Vanja
@halfacrocodile.bsky.social
bald but bearded bioinformatics buddy👨🦲
https://autosome.org
https://autosome.org
(15/15) MIXALIME is written in Python, getting the stable version is as easy as 'pip install mixalime', and the source code plus tutorial are freely available at github.com/autosome-ru/...
February 19, 2025 at 11:43 AM
(15/15) MIXALIME is written in Python, getting the stable version is as easy as 'pip install mixalime', and the source code plus tutorial are freely available at github.com/autosome-ru/...
(14/15) We hope you will find MIXALIME and UDACHA useful in your study of regulatory sequence variants.
February 19, 2025 at 11:43 AM
(14/15) We hope you will find MIXALIME and UDACHA useful in your study of regulatory sequence variants.
(13/15) According to stratified LD score regression, these rSNPs correspond to regulatory regions involved in cell type-specific phenotypes. Most importantly, the collection of significant rSNPs can be fully explored at udacha.autosome.org
February 19, 2025 at 11:43 AM
(13/15) According to stratified LD score regression, these rSNPs correspond to regulatory regions involved in cell type-specific phenotypes. Most importantly, the collection of significant rSNPs can be fully explored at udacha.autosome.org
(12/15) AS-chromatin variants are predominantly located in promoter and enhancer regions and significantly overlap ADASTRA ASBs and GTEx eQTLs.
February 19, 2025 at 11:43 AM
(12/15) AS-chromatin variants are predominantly located in promoter and enhancer regions and significantly overlap ADASTRA ASBs and GTEx eQTLs.
(11/15) Finally, we used MIXALIME to analyze 5858 chromatin accessibility datasets from gtrd.biouml.org. In the end, we identified >200 thousand allele-specific chromatin accessibility variants.
February 19, 2025 at 11:43 AM
(11/15) Finally, we used MIXALIME to analyze 5858 chromatin accessibility datasets from gtrd.biouml.org. In the end, we identified >200 thousand allele-specific chromatin accessibility variants.
(10/15) In most cases, MIXALIME outperforms other popular tools for AS calling, offering a good sensitivity/specificity tradeoff.
February 19, 2025 at 11:43 AM
(10/15) In most cases, MIXALIME outperforms other popular tools for AS calling, offering a good sensitivity/specificity tradeoff.
(9/15) Using heart CAGE-Seq data from Deviatiiarov et al., we benchmarked MIXALIME by calling AS variants in CAGE-Seq and comparing them to allele-specific transcription factor binding from ADASTRA and eQTLs from GTEx.
February 19, 2025 at 11:43 AM
(9/15) Using heart CAGE-Seq data from Deviatiiarov et al., we benchmarked MIXALIME by calling AS variants in CAGE-Seq and comparing them to allele-specific transcription factor binding from ADASTRA and eQTLs from GTEx.
(8/15) Copy-number variation and aneuploidy are accounted for by fitting a mixture model assuming that reads originate from haplotypes with different copy numbers.
February 19, 2025 at 11:43 AM
(8/15) Copy-number variation and aneuploidy are accounted for by fitting a mixture model assuming that reads originate from haplotypes with different copy numbers.
(7/15) MIXALIME also handles reference mapping bias and aneuploidy, see the underlying math in arxiv.org/abs/2306.08287. To counter the mapping bias, MIXALIME uses separate fits for Alt read counts with the fixed number of Ref reads and vice versa.
February 19, 2025 at 11:43 AM
(7/15) MIXALIME also handles reference mapping bias and aneuploidy, see the underlying math in arxiv.org/abs/2306.08287. To counter the mapping bias, MIXALIME uses separate fits for Alt read counts with the fixed number of Ref reads and vice versa.
(6/15) MIXALIME provides a variety of statistical models to fulfill particular use cases, from a standard binomial model to the beta negative binomial (BetaNB) model that accounts for extra overdispersion.
February 19, 2025 at 11:43 AM
(6/15) MIXALIME provides a variety of statistical models to fulfill particular use cases, from a standard binomial model to the beta negative binomial (BetaNB) model that accounts for extra overdispersion.
(5/15) MIXALIME is a novel toolbox that uses MIXture models for ALlelic IMbalance Estimation. In the paper, we describe a general workflow from FASTQ files to allelic read counts and SNV-level allele-specific statistics.
February 19, 2025 at 11:43 AM
(5/15) MIXALIME is a novel toolbox that uses MIXture models for ALlelic IMbalance Estimation. In the paper, we describe a general workflow from FASTQ files to allelic read counts and SNV-level allele-specific statistics.
(4/15) Technically, the allele specificity is revealed by counting the number of reads supporting each of the alleles and estimating the statistical significance of the observed allelic imbalance.
February 19, 2025 at 11:43 AM
(4/15) Technically, the allele specificity is revealed by counting the number of reads supporting each of the alleles and estimating the statistical significance of the observed allelic imbalance.
(3/15) High-throughput sequencing allows tracking chromatin state, gene expression, protein-DNA interactions, and more. Eventually, all methods yield short reads that can be used to call single-nucleotide variants and assess the allele specificity.
February 19, 2025 at 11:43 AM
(3/15) High-throughput sequencing allows tracking chromatin state, gene expression, protein-DNA interactions, and more. Eventually, all methods yield short reads that can be used to call single-nucleotide variants and assess the allele specificity.
(2/15) Check the original Tweetorial describing the respective preprint x.com/halfacrocodi... or follow the thread below.
February 19, 2025 at 11:43 AM
(2/15) Check the original Tweetorial describing the respective preprint x.com/halfacrocodi... or follow the thread below.
Last but not least: this update became possible thanks to the experimental data & motif analysis performed within the Codebook/GRECO-BIT collaboration, ibis.autosome.org/docs/about_us
IBIS Challenge
ibis.autosome.org
February 17, 2025 at 11:44 AM
Last but not least: this update became possible thanks to the experimental data & motif analysis performed within the Codebook/GRECO-BIT collaboration, ibis.autosome.org/docs/about_us
(4/4) Don't hesitate to grab a fresh release from hocomoco.autosome.org and remember that we also provide a fancy online motif scanner, MoLoTool, in all its interactive JS-powered beauty.
February 17, 2025 at 11:38 AM
(4/4) Don't hesitate to grab a fresh release from hocomoco.autosome.org and remember that we also provide a fancy online motif scanner, MoLoTool, in all its interactive JS-powered beauty.
(3/4) Also do not forget that HOCOMOCO also provides motifs for orthologous mouse TFs, >800 of those are covered in v13.
February 17, 2025 at 11:38 AM
(3/4) Also do not forget that HOCOMOCO also provides motifs for orthologous mouse TFs, >800 of those are covered in v13.
(2/4) v13 covers >1100 of ~1600 human TFs with >1600 primary motifs and subtypes. Since v12 we also provide a reduced non-redundant set of motifs, which are often shared between TFs with similar DBDs.
February 17, 2025 at 11:38 AM
(2/4) v13 covers >1100 of ~1600 human TFs with >1600 primary motifs and subtypes. Since v12 we also provide a reduced non-redundant set of motifs, which are often shared between TFs with similar DBDs.
(6/6) 👏 Once again, congratulations to the winners and their mentors including @callitmagic.bsky.social y.social @yaronorenstein.bsky.social @salimovdr.bsky.social @german-roev.bsky.social
November 28, 2024 at 7:59 PM
(6/6) 👏 Once again, congratulations to the winners and their mentors including @callitmagic.bsky.social y.social @yaronorenstein.bsky.social @salimovdr.bsky.social @german-roev.bsky.social
(5/6) 🏁 This is the finishing line of the challenge but more remains to be done to analyze the solutions in detail and perform extra tests against other models for the post-challenge manuscript.
November 28, 2024 at 7:59 PM
(5/6) 🏁 This is the finishing line of the challenge but more remains to be done to analyze the solutions in detail and perform extra tests against other models for the post-challenge manuscript.