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2.
Nat Commun ; 13(1): 1004, 2022 03 04.
Article in English | MEDLINE | ID: mdl-35246524

ABSTRACT

As whole-genome sequencing (WGS) becomes the gold standard tool for studying population genomics and medical applications, data on diverse non-European and admixed individuals are still scarce. Here, we present a high-coverage WGS dataset of 1,171 highly admixed elderly Brazilians from a census-based cohort, providing over 76 million variants, of which ~2 million are absent from large public databases. WGS enables identification of ~2,000 previously undescribed mobile element insertions without previous description, nearly 5 Mb of genomic segments absent from the human genome reference, and over 140 alleles from HLA genes absent from public resources. We reclassify and curate pathogenicity assertions for nearly four hundred variants in genes associated with dominantly-inherited Mendelian disorders and calculate the incidence for selected recessive disorders, demonstrating the clinical usefulness of the present study. Finally, we observe that whole-genome and HLA imputation could be significantly improved compared to available datasets since rare variation represents the largest proportion of input from WGS. These results demonstrate that even smaller sample sizes of underrepresented populations bring relevant data for genomic studies, especially when exploring analyses allowed only by WGS.


Subject(s)
Genomics , Metagenomics , Aged , Brazil/epidemiology , Genome, Human/genetics , Genomics/methods , Humans , Polymorphism, Single Nucleotide , Whole Genome Sequencing
3.
Bioinformatics ; 37(3): 419-421, 2021 04 20.
Article in English | MEDLINE | ID: mdl-32717039

ABSTRACT

MOTIVATION: Retrocopies or processed pseudogenes are gene copies resulting from mRNA retrotransposition. These gene duplicates can be fixed, somatically inserted or polymorphic in the genome. However, knowledge regarding unfixed retrocopies (retroCNVs) is still limited, and the development of computational tools for effectively identifying and genotyping them is an urgent need. RESULTS: Here, we present sideRETRO, a pipeline dedicated not only to detecting retroCNVs in whole-genome or whole-exome sequencing data but also to revealing their insertion sites, zygosity and genomic context and classifying them as somatic or polymorphic events. We show that sideRETRO can identify novel retroCNVs and genotype them, in addition to finding polymorphic retroCNVs in whole-genome and whole-exome data. Therefore, sideRETRO fills a gap in the literature and presents an efficient and straightforward algorithm to accelerate the study of bona fide retroCNVs. AVAILABILITY AND IMPLEMENTATION: sideRETRO is available at https://github.com/galantelab/sideRETRO. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Subject(s)
Genomics , Pseudogenes , Base Sequence , Exome , Genotype , Pseudogenes/genetics , Software
4.
Environ Monit Assess ; 190(6): 319, 2018 May 02.
Article in English | MEDLINE | ID: mdl-29717330

ABSTRACT

The water quality index (WQI) is an important tool for water resource management and planning. However, it has major disadvantages: the generation of chemical waste, is costly, and time-consuming. In order to overcome these drawbacks, we propose to simplify this index determination by replacing traditional analytical methods with ultraviolet-visible (UV-Vis) spectrophotometry associated with artificial neural network (ANN). A total of 100 water samples were collected from two rivers located in Assis, SP, Brazil and calculated the WQI by the conventional method. UV-Vis spectral analyses between 190 and 800 nm were also performed for each sample followed by principal component analysis (PCA) aiming to reduce the number of variables. The scores of the principal components were used as input to calibrate a three-layer feed-forward neural network. Output layer was defined by the WQI values. The modeling efforts showed that the optimal ANN architecture was 19-16-1, trainlm as training function, root-mean-square error (RMSE) 0.5813, determination coefficient between observed and predicted values (R2) of 0.9857 (p < 0.0001), and mean absolute percentage error (MAPE) of 0.57% ± 0.51%. The implications of this work's results open up the possibility to use a portable UV-Vis spectrophotometer connected to a computer to predict the WQI in places where there is no required infrastructure to determine the WQI by the conventional method as well as to monitor water body's in real time.


Subject(s)
Environmental Monitoring/methods , Neural Networks, Computer , Water Pollutants, Chemical/analysis , Water Pollution, Chemical/statistics & numerical data , Brazil , Principal Component Analysis , Rivers/chemistry , Spectrophotometry, Ultraviolet , Ultraviolet Rays , Water Quality
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