Composition for personal growth : program design and evaluation.

<p>Two categories were used for cross-validation of the model, either type 1 or type 2. Clinical isolates were treated as an unknown class and cross-validated sensitivity, specificity, and class error were based on their classification prediction score with their respective reference strain control class. CV, cross-validated.</p><p>Cross-validated PLS-DA modeling statistics for the prediction performance for NA-SERS typing of individual type 1 and 2 <i>M</i>. <i>pneumoniae</i> clinical isolates.</p

Comprehensive bioinformatics analysis of <i>Mycoplasma pneumoniae</i> genomes to investigate underlying population structure and type-specific determinants

<div><p><i>Mycoplasma pneumoniae</i> is a significant cause of respiratory illness worldwide. Despite a minimal and highly conserved genome, genetic diversity within the species may impact disease. We performed whole genome sequencing (WGS) analysis of 107 <i>M</i>. <i>pneumoniae</i> isolates, including 67 newly sequenced using the Pacific BioSciences RS II and/or Illumina MiSeq sequencing platforms. Comparative genomic analysis of 107 genomes revealed >3,000 single nucleotide polymorphisms (SNPs) in total, including 520 type-specific SNPs. Population structure analysis supported the existence of six distinct subgroups, three within each type. We developed a predictive model to classify an isolate based on whole genome SNPs called against the reference genome into the identified subtypes, obviating the need for genome assembly. This study is the most comprehensive WGS analysis for <i>M</i>. <i>pneumoniae</i> to date, underscoring the power of combining complementary sequencing technologies to overcome difficult-to-sequence regions and highlighting potential differential genomic signatures in <i>M</i>. <i>pneumoniae</i>.</p></div

Correction: Comprehensive bioinformatics analysis of <i>Mycoplasma pneumoniae</i> genomes to investigate underlying population structure and type-specific determinants

Correction: Comprehensive bioinformatics analysis of <i>Mycoplasma pneumoniae</i> genomes to investigate underlying population structure and type-specific determinant

NA-SERS specificity spectra

Wavenumber and intensity values for 521 spectra of Mycoplasma pneumoniae, other mycoplasmas, and background controls

PLS-DA distinguishing <i>M</i>. <i>pneumoniae</i> strains from other human commensal and pathogenic <i>Mollicutes</i> species.

<p>Each panel represents a cross-validated class prediction score for <b>(A)</b> class 1, growth medium control; <b>(B)</b> class 2, all <i>M</i>. <i>pneumoniae</i> strains; and <b>(C)</b> class 3, all other human commensal and pathogenic <i>Mollicutes</i> samples. For panels A-C, each individual shape represents a single pre-processed NA-SERS spectrum. The growth medium control spectra are represented by gray diamonds, the <i>M</i>. <i>pneumoniae</i> spectra by open shapes that differ by cluster to indicate the different individual strains and isolates, and the human commensal and pathogenic <i>Mollicutes</i> species are represented by light gray shapes that differ by cluster to indicate the individual species. The red-dotted line indicates the classification threshold line for positive class prediction, and the black-dotted line indicates the 95% confidence interval. Cross-validated sensitivity, specificity, and class error for the panels were as follows: <b>(A)</b> growth medium control: 1.00, 1.00, and 0, respectively; for <b>(B)</b> All <i>M</i>. <i>pneumoniae</i> samples: 1.00, 1.00, and 0, respectively; and for <b>(C)</b> All 12 <i>Mollicutes</i> species: 1.00, 1.00, and 0, respectively. Cross-validated statistics were obtained using Venetian blinds with 10 data splits to represent the prediction performance of the PLS-DA model for <i>M</i>. <i>pneumoniae</i> detection.</p