Automated Author ProfileSarmiento, Juan
Sarmiento, Juan
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: 0.8 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
These datasets contain data on analyses of TE expression stability. Raw RNA seq counts were processed using DESeq2 R package. Low count genes and TEs were removed. Counts across samples were normalized for library sizes and log-transformed using 'regularized log' transformation. Batch normalization was performed on log-transformed data with ComBat function from sva R package. Expression variability (EV) of TEs and genes (probes) was estimated using the previously described method [1, 2]. 1. Bashkeel, N., Perkins, T.J., Kærn, M. et al. Human gene expression variability and its dependence on methylation and aging. BMC Genomics 20, 941 (2019). https://doi.org/10.1186/s12864-019-6308-7
2. Alemu EY, Carl JW Jr, Corrada Bravo H, Hannenhalli S. Determinants of expression variability. Nucleic Acids Res. 2014;42(6):3503-3514. doi:10.1093/nar/gkt1364 PC.zip - the results of TE expression and stability in prostate cancer. 0.PC.RlogMAD.pdf - count barplots for TE identified with MAD criteria 0.PC.RlogSD.pdf - count barplots for TE identified with SD criteria 0.PC.TE.rlogcpm.mad.xls -stability measures according MAD (median absolute deviance) criteria 0.PC.TE.rlogcpm.sd.xls - stability measures according SD criteria 0.PC_TE_bootstrap.pdf - TE expression stability PC.deseq.logCPM.csv - TE log transformed expression matrix PC.TE_count_table.csv - TE raw count matrix PC_Deseq2data.Rdata - R data object with deseq objet, raw and normalized counts MM.zip - the results of TE expression and stability in multiple myeloma. 0.MM.RlogMAD.pdf - count barplots for TE identified with MAD criteria 0.MM.RlogSD.pdf - count barplots for TE identified with SD criteria 0.MM_TE_bootstrap.pdf - TE expression stability MM.deseq.logCPM.csv - TE raw count matrix MM.rlog.mad.xlsx- stability measures according MAD (median absolute deviance) criteria MM.rlog.sd.xlsx - stability measures according MAD (median absolute deviance) criteria MM.TE_count_table.csv - TE raw count matrix Myeloma_Deseq2data.Rdata - R data object with deseq objet, raw and normalized counts
Authors
- Munevver Cinar ;
- Martinez-Medina, Lourdes ;
- Pavan K. Puvvula ;
- Arakelyan, Arsen ;
- Vardarajan, Badri N. ;
- Anthony, Neil ;
- Ganji P. Nagaraju ;
- Dongkyoo Park ;
- Feng, Lei ;
- Sheff, Faith ;
- Mosunjac, Marina ;
- Saxe, Debra ;
- Flygare, Steven ;
- Olatunji B. Alese ;
- Kaufman, Jonathan ;
- Lonial, Sagar ;
- Sarmiento, Juan ;
- Izidore S. Lossos ;
- Vertino, Paula M. ;
- Lopez, Jose A. ;
- El-Rayes, Bassel ;
- Bernal-Mizrachi, Leon
These datasets contain data on analyses of TE expression stability. Raw RNA seq counts were processed using DESeq2 R package. Low count genes and TEs were removed. Counts across samples were normalized for library sizes and log-transformed using 'regularized log' transformation. Batch normalization was performed on log-transformed data with ComBat function from sva R package. Expression variability (EV) of TEs and genes (probes) was estimated using the previously described method [1, 2]. 1. Bashkeel, N., Perkins, T.J., Kærn, M. et al. Human gene expression variability and its dependence on methylation and aging. BMC Genomics 20, 941 (2019). https://doi.org/10.1186/s12864-019-6308-7
2. Alemu EY, Carl JW Jr, Corrada Bravo H, Hannenhalli S. Determinants of expression variability. Nucleic Acids Res. 2014;42(6):3503-3514. doi:10.1093/nar/gkt1364 PC.zip - the results of TE expression and stability in prostate cancer. 0.PC.RlogMAD.pdf - count barplots for TE identified with MAD criteria 0.PC.RlogSD.pdf - count barplots for TE identified with SD criteria 0.PC.TE.rlogcpm.mad.xls -stability measures according MAD (median absolute deviance) criteria 0.PC.TE.rlogcpm.sd.xls - stability measures according SD criteria 0.PC_TE_bootstrap.pdf - TE expression stability PC.deseq.logCPM.csv - TE log transformed expression matrix PC.TE_count_table.csv - TE raw count matrix PC_Deseq2data.Rdata - R data object with deseq objet, raw and normalized counts MM.zip - the results of TE expression and stability in multiple myeloma. 0.MM.RlogMAD.pdf - count barplots for TE identified with MAD criteria 0.MM.RlogSD.pdf - count barplots for TE identified with SD criteria 0.MM_TE_bootstrap.pdf - TE expression stability MM.deseq.logCPM.csv - TE raw count matrix MM.rlog.mad.xlsx- stability measures according MAD (median absolute deviance) criteria MM.rlog.sd.xlsx - stability measures according MAD (median absolute deviance) criteria MM.TE_count_table.csv - TE raw count matrix Myeloma_Deseq2data.Rdata - R data object with deseq objet, raw and normalized counts
Authors
- Munevver Cinar ;
- Martinez-Medina, Lourdes ;
- Pavan K. Puvvula ;
- Arakelyan, Arsen ;
- Vardarajan, Badri N. ;
- Anthony, Neil ;
- Ganji P. Nagaraju ;
- Dongkyoo Park ;
- Feng, Lei ;
- Sheff, Faith ;
- Mosunjac, Marina ;
- Saxe, Debra ;
- Flygare, Steven ;
- Olatunji B. Alese ;
- Kaufman, Jonathan ;
- Lonial, Sagar ;
- Sarmiento, Juan ;
- Izidore S. Lossos ;
- Vertino, Paula M. ;
- Lopez, Jose A. ;
- El-Rayes, Bassel ;
- Bernal-Mizrachi, Leon