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Mike Love ретуитна
Our new paper: Using Equivalent Class counts directly for testing differential transcript usage. Nice work from
@marekcmero@nadia_davidson https://www.biorxiv.org/content/early/2018/12/19/501106 …pic.twitter.com/JTANHlLQzZ
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Mike Love ретуитна
The decontam method introduced in our new
@MicrobiomeJ paper is available as an R package via Bioconductor and has an annotated tutorial. Bioconductor: https://bioconductor.org/packages/release/bioc/html/decontam.html … Tutorial: https://benjjneb.github.io/decontam/vignettes/decontam_intro.html … Manuscript:https://microbiomejournal.biomedcentral.com/articles/10.1186/s40168-018-0605-2 …Показване на тази нишкаБлагодаря. Twitter ще използва това, за да подобри хрониката ти. ОтмянаОтмяна -
Mike Love ретуитна
Our intensely collaborative (5/6 authors are PIs!) review article *for biologists* about theory / mathematical modeling is out in JCS: Unite to divide – how models and biological experimentation have come together to reveal mechanisms of cytokinesishttp://jcs.biologists.org/content/131/24/jcs203570 …
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Mike Love ретуитна
Congrats
@bejcal@hyposalivation and Nicole Davis: really useful piece of work: Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics datahttps://microbiomejournal.biomedcentral.com/articles/10.1186/s40168-018-0605-2?utm_source=dlvr.it&utm_medium=twitter …Благодаря. Twitter ще използва това, за да подобри хрониката ти. ОтмянаОтмяна -
Mike Love ретуитна
#rstats PSA: The incoming CRAN submission queue will be closed from Dec 21 to Jan 2 (assumedly for a well deserved break for the volunteer team). Get your new packages and updates in before the 21st or wait until the new year.Благодаря. Twitter ще използва това, за да подобри хрониката ти. ОтмянаОтмяна -
Mike Love ретуитна
Alevin efficiently estimates accurate gene abundances from dscRNA-seq data https://www.biorxiv.org/content/early/2018/10/24/335000 … I was pleased to see this! Nicely solves an unsightly hack in UMI-based scRNAseq.
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Mike Love ретуитна
In stat method life and then in R pkg life, I had to intentionally cultivate a neutral-to-positive attitude re: what others were doing — especially if the work is adjacent to mine. We’re embarked on a collective effort! This makes me much happier and more productive too.
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Mike Love ретуитна
Our integrative study on dozens of in vivo RNA-binding protein datasets is out! A long standing collaboration with Tom Tuschl and fantastic work led by
@neelmukherj . I think of it as renegade inofficial@ENCODE_NIH companion paper
https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gky1185/5230955#.XBarxpEjROE.twitter …Благодаря. Twitter ще използва това, за да подобри хрониката ти. ОтмянаОтмяна -
Mike Love ретуитна
Very excited to be leading our new Translational
#DataScience Integrated Research Center at@fredhutch So many opportunities in this space bridging many disciplines with terrific computational/experimental investigators. Stay tuned!https://twitter.com/fredhutch/status/1073825736937668608 …Благодаря. Twitter ще използва това, за да подобри хрониката ти. ОтмянаОтмяна -
Mike Love ретуитна
CancerInSilico: An R/Bioconductor package for combining mathematical and statistical modeling to simulate time course bulk and single cell gene expression data in cancer | bioRxivhttps://www.biorxiv.org/content/early/2018/12/14/328807 …
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Mike Love ретуитна
Polygenic risk scores for breast cancer and estrogen-receptor subtypes, developed using individual-level data on 170,000 cases and controls from the Breast Cancer Association Consortium. 313 SNPs can identify 1% of women at 4.3-fold increased risk of ER+ disease.https://twitter.com/AJHGNews/status/1073251358407446529 …
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if you use NNLS for deconvolution, you should be adding expression profiles on the raw expression scale, not log scale. we have a helper function unmix() for making comparisons in log-like scale while doing the NNLS on the raw, easy to copy the code and modify
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Mike Love ретуитна
Breast cancer screening is one of the most tractable uses of
#polygenic risk scoring. Improved predictions, with 32% BC risk in highest 1% PRS. https://www.cell.com/ajhg/fulltext/S0002-9297(18)30405-1#secsectitle0075 …pic.twitter.com/zfTe2PM540
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Mike Love ретуитна
Wow. PsychEncode just flooded the science publication group with 10 manuscripts revealing a significant progress made towards understanding the brain's molecular architecture. They dedicate this release to
@PamelaSklar1http://science.sciencemag.org/content/362/6420/1262 …Благодаря. Twitter ще използва това, за да подобри хрониката ти. ОтмянаОтмяна -
Mike Love ретуитна
Random thoughts about confidence intervals: When we teach precision & accuracy, we often use images of a target, like these from the Wikipedia article: https://en.m.wikipedia.org/wiki/Accuracy_and_precision … But I think this analogy leads to confusion about the interpretation of the confidence interval. 1/4pic.twitter.com/8Ma7KxsHjW
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Mike Love ретуитна
Using multiple measurements of tissue to estimate cell-type-specific gene expression via deconvolutionhttps://www.biorxiv.org/content/early/2018/12/12/379099 …
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Mike Love ретуитна
Our study with
@dulaclab on pup recognition just out! Check it out in the following links: https://www.cell.com/cell/fulltext/S0092-8674(18)31557-5 … or https://authors.elsevier.com/a/1YDU1L7PXUjitБлагодаря. Twitter ще използва това, за да подобри хрониката ти. ОтмянаОтмяна -
Mike Love ретуитна
Check out our new ENIGMA GWAS: Common genetic variants impacting the structure of the human cerebral cortex, measured with MRI, in 35k humans, ~200 loci:https://www.biorxiv.org/content/early/2018/09/03/399402 …
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Mike Love ретуитна
The Brain Transcriptome maps are finally out! This includes some of the RNA-seq data back from my post-doc in 2008 with
@Genomics_Guy! Revealing the brain's molecular architecture, one transcript at a time - see herehttp://science.sciencemag.org/content/362/6420/1262 …Благодаря. Twitter ще използва това, за да подобри хрониката ти. ОтмянаОтмяна -
Mike Love ретуитна
Important session at
@broadinstitute this morning - a discussion of the need for greater diversity in human genetics, led by@genetisaur. She leads off with a pretty astonishing statistic: Europeans are 80% of samples in genetic studies, vs 16% of the global population.Благодаря. Twitter ще използва това, за да подобри хрониката ти. ОтмянаОтмяна
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