of specific actionable genes without additional charge for specimens submitted to WES diagnostics. Methods Individuals could opt‐in for a secondary findings analysis by using a separate electronic consent form. Data from BpG database of electronic consent forms was used for the analysis. Results During the selected study period there were 3263 WES referrals, from which 2012 were index patients. About half of the individuals (50.4%) opted in to receiving secondary findings. Of patients who opted in, a secondary finding was detected for 2.7%, similar to other studies. We detected huge differences relating to opt‐in between individuals from different countries; for instance, 90% of the 41 patients and their family members in Romania opted to receive secondary findings, while none of the 98 patients in Luxembourg chose that option. Conclusion Differences between sexes or between children and adults were small. This data offers one view to the interest of patients and family members to opt in to receiving secondary findings. Research is needed to understand the influence of factors like age, education etc. and possible participation in pre‐test counseling to receiving/not receiving secondary findings