Automated Author ProfileHuber, Paula
Federal University of São Carlos
Huber, Paula
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.7 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Additional file 1: Table S1. Metadata associated with samples from the EukBank dataset analyzed in this work. Table S2. List of picozoan operational taxonomic units (pOTUs) obtained from the EukBank amplicon dataset. Each row corresponds to one unique OTU identified based on 18S rDNA sequence. Table S3. PERMANOVA analysis to determine whether Picozoa communities structure differed among latitudinal rank. Table S4. Kruskal–Wallis analysis to determine whether pairwise NMTD values calculated from Picozoa communities differed among latitudinal rank. Fig. S1. Relative contribution of high-rank Protistan groups (indicated by different colors) to the total number of reads (represented by different areas) in the EukBank dataset (12,549 samples). Fig. S2. Picozoa presence across environments. Colors indicate the percentage of samples where Picozoa was detected in each environmental category. The grey bar indicates the percentage of samples where Picozoa was not detected. Fig. S3. Picozoa relative contribution (in yellow) to the total eukaryotic reads number (in white). Only samples where Picozoa constituted more than 5% of the total eukaryotic reads are presented. Fig. S4. Box Plot showing community features at the sunlit vs. dark ocean. For each community feature, the values were normalized to vary between 0 and 1. Significative differences are indicated with different letters (Test Student, p < s0.001). Fig. S5. 18S rDNA maximum likelihood phylogenetic tree based on Picozoa Reference Tree (Fig. 3) showing the phylogenetic relationships of the pOTUs from EukBank dataset. The tree was constructed with the GTRCATI considering 1000 replicate trees for topology and 1000 trees for bootstrapping using reference sequences and amplicon pOTUs. Fig. S6. Latitudinal Distribution of Abundant pOTUs. This figure shows the abundance patterns (log-transformed) of each abundant pOTU across latitudes, organized by their associated category based on abundance and occupancy patterns in the sunlit ocean. Widespread pOTUs are indicated in green, Polar in blue, and Non-polar in red. Fig. S7. Estimated niche breadth using kernel density for Widespread (green), Polar (blue), and Non-Polar (red) pOTUs. Fig. S8. MNTD values by latitudinal rank for Picozoa Communities (see Supplementary Table S4 for pairwise comparison statistical test). Fig. S9. (a) Relationships between niche overlap (Schoener's D index) and phylogenetic distance (normalized to vary between 0 and 1) for abundant pOTUs, confirming the absence of niche conservatisms in Picozoa. Specific color dots highlight pairwise relationships among pOTUs within the same clade, while grey dots represent pairwise relationships between pOTUs from different clades. (b) Mantel correlograms (Pearson correlations) between pOTU environmental optimal distances and phylogenetic distances with 9 999 permutations. Significant correlations (P < 0.05) were not detected over phylogenetic distances. For each phylogenetic distance, bin phylogenetic distances were normalized to vary between 0 and 1 before analysis.
Authors
- Huber, Paula ;
- De Angelis, Daniele ;
- Sarmento, Hugo ;
- Metz, Sebastian ;
- Giner, Caterina R. ;
- Vargas, Colomban De ;
- Maiorano, Luigi ;
- Massana, Ramon ;
- Logares, Ramiro
Additional file 1: Table S1. Metadata associated with samples from the EukBank dataset analyzed in this work. Table S2. List of picozoan operational taxonomic units (pOTUs) obtained from the EukBank amplicon dataset. Each row corresponds to one unique OTU identified based on 18S rDNA sequence. Table S3. PERMANOVA analysis to determine whether Picozoa communities structure differed among latitudinal rank. Table S4. Kruskal–Wallis analysis to determine whether pairwise NMTD values calculated from Picozoa communities differed among latitudinal rank. Fig. S1. Relative contribution of high-rank Protistan groups (indicated by different colors) to the total number of reads (represented by different areas) in the EukBank dataset (12,549 samples). Fig. S2. Picozoa presence across environments. Colors indicate the percentage of samples where Picozoa was detected in each environmental category. The grey bar indicates the percentage of samples where Picozoa was not detected. Fig. S3. Picozoa relative contribution (in yellow) to the total eukaryotic reads number (in white). Only samples where Picozoa constituted more than 5% of the total eukaryotic reads are presented. Fig. S4. Box Plot showing community features at the sunlit vs. dark ocean. For each community feature, the values were normalized to vary between 0 and 1. Significative differences are indicated with different letters (Test Student, p < s0.001). Fig. S5. 18S rDNA maximum likelihood phylogenetic tree based on Picozoa Reference Tree (Fig. 3) showing the phylogenetic relationships of the pOTUs from EukBank dataset. The tree was constructed with the GTRCATI considering 1000 replicate trees for topology and 1000 trees for bootstrapping using reference sequences and amplicon pOTUs. Fig. S6. Latitudinal Distribution of Abundant pOTUs. This figure shows the abundance patterns (log-transformed) of each abundant pOTU across latitudes, organized by their associated category based on abundance and occupancy patterns in the sunlit ocean. Widespread pOTUs are indicated in green, Polar in blue, and Non-polar in red. Fig. S7. Estimated niche breadth using kernel density for Widespread (green), Polar (blue), and Non-Polar (red) pOTUs. Fig. S8. MNTD values by latitudinal rank for Picozoa Communities (see Supplementary Table S4 for pairwise comparison statistical test). Fig. S9. (a) Relationships between niche overlap (Schoener's D index) and phylogenetic distance (normalized to vary between 0 and 1) for abundant pOTUs, confirming the absence of niche conservatisms in Picozoa. Specific color dots highlight pairwise relationships among pOTUs within the same clade, while grey dots represent pairwise relationships between pOTUs from different clades. (b) Mantel correlograms (Pearson correlations) between pOTU environmental optimal distances and phylogenetic distances with 9 999 permutations. Significant correlations (P < 0.05) were not detected over phylogenetic distances. For each phylogenetic distance, bin phylogenetic distances were normalized to vary between 0 and 1 before analysis.
Authors
- Huber, Paula ;
- De Angelis, Daniele ;
- Sarmento, Hugo ;
- Metz, Sebastian ;
- Giner, Caterina R. ;
- Vargas, Colomban De ;
- Maiorano, Luigi ;
- Massana, Ramon ;
- Logares, Ramiro