Cumulative proportions of patients reporting one or several risk factors and resulting number-to-screen.

<p>Cumulative proportions of patients reporting one or several risk factors and resulting number-to-screen.</p

MRSA prevalence in nursing homes in Saarland, Germany.

<p>Shown is the MRSA prevalence (MRSA cases in percent) of the various LTCF sorted by result. The dots represent the expected rate of MRSA prevalence based to the LTCF pre-study information; the dashed line shows the mean MRSA rate throughout the entire study population.</p

Univariate analysis of risk factors associated with MRSA colonisation.

<p>Univariate analysis of risk factors associated with MRSA colonisation.</p

Risk factor distribution of the study population and MRSA carriers.

<p>Risk factor distribution of the study population and MRSA carriers.</p

Prevalence of <i>spa</i> types in nursing homes in Saarland, Germany.

<p>The number of different <i>spa</i> types is given per LTCF (identical numbering as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0153030#pone.0153030.g001" target="_blank">Fig 1</a>). <i>spa</i> type t003 (grey), t504 (light grey), not classified <i>spa</i> types (white), other <i>spa</i> types (black).</p

Principal component cluster analysis (PCA) of 41 MRSA (R1–R41) and two MSSA (S42, S43) of CC5.

<p>(A) Clustering of the 43 CC5 isolates by PCA as well as (B) subclustering of 30 MRSA CC5 cluster I isolates using a higher resolution PCA plot for in-depth identification of additional subgroups (Ia–Id).</p

Risk factors of MRSA and matched MSSA control group isolates.

#<p>statistical analysis was not performed for clinical criteria applied for selection of matched MSSA cases, ns =  not significant.</p

CC5 isolates (n = 43) characterized by <i>spa</i>-typing and comprehensive MA subgroup analysis using three different bioinformatic modes (principal component analyses, splits graph and cluster dendrogram).

<p>CC5 isolates (n = 43) characterized by <i>spa</i>-typing and comprehensive MA subgroup analysis using three different bioinformatic modes (principal component analyses, splits graph and cluster dendrogram).</p

Diversity analysis of all MSSA (S1–S46) and MRSA (R1–R46) isolates by splits graph.

<p>(A) Splits graph constructed based on cost distance matrix produced by Ridom StaphType and (B) on default settings of the IdentiBAC microarray hybridization profiles of 334 genes and alleles. Clonal complexes (CC) as well as the most abundant <i>spa</i>-types t003 (circles) and t012 (quadrates) were highlighted.</p

Subclassification analysis of 41 MRSA (R1–R41) and two MSSA (S42, S43) of CC5.

<p>(A) Splits graph based on cost distance matrix computed by Ridom StaphType software. (B) Splits graph based on MA hybridization profiles. Characteristic gene profiles for isolate cluster assignment were arbitrarily stated into group A-E. The most common MRSA <i>spa</i>-types t003 (circles), t504 (quadrates) and t010 (hexagons) were highlighed.</p