Automated Author ProfileHao, Yangfan
Hao, Yangfan
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: 2.1 (sum of 4 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
We identified maize lines that are highly resistant (R) or highly susceptible (S) to Goss’s wilt. Whole genome sequencing reads were collected for discovering single nucleotide polymorphisms (SNPs) using the B73 maize reference genome (version 3). We further determined read depths of two alleles of each SNP in each line. This data set includes allelic typing data for 66 maize lines.
Authors
- Liu, Sanzhen ;
- Hao, Yangfan
We identified maize lines that are highly resistant (R) or highly susceptible (S) to Goss’s wilt. Whole genome sequencing reads were collected for discovering single nucleotide polymorphisms (SNPs) using the B73 maize reference genome (version 3). We further determined read depths of two alleles of each SNP in each line. This data set includes allelic typing data for 66 maize lines.
Authors
- Liu, Sanzhen ;
- Hao, Yangfan
The data set includes genotyping data of 269 maize inbred lines developed from whole genome sequencing (WGS) data. Among them, WGS data of 254 lines are publicly available (https://doi.org/10.1093/gigascience/gix134). In addition, we generated WGS of 15 inbred lines that are resistant or susceptible to the bacterial maize disease Goss’s wilt. All WGS reads were trimmed and aligned to the B73 reference genome sequence (B73v3). Reads uniquely mapped to the reference genome were retained for variant calling. SNPs with the minor allele frequency higher than 5% and the genotyping missing data rate less than 30% were kept for genome-wide association mapping of genomic loci conferring Goss’s wilt resistance. SNP data were split to ten files each of which stores genotyping data for a chromosome.
Authors
- Hao, Yangfan ;
- Liu, Sanzhen
The data set includes genotyping data of 269 maize inbred lines developed from whole genome sequencing (WGS) data. Among them, WGS data of 254 lines are publicly available (https://doi.org/10.1093/gigascience/gix134). In addition, we generated WGS of 15 inbred lines that are resistant or susceptible to the bacterial maize disease Goss’s wilt. All WGS reads were trimmed and aligned to the B73 reference genome sequence (B73v3). Reads uniquely mapped to the reference genome were retained for variant calling. SNPs with the minor allele frequency higher than 5% and the genotyping missing data rate less than 30% were kept for genome-wide association mapping of genomic loci conferring Goss’s wilt resistance. SNP data were split to ten files each of which stores genotyping data for a chromosome.
Authors
- Hao, Yangfan ;
- Liu, Sanzhen