AIMC Topic: Exome Sequencing

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Polishing copy number variant calls on exome sequencing data via deep learning.

Genome research Jun 13, 2022
Accurate and efficient detection of copy number variants (CNVs) is of critical importance owing to their significant association with complex genetic diseases. Although algorithms that use whole-genome sequencing (WGS) data provide stable results wit...
Algorithms Reproducibility of Results High-Throughput Nucleotide Sequencing Exome Sequencing Exome Deep Learning DNA Copy Number Variations
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Recommendations for next generation sequencing data reanalysis of unsolved cases with suspected Mendelian disorders: A systematic review and meta-analysis.

Genetics in medicine : official journal of the American College of Medical Genetics May 14, 2022
PURPOSE: The study aimed to determine the diagnostic yield, optimal timing, and methodology of next generation sequencing data reanalysis in suspected Mendelian disorders.
Exome Sequencing Humans Artificial Intelligence High-Throughput Nucleotide Sequencing
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One Cell At a Time (OCAT): a unified framework to integrate and analyze single-cell RNA-seq data.

Genome biology Apr 20, 2022
Integrative analysis of large-scale single-cell RNA sequencing (scRNA-seq) datasets can aggregate complementary biological information from different datasets. However, most existing methods fail to efficiently integrate multiple large-scale scRNA-se...
RNA-Seq Gene Expression Profiling Sequence Analysis, RNA Machine Learning Exome Sequencing Cluster Analysis Single-Cell Analysis Algorithms
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A copula based topology preserving graph convolution network for clustering of single-cell RNA-seq data.

PLoS computational biology Mar 10, 2022
Annotation of cells in single-cell clustering requires a homogeneous grouping of cell populations. There are various issues in single cell sequencing that effect homogeneous grouping (clustering) of cells, such as small amount of starting RNA, limite...
RNA-Seq Cluster Analysis Exome Sequencing Artificial Intelligence Single-Cell Analysis
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Deep learning using bulk RNA-seq data expands cell landscape identification in tumor microenvironment.

Oncoimmunology Feb 25, 2022
The tumor microenvironment (TME) profoundly influences tumor progression and affects immunotherapy responses and resistance. Understanding its heterogeneity is the key for developing immunotherapy. However, the available methods can only partially po...
Humans Tumor Microenvironment RNA-Seq Immunotherapy Deep Learning Exome Sequencing
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Universal prediction of cell-cycle position using transfer learning.

Genome biology Jan 31, 2022
BACKGROUND: The cell cycle is a highly conserved, continuous process which controls faithful replication and division of cells. Single-cell technologies have enabled increasingly precise measurements of the cell cycle both as a biological process of ...
Cell Cycle Exome Sequencing Single-Cell Analysis Sequence Analysis, RNA Machine Learning Principal Component Analysis
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PhenoApt leverages clinical expertise to prioritize candidate genes via machine learning.

American journal of human genetics Jan 20, 2022
In recent years, exome sequencing (ES) has shown great utility in the diagnoses of Mendelian disorders. However, after rigorous filtering, a typical ES analysis still involves the interpretation of hundreds of variants, which greatly hinders the rapi...
Exome Microcephaly Nystagmus, Congenital Intellectual Disability Genetic Diseases, Inborn Databases, Genetic Genetic Testing Exome Sequencing Hearing Loss, Sensorineural Scoliosis Genotype Computational Biology Phenotype Cohort Studies Machine Learning Software Humans
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DNN-Boost: Somatic mutation identification of tumor-only whole-exome sequencing data using deep neural network and XGBoost.

Journal of bioinformatics and computational biology Dec 13, 2021
Detection of somatic mutation in whole-exome sequencing data can help elucidate the mechanism of tumor progression. Most computational approaches require exome sequencing for both tumor and normal samples. However, it is more common to sequence exome...
Exome Sequencing Exome Mutation High-Throughput Nucleotide Sequencing Humans Neural Networks, Computer Neoplasms
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Artificial intelligence (AI)-assisted exome reanalysis greatly aids in the identification of new positive cases and reduces analysis time in a clinical diagnostic laboratory.

Genetics in medicine : official journal of the American College of Medical Genetics Nov 30, 2021
PURPOSE: Artificial intelligence (AI) and variant prioritization tools for genomic variant analysis are being rapidly developed for use in clinical diagnostic testing. However, their clinical utility and reliability are currently limited. Therefore, ...
Exome Sequencing Reproducibility of Results Humans Exome Genetic Testing Artificial Intelligence
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Sparsely Connected Autoencoders: A Multi-Purpose Tool for Single Cell omics Analysis.

International journal of molecular sciences Nov 25, 2021
BACKGROUND: Biological processes are based on complex networks of cells and molecules. Single cell multi-omics is a new tool aiming to provide new incites in the complex network of events controlling the functionality of the cell.
Computational Biology Cluster Analysis Neural Networks, Computer Single-Cell Analysis Humans Lung Neoplasms Machine Learning Exome Sequencing Adenocarcinoma of Lung
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