Herald:The Biostar Herald for Monday, January 22, 2024
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The Biostar Herald publishes user submitted links of bioinformatics relevance. It aims to provide a summary of interesting and relevant information you may have missed. You too can submit links here.

This edition of the Herald was brought to you by contribution from Mensur Dlakic, Istvan Albert, and was edited by Istvan Albert,


BSAlign: a library for nucleotide sequence alignment | bioRxiv (www.biorxiv.org)

We have developed a Banded Striped Aligner(library) named BSAlign that delivers accurate alignment results at an ultra-fast speed by knitting a series of novel methods together to take advantage of all of the aforementioned three perspectives with highlights such as active F-loop in striped vectorization and striped move in banded dynamic programming. We applied our new acceleration design on both regular and edit-distance pairwise alignment. BSAlign achieved 2-fold speed-up than other SIMD based implementations for regular pairwise alignment, and 1.5 to 4-fold speedup in edit distance based implementations for long reads. BSAlign is implemented in C programing language

submitted by: Istvan Albert


Interpretation of biological experiments changes with evolution of the Gene Ontology and its annotations | Scientific Reports (www.nature.com)

Gene Ontology (GO) enrichment analysis is ubiquitously used for interpreting high throughput molecular data and generating hypotheses about underlying biological phenomena of experiments. However, the two building blocks of this analysis — the ontology and the annotations — evolve rapidly. We used gene signatures derived from 104 disease analyses to systematically evaluate how enrichment analysis results were affected by evolution of the GO over a decade. We found low consistency between enrichment analyses results obtained with early and more recent GO versions. Furthermore, there continues to be a strong annotation bias in the GO annotations where 58% of the annotations are for 16% of the human genes. Our analysis suggests that GO evolution may have affected the interpretation and possibly reproducibility of experiments over time. Hence, researchers must exercise caution when interpreting GO enrichment analyses and should reexamine previous analyses with the most recent GO version.

submitted by: Istvan Albert


TileDB-VCF (tiledb-inc.github.io)

A C++ library for efficient storage and retrieval of genomic variant-call data

submitted by: Istvan Albert


Inference of phylogenetic trees directly from raw sequencing reads using Read2Tree | Nature Biotechnology (www.nature.com)

Read2Tree directly processes raw sequencing reads into groups of corresponding genes and bypasses traditional steps in phylogeny inference, such as genome assembly, annotation and all-versus-all sequence comparisons, while retaining accuracy.

submitted by: Mensur Dlakic


Impact of genome build on RNA-seq interpretation and diagnostics | medRxiv (www.medrxiv.org)

Transcriptomics is a powerful tool for unraveling the molecular effects of genetic variants and disease diagnosis. Prior studies have demonstrated that choice of genome build impacts variant interpretation and diagnostic yield for genomic analyses. To identify the extent genome build also impacts transcriptomics analyses, we studied the effect of the hg19, hg38, and CHM13 genome builds on expression quantification and outlier detection in 386 rare disease and familial control samples from both the Undiagnosed Diseases Network (UDN) and Genomics Research to Elucidate the Genetics of Rare Disease (GREGoR) Consortium. We identified 2,800 genes with build-dependent quantification across six routinely-collected biospecimens, including 1,391 protein-coding genes and 341 known rare disease genes. We further observed multiple genes that only have detectable expression in a subset of genome builds. Finally, we characterized how genome build impacts the detection of outlier transcriptomic events. Combined, we provide a database of genes impacted by build choice, and recommend that transcriptomics-guided analyses and diagnoses are cross-referenced with these data for robustness.

submitted by: Istvan Albert


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