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  1. ..., divergence times, and population sizes) is computed by simulating data under the coalescent with recombination using the candidate model, using these data to automatically construct an HMM, and then computing the likelihood by means of the forward algorithm (Chang and Hancock 1966; Baum et al. 1970, 1972...
  2. ...SiCloneFit: Bayesian inference of population structure, genotype, and phylogeny of tumor clones from single-cell sequencing data Hamim Zafar1,2, Nicholas Navin3, Ken Chen2 and Luay Nakhleh1 1Department of Computer Science, Rice University, Houston, Texas 77005, USA; 2Department of Bioinformatics...
  3. ....sahinalp@nih.govAbstractAvailable computational methods for tumor phylogeny inference via single-cell sequencing (SCS) data typically aim to identify the most likely perfect phylogeny tree satisfying the infinite sites assumption (ISA). However, the limitations of SCS technologies including frequent allele dropout and variable sequence coverage...
  4. ...and generating 53 tissue-enriched cis-regulatory elements (CREs), including 1,645 promoter- and 54 enhancer-associated elements. This study establishes a robust computational framework for 55 cross-species TE analysis and provides key insights into the coevolution of KZFPs and TEs, 56 advancing our understanding...
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  5. ...and Triturus but on a separate chromosome in Pleurodeles.View larger version: In this window In a new window Figure 4. Phylogeny of newt MHC in the context of MHC sequences from other tetrapod taxa. The RAxML-NG maximum likelihood trees were constructed from protein sequences under the JTT+G4 amino...
  6. ...likelihood estimation (ape R package) (Paradis and Schliep 2019). This provided us with the scaled likelihoods of ancestral states for each internal node of the tree. Based on this extensive automated annotation, we then reviewed individually the transitions based on literature on rodent phylogeny...
  7. ...Bio) and Oxford Nanopore Technologies (ONT), has markedly enhanced both the efficiency and accuracy of genomic studies (Sedlazeck et al. 2018). These technological advances have also propelled pan analyses. Initially developed for bacterial studies (Sherman and Salzberg 2020), the pan approach has now gained...
  8. ...a maximum-likelihood approach along our time-calibrated phylogeny in the R package phytools (Revell 2012; R Core Team 2014).Transposable element evolutionTo identify transposable elements in the s of the three studied gar species (L. osseus, L. oculatus, A. spatula), Danio rerio, Acipenser ruthenus, Amia...
  9. ...of morphologies, vacuolar morphologies dominate cultured samples (Fig. 1B).View larger version: In this window In a new window Figure 1. Phylogenetic relationships and assembly characteristics of Blastocystis. (A) 18S rRNA maximum likelihood (ML) phylogeny of Blastocystis subtypes, with Proteromonas lacertae...
  10. ...duplication blocks, with DupMasker annotations illustrated with colored arrows. The diverse organizational differences of each expansion, including expansion size, duplicon content, and copy number, suggest independent expansion. (B) TBC1D3 neutral phylogeny generated by maximum likelihood; 2300 bp...
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