| 1. |
- Brueffer, Christian, et al.
(author)
-
Biopython Project Update 2016
- 2016
-
Conference paper (other academic/artistic)abstract
- The Biopython Project is a long-running distributed collaborative effort, supported by the Open Bioinformatics Foundation, which develops a freely available Python library for biological computation.We present here details of the latest Biopython release - version 1.66. New features include: extended Bio.KEGG and Bio.Graphics modules to support drawing KEGG pathways with transparency; extended “abi” Bio.SeqIO parser to decode almost all documented fields used by ABIF instruments; a QCPSuperimposer module using the Quaternion Characteristic Polynomial algorithm for superimposing structures to Bio.PDB; and an extended Bio.Entrez module to implement the NCBI Entrez Citation Matching function and to support NCBI XML files with XSD schemas. Additionally we fixed miscellaneous bugs, enhanced our test suite and continued our efforts to abide by the PEP8 coding style guidelines.We are currently preparing a new release – version 1.67 – that will deprecate the ability to compare SeqRecord objects with “==”, which sometimes lead to surprising results. In addition it will feature a new experimental Bio.phenotype module for working with Phenotype Microarray data; updates to Bio.Data toinclude NCBI genetic code table 25, covering Candidate Division SR1 and Gracilibacteria; an update to Bio.Restriction to include the REBASE May 2016 restriction enzyme list; updates to BioSQL to use foreign keys with SQLite3 databases; as well as corrections to the Bio.Entrez module and the MMCIF structure parser.Our website has been migrated from MediaWiki to GitHub Pages and is now under version control. The continuous integration process on GitHub has been enhanced by including external services like Landscape, Quantified Code and Codecov to perform quality review, test coverage analysis and generation of quality metrics.Finally, our range of Docker containers has been greatly enhanced. In addition to a basic container that includes Python 2 and 3 with Biopython and all its dependencies, as well as a BioSQL container, we now also provide two versions of Jupyter notebook containers: a basic one, and a version including the Biopython tutorial as notebooks.
|
|
| 2. |
- Dai, Qile, et al.
(author)
-
OTTERS: a powerful TWAS framework leveraging summary-level reference data
- 2023
-
In: Nature Communications. - : Springer Nature. - 2041-1723. ; 14:1
-
Journal article (peer-reviewed)abstract
- Most existing TWAS tools require individual-level eQTL reference data and thus are not applicable to summary-level reference eQTL datasets. The development of TWAS methods that can harness summary-level reference data is valuable to enable TWAS in broader settings and enhance power due to increased reference sample size. Thus, we develop a TWAS framework called OTTERS (Omnibus Transcriptome Test using Expression Reference Summary data) that adapts multiple polygenic risk score (PRS) methods to estimate eQTL weights from summary-level eQTL reference data and conducts an omnibus TWAS. We show that OTTERS is a practical and powerful TWAS tool by both simulations and application studies.
|
|
| 3. |
- Hop, Paul J., et al.
(author)
-
Genome-wide study of DNA methylation shows alterations in metabolic, inflammatory, and cholesterol pathways in ALS
- 2022
-
In: Science Translational Medicine. - : American Association for the Advancement of Science. - 1946-6234 .- 1946-6242. ; 14:633
-
Journal article (peer-reviewed)abstract
- Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with an estimated heritability between 40 and 50%. DNA methylation patterns can serve as proxies of (past) exposures and disease progression, as well as providing a potential mechanism that mediates genetic or environmental risk. Here, we present a blood-based epigenome-wide association study meta-analysis in 9706 samples passing stringent quality control (6763 patients, 2943 controls). We identified a total of 45 differentially methylated positions (DMPs) annotated to 42 genes, which are enriched for pathways and traits related to metabolism, cholesterol biosynthesis, and immunity. We then tested 39 DNA methylation-based proxies of putative ALS risk factors and found that high-density lipoprotein cholesterol, body mass index, white blood cell proportions, and alcohol intake were independently associated with ALS. Integration of these results with our latest genome-wide association study showed that cholesterol biosynthesis was potentially causally related to ALS. Last, DNA methylation at several DMPs and blood cell proportion estimates derived from DNA methylation data were associated with survival rate in patients, suggesting that they might represent indicators of underlying disease processes potentially amenable to therapeutic interventions.
|
|
