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- Garbulowski, Mateusz, et al.
(författare)
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Interpretable Machine Learning Reveals Dissimilarities Between Subtypes of Autism Spectrum Disorder
- 2021
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Ingår i: Frontiers in Genetics. - : Frontiers Media S.A.. - 1664-8021. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Autism spectrum disorder (ASD) is a heterogeneous neuropsychiatric disorder with a complex genetic background. Analysis of altered molecular processes in ASD patients requires linear and nonlinear methods that provide interpretable solutions. Interpretable machine learning provides legible models that allow explaining biological mechanisms and support analysis of clinical subgroups. In this work, we investigated several case-control studies of gene expression measurements of ASD individuals. We constructed a rule-based learning model from three independent datasets that we further visualized as a nonlinear gene-gene co-predictive network. To find dissimilarities between ASD subtypes, we scrutinized a topological structure of the network and estimated a centrality distance. Our analysis revealed that autism is the most severe subtype of ASD, while pervasive developmental disorder-not otherwise specified and Asperger syndrome are closely related and milder ASD subtypes. Furthermore, we analyzed the most important ASD-related features that were described in terms of gene co-predictors. Among others, we found a strong co-predictive mechanism between EMC4 and TMEM30A, which may suggest a co-regulation between these genes. The present study demonstrates the potential of applying interpretable machine learning in bioinformatics analyses. Although the proposed methodology was designed for transcriptomics data, it can be applied to other omics disciplines.
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| 2. |
- Klar, Joakim, PhD, 1974-, et al.
(författare)
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Whole genome sequencing of familial isolated oesophagus atresia uncover shared structural variants
- 2020
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Ingår i: BMC Medical Genomics. - : Springer Science and Business Media LLC. - 1755-8794. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundOesophageal atresia (OA) is a life-threatening developmental defect characterized by a lost continuity between the upper and lower oesophagus. The most common form is a distal connection between the trachea and the oesophagus, i.e. a tracheoesophageal fistula (TEF). The condition may be part of a syndrome or occurs as an isolated feature. The recurrence risk in affected families is increased compared to the population-based incidence suggesting contributing genetic factors.MethodsTo gain insight into gene variants and genes associated with isolated OA we conducted whole genome sequencing on samples from three families with recurrent cases affected by congenital and isolated TEF.ResultsWe identified a combination of single nucleotide variants (SNVs), splice site variants (SSV) and structural variants (SV) annotated to altogether 100 coding genes in the six affected individuals.ConclusionThis study highlights rare SVs among candidate gene variants in our individuals with OA and provides a gene framework for further investigations of genetic factors behind this malformation.
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| 3. |
- Shebanits, Kateryna, et al.
(författare)
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Copy number determination of the gene for the human pancreatic polypeptide receptor NPY4R using read depth analysis and droplet digital PCR.
- 2019
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Ingår i: BMC Biotechnology. - : Springer Science and Business Media LLC. - 1472-6750. ; 19
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Tidskriftsartikel (refereegranskat)abstract
- Background: Copy number variation (CNV) plays an important role in human genetic diversity and has been associated with multiple complex disorders. Here we investigate a CNV on chromosome 10q11.22 that spans NPY4R, the gene for the appetite-regulating pancreatic polypeptide receptor Y4. This genomic region has been challenging to map due to multiple repeated elements and its precise organization has not yet been resolved. Previous studies using microarrays were interpreted to show that the most common copy number was 2 per genome.Results: We have investigated 18 individuals from the 1000 Genomes project using the well-established method of read depth analysis and the new droplet digital PCR (ddPCR) method. We find that the most common copy number for NPY4R is 4. The estimated number of copies ranged from three to seven based on read depth analyses with Control-FREEC and CNVnator, and from four to seven based on ddPCR. We suggest that the difference between our results and those published previously can be explained by methodological differences such as reference gene choice, data normalization and method reliability. Three high-quality archaic human genomes (two Neanderthal and one Denisova) display four copies of the NPY4R gene indicating that a duplication occurred prior to the human-Neanderthal/Denisova split.Conclusions: We conclude that ddPCR is a sensitive and reliable method for CNV determination, that it can be used for read depth calibration in CNV studies based on already available whole-genome sequencing data, and that further investigation of NPY4R copy number variation and its consequences are necessary due to the role of Y4 receptor in food intake regulation.
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