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Day: June 13, 2022

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phylogenetic origins of relapse using single-cell data

Our phylogenetic analysis of single cells exposes how, where and when malignant cells survive treatment in a personalized manner in…

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Recent Posts

  • Scalable single-cell phylogenies June 28, 2022
  • mini-review on single-cell DNA variant callers June 20, 2022
  • phylogenetic origins of relapse using single-cell data June 13, 2022
  • mtDNA single-cell paper February 21, 2022
  • Understanding SARS-CoV-2 transmission February 7, 2022

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    David Posada Follow

    A computational evolutionary biologist lately interested in cancer evolution.

    dposada_
    dposada_ David Posada @dposada_ ·
    28 Jun

    Nice collaboration with @NakhlehRice and @Quasarzafar labs on scalable single-cell phylogenetic inference: https://doi.org/10.1093/bioinformatics/btac254

    Reply on Twitter 1541702269086957572 Retweet on Twitter 1541702269086957572 2 Like on Twitter 1541702269086957572 7 Twitter 1541702269086957572
    dposada_ David Posada @dposada_ ·
    20 Jun

    A simple review on scDNA-seq variant callers: https://doi.org/10.1016/j.csbj.2022.06.013

    Reply on Twitter 1538788198884728832 Retweet on Twitter 1538788198884728832 4 Like on Twitter 1538788198884728832 17 Twitter 1538788198884728832
    dposada_ David Posada @dposada_ ·
    13 Jun

    Here we show how single-cell cancer genomics can help to understand how a liver relapse took place in a mCRC patient. Great collaborative work with @CD68PHD2, @JMFAlves et al:
    https://doi.org/10.1016/j.canlet.2022.215767

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    ewa_szczurek Ewa Szczurek @ewa_szczurek ·
    21 Apr

    Great opportunity for a postdoc position in my lab. Both involve research on machine learning and cancer. Please RT! https://www.mimuw.edu.pl/~szczurek/positions.html

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    trevoragraham Trevor Graham @trevoragraham ·
    21 Mar

    This method is important because it allows phylogeny reconstruction & mutation rate estimation from copy number data without b-alleles, & handles time explicitly. Use it to make more of cheap and high throughput low-coverage sequencing data. Fab stuff from @lubingxin & @cssb_lab https://twitter.com/cssb_lab/status/1505826987390246912

    CSSB Lab @cssb_lab

    New work from @lubingxin on temporal phylogeny inference from tumour shallow WGS samples. With Ziheng Yang, @trevoragraham, @yosoykit. Great to see this out there! https://twitter.com/biorxivpreprint/status/1505737538572636161
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