correlation coefficient analysis (cc) Search Results


intra-class correlation estimates (iccs)  (RStudio)
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RStudio intra-class correlation estimates (iccs)
Intra Class Correlation Estimates (Iccs), supplied by RStudio, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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correlation coefficient analysis  (GraphPad Software Inc)
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GraphPad Software Inc correlation coefficient analysis
Correlation Coefficient Analysis, supplied by GraphPad Software Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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correlation analysis using pearson correlation coefficient  (SYSTAT)
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SYSTAT correlation analysis using pearson correlation coefficient
Correlation Analysis Using Pearson Correlation Coefficient, supplied by SYSTAT, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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simple correlation analysis (pearson’s correlation coefficient)  (SYSTAT)
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SYSTAT simple correlation analysis (pearson’s correlation coefficient)
Simple Correlation Analysis (Pearson’s Correlation Coefficient), supplied by SYSTAT, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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correlation analysis and coefficient calculation  (GraphPad Software Inc)
90
GraphPad Software Inc correlation analysis and coefficient calculation
Correlation Analysis And Coefficient Calculation, supplied by GraphPad Software Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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linear correlation analysis using 2-tailed pearson correlation coefficient  (GraphPad Software Inc)
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GraphPad Software Inc linear correlation analysis using 2-tailed pearson correlation coefficient
Linear Correlation Analysis Using 2 Tailed Pearson Correlation Coefficient, supplied by GraphPad Software Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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spearman’s correlation coefficient analysis  (BGI Shenzhen)
90
BGI Shenzhen spearman’s correlation coefficient analysis
Bacterial richness and diversity analysis. (A) We found 510 shared universal OTUs in samples from both FHRAC-positive and FHRAC-negative patients. FHRAC-positive patients contained more unique OTUs than did FHRAC-negative patients (554 vs. 538 OTUs). (B) α-diversity analysis showed no significant differences in the Simpson’s, Shannon’s, Sobs, abundance-based coverage estimator (ACE), Chao, or other observed species indexes between the two groups ( P > 0.05). (C) Microbial community diversity in the FHRAC-positive patients was significantly lower than that of the FHRAC-negative patients ( P < 0.05). (D) Twenty-seven microbial genera were detected. In FHRAC-positive patients, Bacteroides , Escherichia , Others, Faecalibacterium , Phascolarctobacterium , Prevotella , Lachnospiraceae incertae , Megamonas , Veillonella , and Megasphaera were the top genera, constituting 79% of the taxa. Escherichia , Others, Bacteroides , Megamonas , Prevotella , Faecalibacterium , Gemmiger , Ruminococcus , Megasphaera and Citrobacter were the top genera in the FHRAC-negative patients (78%). (E) The Wilcoxon test was used to compare the significantly different top 10 genera. Lachnospiraceae_incertae_sedis was higher in FHRAC-positive patients than in FHRAC-negative patients. (F) linear discriminant analysis (LDA) effect-size (LEfSe) analysis showed that FHRAC-negative patient samples contained mainly Epsilonproteobacteria at the class level, Campylobacterales and Actinomycetales at the order level and Campylobacteraceae at the family level. (G) Lachnospiraceae_incertae_sedis , Anaerostipes , Actinomycetales , Desulfovibrio , Barnesiella , Lachnospira , Campylobacteraceae , Epsilonproteobacteria , Campylobacterales , Campylobacter , and Klebsiella were differentially expressed among the taxonomic levels. (H) We detected 157 metabolites or pathways at the KEGG level 3. The Wilcoxon test was used to compare the significantly different features. The differentially expressed microbiota were closely related to four differential metabolic pathways, including glycosaminoglycan degradation. (I) The Spearman’s correlation <t>coefficient</t> showed an association between clinical manifestations and microbial taxa. Glycosaminoglycan degradation was positively correlated with albumin (ALB). Lachnospiraceae_incertae_sedis was positively correlated with IgG. *P<0.05.
Spearman’s Correlation Coefficient Analysis, supplied by BGI Shenzhen, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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pairwise correlation coefficient analysis  (SAS institute)
90
SAS institute pairwise correlation coefficient analysis
Bacterial richness and diversity analysis. (A) We found 510 shared universal OTUs in samples from both FHRAC-positive and FHRAC-negative patients. FHRAC-positive patients contained more unique OTUs than did FHRAC-negative patients (554 vs. 538 OTUs). (B) α-diversity analysis showed no significant differences in the Simpson’s, Shannon’s, Sobs, abundance-based coverage estimator (ACE), Chao, or other observed species indexes between the two groups ( P > 0.05). (C) Microbial community diversity in the FHRAC-positive patients was significantly lower than that of the FHRAC-negative patients ( P < 0.05). (D) Twenty-seven microbial genera were detected. In FHRAC-positive patients, Bacteroides , Escherichia , Others, Faecalibacterium , Phascolarctobacterium , Prevotella , Lachnospiraceae incertae , Megamonas , Veillonella , and Megasphaera were the top genera, constituting 79% of the taxa. Escherichia , Others, Bacteroides , Megamonas , Prevotella , Faecalibacterium , Gemmiger , Ruminococcus , Megasphaera and Citrobacter were the top genera in the FHRAC-negative patients (78%). (E) The Wilcoxon test was used to compare the significantly different top 10 genera. Lachnospiraceae_incertae_sedis was higher in FHRAC-positive patients than in FHRAC-negative patients. (F) linear discriminant analysis (LDA) effect-size (LEfSe) analysis showed that FHRAC-negative patient samples contained mainly Epsilonproteobacteria at the class level, Campylobacterales and Actinomycetales at the order level and Campylobacteraceae at the family level. (G) Lachnospiraceae_incertae_sedis , Anaerostipes , Actinomycetales , Desulfovibrio , Barnesiella , Lachnospira , Campylobacteraceae , Epsilonproteobacteria , Campylobacterales , Campylobacter , and Klebsiella were differentially expressed among the taxonomic levels. (H) We detected 157 metabolites or pathways at the KEGG level 3. The Wilcoxon test was used to compare the significantly different features. The differentially expressed microbiota were closely related to four differential metabolic pathways, including glycosaminoglycan degradation. (I) The Spearman’s correlation <t>coefficient</t> showed an association between clinical manifestations and microbial taxa. Glycosaminoglycan degradation was positively correlated with albumin (ALB). Lachnospiraceae_incertae_sedis was positively correlated with IgG. *P<0.05.
Pairwise Correlation Coefficient Analysis, supplied by SAS institute, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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non-parametric spearman’s rank correlation coefficient analysis  (SPSS Inc)
90
SPSS Inc non-parametric spearman’s rank correlation coefficient analysis
Bacterial richness and diversity analysis. (A) We found 510 shared universal OTUs in samples from both FHRAC-positive and FHRAC-negative patients. FHRAC-positive patients contained more unique OTUs than did FHRAC-negative patients (554 vs. 538 OTUs). (B) α-diversity analysis showed no significant differences in the Simpson’s, Shannon’s, Sobs, abundance-based coverage estimator (ACE), Chao, or other observed species indexes between the two groups ( P > 0.05). (C) Microbial community diversity in the FHRAC-positive patients was significantly lower than that of the FHRAC-negative patients ( P < 0.05). (D) Twenty-seven microbial genera were detected. In FHRAC-positive patients, Bacteroides , Escherichia , Others, Faecalibacterium , Phascolarctobacterium , Prevotella , Lachnospiraceae incertae , Megamonas , Veillonella , and Megasphaera were the top genera, constituting 79% of the taxa. Escherichia , Others, Bacteroides , Megamonas , Prevotella , Faecalibacterium , Gemmiger , Ruminococcus , Megasphaera and Citrobacter were the top genera in the FHRAC-negative patients (78%). (E) The Wilcoxon test was used to compare the significantly different top 10 genera. Lachnospiraceae_incertae_sedis was higher in FHRAC-positive patients than in FHRAC-negative patients. (F) linear discriminant analysis (LDA) effect-size (LEfSe) analysis showed that FHRAC-negative patient samples contained mainly Epsilonproteobacteria at the class level, Campylobacterales and Actinomycetales at the order level and Campylobacteraceae at the family level. (G) Lachnospiraceae_incertae_sedis , Anaerostipes , Actinomycetales , Desulfovibrio , Barnesiella , Lachnospira , Campylobacteraceae , Epsilonproteobacteria , Campylobacterales , Campylobacter , and Klebsiella were differentially expressed among the taxonomic levels. (H) We detected 157 metabolites or pathways at the KEGG level 3. The Wilcoxon test was used to compare the significantly different features. The differentially expressed microbiota were closely related to four differential metabolic pathways, including glycosaminoglycan degradation. (I) The Spearman’s correlation <t>coefficient</t> showed an association between clinical manifestations and microbial taxa. Glycosaminoglycan degradation was positively correlated with albumin (ALB). Lachnospiraceae_incertae_sedis was positively correlated with IgG. *P<0.05.
Non Parametric Spearman’s Rank Correlation Coefficient Analysis, supplied by SPSS Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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kruskal-wallis test and pearson correlation coefficient analysis  (RStudio)
90
RStudio kruskal-wallis test and pearson correlation coefficient analysis
Bacterial richness and diversity analysis. (A) We found 510 shared universal OTUs in samples from both FHRAC-positive and FHRAC-negative patients. FHRAC-positive patients contained more unique OTUs than did FHRAC-negative patients (554 vs. 538 OTUs). (B) α-diversity analysis showed no significant differences in the Simpson’s, Shannon’s, Sobs, abundance-based coverage estimator (ACE), Chao, or other observed species indexes between the two groups ( P > 0.05). (C) Microbial community diversity in the FHRAC-positive patients was significantly lower than that of the FHRAC-negative patients ( P < 0.05). (D) Twenty-seven microbial genera were detected. In FHRAC-positive patients, Bacteroides , Escherichia , Others, Faecalibacterium , Phascolarctobacterium , Prevotella , Lachnospiraceae incertae , Megamonas , Veillonella , and Megasphaera were the top genera, constituting 79% of the taxa. Escherichia , Others, Bacteroides , Megamonas , Prevotella , Faecalibacterium , Gemmiger , Ruminococcus , Megasphaera and Citrobacter were the top genera in the FHRAC-negative patients (78%). (E) The Wilcoxon test was used to compare the significantly different top 10 genera. Lachnospiraceae_incertae_sedis was higher in FHRAC-positive patients than in FHRAC-negative patients. (F) linear discriminant analysis (LDA) effect-size (LEfSe) analysis showed that FHRAC-negative patient samples contained mainly Epsilonproteobacteria at the class level, Campylobacterales and Actinomycetales at the order level and Campylobacteraceae at the family level. (G) Lachnospiraceae_incertae_sedis , Anaerostipes , Actinomycetales , Desulfovibrio , Barnesiella , Lachnospira , Campylobacteraceae , Epsilonproteobacteria , Campylobacterales , Campylobacter , and Klebsiella were differentially expressed among the taxonomic levels. (H) We detected 157 metabolites or pathways at the KEGG level 3. The Wilcoxon test was used to compare the significantly different features. The differentially expressed microbiota were closely related to four differential metabolic pathways, including glycosaminoglycan degradation. (I) The Spearman’s correlation <t>coefficient</t> showed an association between clinical manifestations and microbial taxa. Glycosaminoglycan degradation was positively correlated with albumin (ALB). Lachnospiraceae_incertae_sedis was positively correlated with IgG. *P<0.05.
Kruskal Wallis Test And Pearson Correlation Coefficient Analysis, supplied by RStudio, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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correlation coefficient analysis  (Minitab Inc)
90
Minitab Inc correlation coefficient analysis
Bacterial richness and diversity analysis. (A) We found 510 shared universal OTUs in samples from both FHRAC-positive and FHRAC-negative patients. FHRAC-positive patients contained more unique OTUs than did FHRAC-negative patients (554 vs. 538 OTUs). (B) α-diversity analysis showed no significant differences in the Simpson’s, Shannon’s, Sobs, abundance-based coverage estimator (ACE), Chao, or other observed species indexes between the two groups ( P > 0.05). (C) Microbial community diversity in the FHRAC-positive patients was significantly lower than that of the FHRAC-negative patients ( P < 0.05). (D) Twenty-seven microbial genera were detected. In FHRAC-positive patients, Bacteroides , Escherichia , Others, Faecalibacterium , Phascolarctobacterium , Prevotella , Lachnospiraceae incertae , Megamonas , Veillonella , and Megasphaera were the top genera, constituting 79% of the taxa. Escherichia , Others, Bacteroides , Megamonas , Prevotella , Faecalibacterium , Gemmiger , Ruminococcus , Megasphaera and Citrobacter were the top genera in the FHRAC-negative patients (78%). (E) The Wilcoxon test was used to compare the significantly different top 10 genera. Lachnospiraceae_incertae_sedis was higher in FHRAC-positive patients than in FHRAC-negative patients. (F) linear discriminant analysis (LDA) effect-size (LEfSe) analysis showed that FHRAC-negative patient samples contained mainly Epsilonproteobacteria at the class level, Campylobacterales and Actinomycetales at the order level and Campylobacteraceae at the family level. (G) Lachnospiraceae_incertae_sedis , Anaerostipes , Actinomycetales , Desulfovibrio , Barnesiella , Lachnospira , Campylobacteraceae , Epsilonproteobacteria , Campylobacterales , Campylobacter , and Klebsiella were differentially expressed among the taxonomic levels. (H) We detected 157 metabolites or pathways at the KEGG level 3. The Wilcoxon test was used to compare the significantly different features. The differentially expressed microbiota were closely related to four differential metabolic pathways, including glycosaminoglycan degradation. (I) The Spearman’s correlation <t>coefficient</t> showed an association between clinical manifestations and microbial taxa. Glycosaminoglycan degradation was positively correlated with albumin (ALB). Lachnospiraceae_incertae_sedis was positively correlated with IgG. *P<0.05.
Correlation Coefficient Analysis, supplied by Minitab Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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spearman correlation coefficients calculated by multivariate analysis-non-parametric correlations  (SAS institute)
90
SAS institute spearman correlation coefficients calculated by multivariate analysis-non-parametric correlations
Bacterial richness and diversity analysis. (A) We found 510 shared universal OTUs in samples from both FHRAC-positive and FHRAC-negative patients. FHRAC-positive patients contained more unique OTUs than did FHRAC-negative patients (554 vs. 538 OTUs). (B) α-diversity analysis showed no significant differences in the Simpson’s, Shannon’s, Sobs, abundance-based coverage estimator (ACE), Chao, or other observed species indexes between the two groups ( P > 0.05). (C) Microbial community diversity in the FHRAC-positive patients was significantly lower than that of the FHRAC-negative patients ( P < 0.05). (D) Twenty-seven microbial genera were detected. In FHRAC-positive patients, Bacteroides , Escherichia , Others, Faecalibacterium , Phascolarctobacterium , Prevotella , Lachnospiraceae incertae , Megamonas , Veillonella , and Megasphaera were the top genera, constituting 79% of the taxa. Escherichia , Others, Bacteroides , Megamonas , Prevotella , Faecalibacterium , Gemmiger , Ruminococcus , Megasphaera and Citrobacter were the top genera in the FHRAC-negative patients (78%). (E) The Wilcoxon test was used to compare the significantly different top 10 genera. Lachnospiraceae_incertae_sedis was higher in FHRAC-positive patients than in FHRAC-negative patients. (F) linear discriminant analysis (LDA) effect-size (LEfSe) analysis showed that FHRAC-negative patient samples contained mainly Epsilonproteobacteria at the class level, Campylobacterales and Actinomycetales at the order level and Campylobacteraceae at the family level. (G) Lachnospiraceae_incertae_sedis , Anaerostipes , Actinomycetales , Desulfovibrio , Barnesiella , Lachnospira , Campylobacteraceae , Epsilonproteobacteria , Campylobacterales , Campylobacter , and Klebsiella were differentially expressed among the taxonomic levels. (H) We detected 157 metabolites or pathways at the KEGG level 3. The Wilcoxon test was used to compare the significantly different features. The differentially expressed microbiota were closely related to four differential metabolic pathways, including glycosaminoglycan degradation. (I) The Spearman’s correlation <t>coefficient</t> showed an association between clinical manifestations and microbial taxa. Glycosaminoglycan degradation was positively correlated with albumin (ALB). Lachnospiraceae_incertae_sedis was positively correlated with IgG. *P<0.05.
Spearman Correlation Coefficients Calculated By Multivariate Analysis Non Parametric Correlations, supplied by SAS institute, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


Bacterial richness and diversity analysis. (A) We found 510 shared universal OTUs in samples from both FHRAC-positive and FHRAC-negative patients. FHRAC-positive patients contained more unique OTUs than did FHRAC-negative patients (554 vs. 538 OTUs). (B) α-diversity analysis showed no significant differences in the Simpson’s, Shannon’s, Sobs, abundance-based coverage estimator (ACE), Chao, or other observed species indexes between the two groups ( P > 0.05). (C) Microbial community diversity in the FHRAC-positive patients was significantly lower than that of the FHRAC-negative patients ( P < 0.05). (D) Twenty-seven microbial genera were detected. In FHRAC-positive patients, Bacteroides , Escherichia , Others, Faecalibacterium , Phascolarctobacterium , Prevotella , Lachnospiraceae incertae , Megamonas , Veillonella , and Megasphaera were the top genera, constituting 79% of the taxa. Escherichia , Others, Bacteroides , Megamonas , Prevotella , Faecalibacterium , Gemmiger , Ruminococcus , Megasphaera and Citrobacter were the top genera in the FHRAC-negative patients (78%). (E) The Wilcoxon test was used to compare the significantly different top 10 genera. Lachnospiraceae_incertae_sedis was higher in FHRAC-positive patients than in FHRAC-negative patients. (F) linear discriminant analysis (LDA) effect-size (LEfSe) analysis showed that FHRAC-negative patient samples contained mainly Epsilonproteobacteria at the class level, Campylobacterales and Actinomycetales at the order level and Campylobacteraceae at the family level. (G) Lachnospiraceae_incertae_sedis , Anaerostipes , Actinomycetales , Desulfovibrio , Barnesiella , Lachnospira , Campylobacteraceae , Epsilonproteobacteria , Campylobacterales , Campylobacter , and Klebsiella were differentially expressed among the taxonomic levels. (H) We detected 157 metabolites or pathways at the KEGG level 3. The Wilcoxon test was used to compare the significantly different features. The differentially expressed microbiota were closely related to four differential metabolic pathways, including glycosaminoglycan degradation. (I) The Spearman’s correlation coefficient showed an association between clinical manifestations and microbial taxa. Glycosaminoglycan degradation was positively correlated with albumin (ALB). Lachnospiraceae_incertae_sedis was positively correlated with IgG. *P<0.05.

Journal: Frontiers in Immunology

Article Title: Disease predisposition of human leukocyte antigen class II genes influences the gut microbiota composition in patients with primary biliary cholangitis

doi: 10.3389/fimmu.2022.984697

Figure Lengend Snippet: Bacterial richness and diversity analysis. (A) We found 510 shared universal OTUs in samples from both FHRAC-positive and FHRAC-negative patients. FHRAC-positive patients contained more unique OTUs than did FHRAC-negative patients (554 vs. 538 OTUs). (B) α-diversity analysis showed no significant differences in the Simpson’s, Shannon’s, Sobs, abundance-based coverage estimator (ACE), Chao, or other observed species indexes between the two groups ( P > 0.05). (C) Microbial community diversity in the FHRAC-positive patients was significantly lower than that of the FHRAC-negative patients ( P < 0.05). (D) Twenty-seven microbial genera were detected. In FHRAC-positive patients, Bacteroides , Escherichia , Others, Faecalibacterium , Phascolarctobacterium , Prevotella , Lachnospiraceae incertae , Megamonas , Veillonella , and Megasphaera were the top genera, constituting 79% of the taxa. Escherichia , Others, Bacteroides , Megamonas , Prevotella , Faecalibacterium , Gemmiger , Ruminococcus , Megasphaera and Citrobacter were the top genera in the FHRAC-negative patients (78%). (E) The Wilcoxon test was used to compare the significantly different top 10 genera. Lachnospiraceae_incertae_sedis was higher in FHRAC-positive patients than in FHRAC-negative patients. (F) linear discriminant analysis (LDA) effect-size (LEfSe) analysis showed that FHRAC-negative patient samples contained mainly Epsilonproteobacteria at the class level, Campylobacterales and Actinomycetales at the order level and Campylobacteraceae at the family level. (G) Lachnospiraceae_incertae_sedis , Anaerostipes , Actinomycetales , Desulfovibrio , Barnesiella , Lachnospira , Campylobacteraceae , Epsilonproteobacteria , Campylobacterales , Campylobacter , and Klebsiella were differentially expressed among the taxonomic levels. (H) We detected 157 metabolites or pathways at the KEGG level 3. The Wilcoxon test was used to compare the significantly different features. The differentially expressed microbiota were closely related to four differential metabolic pathways, including glycosaminoglycan degradation. (I) The Spearman’s correlation coefficient showed an association between clinical manifestations and microbial taxa. Glycosaminoglycan degradation was positively correlated with albumin (ALB). Lachnospiraceae_incertae_sedis was positively correlated with IgG. *P<0.05.

Article Snippet: Spearman’s correlation coefficient analysis of the species revealed important patterns and relationships among dominant species ( BGI-Shenzhen, Shenzhen, China).

Techniques: