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dposada June 20, 2022

mini-review on single-cell DNA variant callers

https://doi.org/10.1016/j.csbj.2022.06.013

Here, we review current approaches for single-cell variant calling, emphasizing single nucleotide variants. We highlight their potential benefits and shortcomings to help users choose a suitable tool for their data at hand.

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dposada - 10 posts Uncategorized

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phylogenetic origins of relapse using single-cell data
Scalable single-cell phylogenies

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CellPhy paper

Finally out! ML inference of single-cell phylogenies https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02583-w Download CellPhy at: https://github.com/amkozlov/cellphy

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AECC grant: Microbiome as biomarker for CRC

We want to thank the Spanish Cancer Association (AECC) for awarding us a research grant to study the role of…

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New PhD fellowships

Congratulations to Pilar Gallego and Pablo Fonseca for their Xunta de Galicia Ph.D. fellowships! Pilar is already working on SARS-CoV-2…

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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

    Reply on Twitter 1536250686555492352 Retweet on Twitter 1536250686555492352 8 Like on Twitter 1536250686555492352 28 Twitter 1536250686555492352
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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

    Reply on Twitter 1517093700005990400 Retweet on Twitter 1517093700005990400 10 Like on Twitter 1517093700005990400 15 Twitter 1517093700005990400
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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

    Reply on Twitter 1505831647312289798 Retweet on Twitter 1505831647312289798 8 Like on Twitter 1505831647312289798 33 Twitter 1505831647312289798
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