Shi, Yang Wang, Mengqiao Shi, Weiping Lee, Ji-Hyun Kang, Huining Jiang, Hui
Published in
Bioinformatics (Oxford, England)
Small P-values are often required to be accurately estimated in large-scale genomic studies for the adjustment of multiple hypothesis tests and the ranking of genomic features based on their statistical significance. For those complicated test statistics whose cumulative distribution functions are analytically intractable, existing methods usually ...
Linard, Benjamin Swenson, Krister Pardi, Fabio
Published in
Bioinformatics (Oxford, England)
Taxonomic classification is at the core of environmental DNA analysis. When a phylogenetic tree can be built as a prior hypothesis to such classification, phylogenetic placement (PP) provides the most informative type of classification because each query sequence is assigned to its putative origin in the tree. This is useful whenever precision is s...
Zhu, Wensi Shenoy, Aditi Kundrotas, Petras Elofsson, Arne
Published in
Bioinformatics (Oxford, England)
Despite near-experimental accuracy on single-chain predictions, there is still scope for improvement among multimeric predictions. Methods like AlphaFold-Multimer and FoldDock can accurately model dimers. However, how well these methods fare on larger complexes is still unclear. Further, evaluation methods of the quality of multimeric complexes are...
Hardy, Alexis Matelot, Mélody Touzeau, Amandine Klopp, Christophe Lopez-Roques, Céline Duharcourt, Sandra Defrance, Matthieu
Published in
Bioinformatics (Oxford, England)
Long-read sequencing technologies can be employed to detect and map DNA modifications at the nucleotide resolution on a genome-wide scale. However, published software packages neglect the integration of genomic annotation and comprehensive filtering when analyzing patterns of modified bases detected using Pacific Biosciences (PacBio) or Oxford Nano...
De Jesus Martinez, Teresa Hershberg, Elliot A Guo, Emma Stevens, Garrett J Diesh, Colin Xie, Peter Bridge, Caroline Cain, Scott Haw, Robin Buels, Robert M
...
Published in
Bioinformatics (Oxford, England)
JBrowse Jupyter is a package that aims to close the gap between Python programming and genomic visualization. Web-based genome browsers are routinely used for publishing and inspecting genome annotations. Historically they have been deployed at the end of bioinformatics pipelines, typically decoupled from the analysis itself. However, emerging tech...
Adamer, Michael F Roellin, Eljas Bourguignon, Lucie Borgwardt, Karsten
Published in
Bioinformatics (Oxford, England)
In many modern bioinformatics applications, such as statistical genetics, or single-cell analysis, one frequently encounters datasets which are orders of magnitude too large for conventional in-memory analysis. To tackle this challenge, we introduce SIMBSIG (SIMmilarity Batched Search Integrated GPU), a highly scalable Python package which provides...
Elghraoui, Afif Mirarab, Siavash Swenson, Krister M Valafar, Faramarz
Published in
Bioinformatics (Oxford, England)
The phylogenetic signal of structural variation informs a more comprehensive understanding of evolution. As (near-)complete genome assembly becomes more commonplace, the next methodological challenge for inferring genome rearrangement trees is the identification of syntenic blocks of orthologous sequences. In this article, we studied 94 reference q...
Tu, Jia-Juan Li, Hui-Sheng Yan, Hong Zhang, Xiao-Fei
Published in
Bioinformatics (Oxford, England)
Spatially resolved gene expression profiles are the key to exploring the cell type spatial distributions and understanding the architecture of tissues. Many spatially resolved transcriptomics (SRT) techniques do not provide single-cell resolutions, but they measure gene expression profiles on captured locations (spots) instead, which are mixtures o...
Chan, Trevor J Zhang, Xingjian Mak, Michael
Published in
Bioinformatics (Oxford, England)
In this work, we present an analytical method for quantifying both single-cell morphologies and cell network topologies of tumor cell populations and use it to predict 3D cell behavior. We utilized a supervised deep learning approach to perform instance segmentation on label-free live cell images across a wide range of cell densities. We measured c...
Zhu, Wanying Chen, Hung-Hsin Petty, Alexander S Petty, Lauren E Polikowsky, Hannah G Gamazon, Eric R Below, Jennifer E Highland, Heather M
Published in
Bioinformatics (Oxford, England)
Genomic data are often processed in batches and analyzed together to save time. However, it is challenging to combine multiple large VCFs and properly handle imputation quality and missing variants due to the limitations of available tools. To address these concerns, we developed IMMerge, a Python-based tool that takes advantage of multiprocessing ...
