Log In Sign up
The largest database of trusted experimental protocols

Power tools suite v1.18

Manufactured by Thermo Fisher Scientific
Visit Supplier

Power Tools Suite (v1.18) is a collection of software tools designed to assist laboratory professionals in managing and optimizing their workflows. The suite includes a range of applications focused on streamlining common tasks, enhancing productivity, and improving data management within the laboratory environment.

Automatically generated - may contain errors

Lab products found in correlation

Axiom biobank array, by Thermo Fisher Scientific (3 mentions)

Close spelling variants of this product

Power Tools

3 protocols using power tools suite v1.18

1

Million Veteran Program Genotyping Pipeline

Cited 3 times
Check if the same lab product or an alternative is used in the 5 most similar protocols
Blood samples drawn from consenting MVP participants were shipped to the Central Biorepository in Boston, MA, where DNA was extracted and shipped to two external centers for genotyping on an Affymetrix Axiom Biobank array designed specifically for the MVP. The MVP genomics working group applied standard quality control and genotype calling algorithms to the data in batches using the Affymetrix Power Tools Suite (v1.18). Standard quality control pipelines were used to exclude duplicate samples, samples with more heterozygosity than expected, samples with an excess (>2.5%) of missing genotype calls, and samples with discordance of genetically inferred sex versus self-report. We excluded related individuals (halfway between 2nd and 3rd degree relatives or closer) as measured by the KING software83 (link). Prior to imputation, variants that were poorly called or that deviated from their expected allele frequency based on reference data from the 1000 Genomes Project84 (link) were excluded. After pre-phasing using EAGLE v285 (link), genotypes from the 1000 Genomes Project84 (link) phase 3, version 5 reference panel were imputed into Million Veteran Program (MVP) participants via Minimac3 software86 (link). Principal component analysis was performed using the FlashPCA87 (link), to generate the top 10 genetic principal components explaining the greatest variability.
Giri A., Hellwege J.N., Keaton J.M., Park J., Qiu C., Warren H.R., Torstenson E.S., Kovesdy C.P., Sun Y.V., Wilson O.D., Robinson-Cohen C., Roumie C.L., Chung C.P., Birdwell K.A., Damrauer S.M., DuVall S.L., Klarin D., Cho K., Wang Y., Evangelou E., Cabrera C.P., Wain L.V., Shrestha R., Mautz B.S., Akwo E.A., Sargurupremraj M., Debette S., Boehnke M., Scott L.J., Luan J., Jing-Hua Z., Willems S.M., Thériault S., Shah N., Oldmeadow C., Almgren P., Li-Gao R., Verweij N., Boutin T.S., Mangino M., Ntalla I., Feofanova E., Surendran P., Cook J.P., Karthikeyan S., Lahrouchi N., Liu C., Sepúlveda N., Richardson T.G., Kraja A., Amouyel P., Farrall M., Poulter N.R., Laakso M., Zeggini E., Sever P., Scott R.A., Langenberg C., Wareham N.J., Conen D., Alexander Palmer C.N., Attia J., Chasman D.I., Ridker P.M., Melander O., Mook-Kanamori D.O., van der Harst P., Cucca F., Schlessinger D., Hayward C., Spector T.D., Marjo-Riitta J., Hennig B.J., Timpson N.J., Wei-Qi W., Smith J.C., Xu Y., Matheny M.E., Siew E.E., Lindgren C., Karl-Heinz H., Dedoussis G., Denny J.C., Psaty B.M., Howson J.M., Munroe P.B., Newton-Cheh C., Caulfield M.J., Elliott P., Gaziano J.M., Concato J., Wilson P.W., Tsao P.S., Velez Edwards D.R., Susztak K., O’Donnell C.J., Hung A.M, & Edwards T.L. (2018). Trans-ethnic association study of blood pressure determinants in over 750,000 individuals. Nature genetics, 51(1), 51-62.
+ Open protocol
+ Expand
2

Large-Scale Genotyping of MVP Cohort

Check if the same lab product or an alternative is used in the 5 most similar protocols
DNA was extracted from whole blood drawn from MVP participants at the Central Biorepository in Boston, Massachusetts, USA and shipped to two external centers for genotyping. Genotyping of the MVP samples was performed using a custom Affymetrix Axiom Biobank Array as previously described [15 (link)]. The custom array includes assays for approximately 723 000 genetic variants and is enriched for validated GWAS single nucleotide polymorphisms (SNPs), exome content, and Hispanic and African ancestry markers. Standard quality control procedures and genotype calling of the data in batches using algorithms from Affymetrix Power Tools Suite (v1.18) were performed by the MVP genomics working. Sample exclusion criteria included genotypic duplicates, excess heterozygosity, call rate below 97.5%, and discordance between genetically inferred sex and phenotypic sex. Closely related individuals (halfway between second and third degree relatives or closer) as measured using the KING software program [18 ] were removed. Variants with low call rate or that diverged from allele frequencies in 1000 Genomes Project [19 (link)] reference data were excluded from subsequent analyses.
Keaton J.M., Hellwege J.N., Giri A., Torstenson E.S., Kovesdy C.P., Sun Y.V., Wilson P.W., O’Donnell C.J., Edwards T.L., Hung A.M, & Velez Edwards D.R. (2021). Associations of biogeographic ancestry with hypertension traits. Journal of hypertension, 39(4), 633-642.
+ Open protocol
+ Expand
3

Million Veteran Program Genotyping Pipeline

Cited 3 times
Check if the same lab product or an alternative is used in the 5 most similar protocols
Blood samples drawn from consenting MVP participants were shipped to the Central Biorepository in Boston, MA, where DNA was extracted and shipped to two external centers for genotyping on an Affymetrix Axiom Biobank array designed specifically for the MVP. The MVP genomics working group applied standard quality control and genotype calling algorithms to the data in batches using the Affymetrix Power Tools Suite (v1.18). Standard quality control pipelines were used to exclude duplicate samples, samples with more heterozygosity than expected, samples with an excess (>2.5%) of missing genotype calls, and samples with discordance of genetically inferred sex versus self-report. We excluded related individuals (halfway between 2nd and 3rd degree relatives or closer) as measured by the KING software83 (link). Prior to imputation, variants that were poorly called or that deviated from their expected allele frequency based on reference data from the 1000 Genomes Project84 (link) were excluded. After pre-phasing using EAGLE v285 (link), genotypes from the 1000 Genomes Project84 (link) phase 3, version 5 reference panel were imputed into Million Veteran Program (MVP) participants via Minimac3 software86 (link). Principal component analysis was performed using the FlashPCA87 (link), to generate the top 10 genetic principal components explaining the greatest variability.
Giri A., Hellwege J.N., Keaton J.M., Park J., Qiu C., Warren H.R., Torstenson E.S., Kovesdy C.P., Sun Y.V., Wilson O.D., Robinson-Cohen C., Roumie C.L., Chung C.P., Birdwell K.A., Damrauer S.M., DuVall S.L., Klarin D., Cho K., Wang Y., Evangelou E., Cabrera C.P., Wain L.V., Shrestha R., Mautz B.S., Akwo E.A., Sargurupremraj M., Debette S., Boehnke M., Scott L.J., Luan J., Jing-Hua Z., Willems S.M., Thériault S., Shah N., Oldmeadow C., Almgren P., Li-Gao R., Verweij N., Boutin T.S., Mangino M., Ntalla I., Feofanova E., Surendran P., Cook J.P., Karthikeyan S., Lahrouchi N., Liu C., Sepúlveda N., Richardson T.G., Kraja A., Amouyel P., Farrall M., Poulter N.R., Laakso M., Zeggini E., Sever P., Scott R.A., Langenberg C., Wareham N.J., Conen D., Alexander Palmer C.N., Attia J., Chasman D.I., Ridker P.M., Melander O., Mook-Kanamori D.O., van der Harst P., Cucca F., Schlessinger D., Hayward C., Spector T.D., Marjo-Riitta J., Hennig B.J., Timpson N.J., Wei-Qi W., Smith J.C., Xu Y., Matheny M.E., Siew E.E., Lindgren C., Karl-Heinz H., Dedoussis G., Denny J.C., Psaty B.M., Howson J.M., Munroe P.B., Newton-Cheh C., Caulfield M.J., Elliott P., Gaziano J.M., Concato J., Wilson P.W., Tsao P.S., Velez Edwards D.R., Susztak K., O’Donnell C.J., Hung A.M, & Edwards T.L. (2018). Trans-ethnic association study of blood pressure determinants in over 750,000 individuals. Nature genetics, 51(1), 51-62.
+ Open protocol
+ Expand

About PubCompare

Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.

We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.

However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.

Ready to get started?

Sign up for free.
Registration takes 20 seconds.
Available from any computer
No download required

Sign up now

Revolutionizing how scientists
search and build protocols!