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biostatistical microbiome data analysis  (Biostatistical Consulting)

 
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    Biostatistical Consulting biostatistical microbiome data analysis
    Biostatistical Microbiome Data Analysis, supplied by Biostatistical Consulting, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/biostatistical microbiome data analysis/product/Biostatistical Consulting
    Average 86 stars, based on 1 article reviews
    biostatistical microbiome data analysis - by Bioz Stars, 2026-05
    86/100 stars

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    Image Search Results


    Analysis of microbial community composition and diversity. ( A / B ) Species abundance bar plots of gut microbiota at the phylum and genus levels, respectively; ( C ) Comparison of Chao 1 index for gut microbiota diversity between groups; ( D ) Comparison of the Firmicutes -to- Bacteroidota ratio between groups. Data are presented as mean ± SEM; ns P > 0.05; ** P < 0.01.

    Journal: Scientific Reports

    Article Title: Gut microbiota-dependent protection by Lactobacillus reuteri against renal injury in brain-dead rats

    doi: 10.1038/s41598-026-47230-1

    Figure Lengend Snippet: Analysis of microbial community composition and diversity. ( A / B ) Species abundance bar plots of gut microbiota at the phylum and genus levels, respectively; ( C ) Comparison of Chao 1 index for gut microbiota diversity between groups; ( D ) Comparison of the Firmicutes -to- Bacteroidota ratio between groups. Data are presented as mean ± SEM; ns P > 0.05; ** P < 0.01.

    Article Snippet: The microbiome data analysis was conducted by Servicebio (Wuhan, China).

    Techniques: Comparison

    Species-level inter-group microbiota differences and their immune-inflammatory correlations. ( A ) Differences in microbiota abundance at the species level between groups (data presented as mean ± SEM; *** P < 0.001; ** P < 0.01; * P < 0.05); ( B / C ) Correlation analysis of unclassified Muribaculaceae abundance with serum LPS concentration (simple linear regression; P < 0.05; Pearson r = 0.67; ( B ) and ileal gland CD25 + proportion (simple linear regression; P < 0.05; Pearson r = 0.58; ( C ) within the BD + L. reuteri group; ( D ) Correlation analysis of serum LPS concentration and renal CXCL2 + proportion (simple linear regression; P < 0.05; Pearson r = 0.63; ( D ) within the BD + L. reuteri group.

    Journal: Scientific Reports

    Article Title: Gut microbiota-dependent protection by Lactobacillus reuteri against renal injury in brain-dead rats

    doi: 10.1038/s41598-026-47230-1

    Figure Lengend Snippet: Species-level inter-group microbiota differences and their immune-inflammatory correlations. ( A ) Differences in microbiota abundance at the species level between groups (data presented as mean ± SEM; *** P < 0.001; ** P < 0.01; * P < 0.05); ( B / C ) Correlation analysis of unclassified Muribaculaceae abundance with serum LPS concentration (simple linear regression; P < 0.05; Pearson r = 0.67; ( B ) and ileal gland CD25 + proportion (simple linear regression; P < 0.05; Pearson r = 0.58; ( C ) within the BD + L. reuteri group; ( D ) Correlation analysis of serum LPS concentration and renal CXCL2 + proportion (simple linear regression; P < 0.05; Pearson r = 0.63; ( D ) within the BD + L. reuteri group.

    Article Snippet: The microbiome data analysis was conducted by Servicebio (Wuhan, China).

    Techniques: Concentration Assay

    Correlation analysis between the root microbiome and metabolome at the late storage time point reveals a distinct pattern in the two highly resistant genotypes vs. the susceptible genotype. ( A ) Susceptible genotype (Sus_Ck); ( B ) resistant genotype, KSG4; and ( C ) resistant genotype, KSG6. Data are mean ± standard error of 4 replicates (each replicate consists of samples obtained from two roots). An ‘X’ sign inside the rectangular boxes in the heatmap indicates p < 0.05.

    Journal: International Journal of Molecular Sciences

    Article Title: Root Microbiome and Metabolome Traits Associated with Improved Post-Harvest Root Storage for Sugar Beet Breeding Lines Under Southern Idaho Conditions

    doi: 10.3390/ijms252312681

    Figure Lengend Snippet: Correlation analysis between the root microbiome and metabolome at the late storage time point reveals a distinct pattern in the two highly resistant genotypes vs. the susceptible genotype. ( A ) Susceptible genotype (Sus_Ck); ( B ) resistant genotype, KSG4; and ( C ) resistant genotype, KSG6. Data are mean ± standard error of 4 replicates (each replicate consists of samples obtained from two roots). An ‘X’ sign inside the rectangular boxes in the heatmap indicates p < 0.05.

    Article Snippet: The metagenomic reads obtained from the 16S sequencing were processed using the microbiome data analysis pipeline from LC Sciences (Houston, TX, USA).

    Techniques: