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This edition of the Herald was brought to you by contribution from Istvan Albert, and was edited by Istvan Albert,
GitHub - GuyTeichman/RNAlysis: RNA sequencing analysis software (github.com)
RNAlysis is a Python-based software for analyzing RNA sequencing data. RNAlysis allows you to build customized analysis pipelines suiting your specific research questions, going all the way from exploratory data analysis and data visualization through clustering analysis and gene-set enrichment analysis.
submitted by: Istvan Albert
excluderanges: exclusion sets for T2T-CHM13, GRCm39, and other genome assemblies | bioRxiv (www.biorxiv.org)
Exclusion regions are sections of reference genomes with abnormal pileups of short sequencing reads. Removing reads overlapping them improves biological signal, and these benefits are most pronounced in differential analysis settings. Several labs created exclusion region sets, available primarily through ENCODE and Github. However, the variety of exclusion sets creates uncertainty which sets to use. Furthermore, gap regions (e.g., centromeres, telomeres, short arms) create additional considerations in generating exclusion sets. We generated exclusion sets for the latest human T2T-CHM13 and mouse GRCm39 genomes and systematically assembled and annotated these and other sets in the excluderanges R/Bioconductor data package, also accessible via the BEDbase.org API. The package provides unified access to 82 GenomicRanges objects covering six organisms, multiple genome assemblies and types of exclusion regions.
submitted by: Istvan Albert
A Quantitative Proteome Map of the Human Body: Cell (www.cell.com)
- Quantified proteins from more than 12,000 genes across 32 normal human tissues
- Discordance of RNA and protein enrichment provides evidence of protein secretion
- Tissue-specific distribution of enzymes indicates a coordinated control of metabolism
- Tissue-enriched proteins provide insights into phenotypes of genetic diseases
submitted by: Istvan Albert
Fast and accurate mapping of long reads to complete genome assemblies with VerityMap (genome.cshlp.org)
Since the accuracy of read mapping tools deteriorates in highly-repetitive regions, there is a need to develop accurate, error-exposing (detecting potential assembly errors), and diploid-aware (distinguishing different haplotypes) tools for read mapping in complete assemblies. We describe the first accurate, error-exposing, and partially diploid-aware VerityMap tool for long-read mapping to complete assemblies.
submitted by: Istvan Albert
A proposed metric set for evaluation of genome assembly quality: Trends in Genetics (www.cell.com)
Quality control is essential for genome assemblies; however, a consensus has yet to be reached on what metrics should be adopted for the evaluation of assembly quality. N50 is widely used for contiguity measurement, but its effectiveness is constantly in question. Prevailing metrics for the completeness evaluation focus on gene space, yet challenging areas such as tandem repeats are commonly overlooked. Achieving correctness has become an indispensable dimension for quality control, while prevailing assembly releases lack scores reflecting this aspect. We propose a metric set with a set of statistic indexes for effective, comprehensive evaluation of assemblies and provide a score of a finished assembly for each metric, which can be utilized as a benchmark for achieving high-quality genome assemblies.
submitted by: Istvan Albert
This is truly mind blowing.
In 2001, @McC_Nick promised that Solexa* will be able to sequence 1x genome for $700. He did not overhyped it -- it just took a decade to get to this point 🤯. Today, it costs <$20 for 1x genome.
*aka @Illumina for GenZ readers👶 pic.twitter.com/7CVbFeD7S0
— Yaniv Erlich (@erlichya) November 23, 2022
This is truly mind blowing.
In 2001, @McC_Nick promised that Solexa* will be able to sequence 1x genome for $700. He did not overhyped it -- it just took a decade to get to this point 🤯. Today, it costs <$20 for 1x genome.
*aka @Illumina for GenZ readers👶 pic.twitter.com/7CVbFeD7S0
submitted by: Istvan Albert
https://academic.oup.com/gigascience/article/8/4/giz040/5477467
Here, we present "duphold," a new method to efficiently annotate SV calls with sequence depth information that can add (or remove) confidence to SVs that are predicted to affect copy number. Duphold indicates not only the change in depth across the event but also the presence of a rapid change in depth relative to the regions surrounding the break-points. It uses a unique algorithm that allows the run time to be nearly independent of the number of variants.
submitted by: Istvan Albert
GitHub - broadinstitute/gtex-pipeline: GTEx & TOPMed data production and analysis pipelines (github.com)
This repository contains analysis pipelines for:
- RNA-seq alignment, quantification, and quality control
- eQTL mapping and annotation
- Allele-specific expression quantification
- Generation of the collapsed annotation used for gene-level expression quantification
submitted by: Istvan Albert
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Corrected link:
A proposed metric set for evaluation of genome assembly quality