Power tool

Manufactured by Thermo Fisher Scientific

Sourced in United States

Power Tools are a type of lab equipment designed to provide mechanical power for various tasks. They are typically used to perform tasks such as drilling, grinding, sanding, and cutting, which are essential in laboratory settings. Power Tools are available in various sizes and configurations to accommodate different laboratory needs.

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Power Tools software (13 citations) Affymetrix Power Tools (11 citations) Power Tools (APT) (7 citations) Power Tools v1.16.0 (APT) (6 citations) Power Tools Suite (v1.18). (3 citations) Affymetrix Power Tools Software (2 citations) Analysis Power Tools 2.10.2.2 (2 citations) Analysis Power Tools (2 citations) Power Tools bundle (2 citations) Power Tools (APT) Software (2 citations)

102 protocols using power tool

Genome-wide Linkage Analysis of Recessive Inheritance

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Ten members of the Israeli family (P1, P2, their four parents, their
three healthy siblings including two sisters and one brother, a grandmother
of P1) and five members of the Portuguese family (P5, P6, their two parents,
their healthy brother) were genotyped with the Affymetrix genome-wide SNP
6.0 array. Genotype calling was achieved with Affymetrix Power Tools
(www.affymetrix.com/partners_programs/programs/developer/tools/powertools.affx)
for all the genotyped family members. We discarded monomorphic SNPs, SNPs
with a call rate lower than 100% and SNPs presenting more than one
Mendelian inconsistency in the family. SNPs were further filtered with
population-based filters. We then used the high-quality SNP markers to carry
out linkage analysis, assuming autosomal recessive inheritance with complete
penetrance (homozygosity mapping). Parametric multipoint linkage analysis
was carried out with Merlin (Abecasis et al.,
2002).

Zhang S.Y., Clark N.E., Freije C.A., Pauwels E., Taggart A., Okada S., Mandel H., Garcia P., Ciancanelli M.J., Biran A., Lafaille F.G., Tsumura M., Cobat A., Luo J., Volpi S., Zimmer B., Sakata S., Dinis A., Ohara O., Garcia Reino E.J., Dobbs K., Hasek M., Holloway S.P., McCammon K., Hussong S.A., DeRosa N., Van Skike C.E., Katolik A., Lorenzo L., Hyodo M., Faria E., Halwani R., Fukuhara R., Smith G.A., Galvan V., Damha M.J., Al-Muhsen S., Itan Y., Boeke J.D., Notarangelo L.D., Studer L., Kobayashi M., Diogo L., Fairbrother W., Abel L., Rosenberg B., Hart J., Etzioni A, & Casanova J.L. (2018). Inborn errors of RNA lariat metabolism in humans with brainstem viral infection. Cell, 172(5), 952-965.e18.

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Affymetrix Genotyping Protocols Comparison

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Sample 1 was genotyped with the Affymetrix Genome-wide Human SNP array 5.0 (Affymetrix, Santa Clara, CA) following standard protocols. Genotype calling was done with the Affymetrix PowerTools (APT) software package including the full sample set, and using two genotyping algorithms, the BRLMM-P and Birdseed algorithms. In order to minimize genotyping errors, the program PLINK v 1.06 was used to merge the genotype results obtained with both algorithms, using the consensus call mode.
Sample 2 was genotyped with the Affymetrix Axiom LAT array (Affymetrix, Santa Clara, CA) following standard protocols. Genotype calling was done with the Affymetrix PowerTools (APT) software package, using the AxiomGT1/ BRLMM-P algorithm and the manufacturer recommended calling pipeline.

Parra E.J., Mazurek A., Gignoux C.R., Sockell A., Agostino M., Morris A.P., Petty L.E., Hanis C.L., Cox N.J., Valladares-Salgado A., Below J.E, & Cruz M. (2017). Admixture mapping in two Mexican samples identifies significant associations of locus ancestry with triglyceride levels in the BUD13/ZNF259/APOA5 region and fine mapping points to rs964184 as the main driver of the association signal. PLoS ONE, 12(2), e0172880.

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HNSCC Cell Transcriptomic Profiles

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UMSCC25, 584-A2, and Ca9-22 HNSCC cells were treated with dimethylsulfoxide (DMSO) as a control, 0.3μM FGFR-TKI, AZD8010, 0.1μM EGFR-TKI, gefitinib, or both AZD8010 and gefitinib for 4 days after which RNA was purified and used to probe Affymetrix Human Gene 1.0 ST arrays by the Genomics and Microarray Core, University of Colorado Cancer Center Gene Expression Core. Gene expression profiles were extracted and normalized by using Robust Multiarray Average (RMA) using Affymetrix Power Tools. Data analysis was performed on these normalized gene expression profiles.

Kleczko E.K., Kim J., Keysar S.B., Heasley L.R., Eagles J.R., Simon M., Marshall M.E., Singleton K.R., Jimeno A., Tan A.C, & Heasley L.E. (2015). An Inducible TGF-β2-TGFβR Pathway Modulates the Sensitivity of HNSCC Cells to Tyrosine Kinase Inhibitors Targeting Dominant Receptor Tyrosine Kinases. PLoS ONE, 10(5), e0123600.

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Genotyping with Affymetrix Axiom ASI 1 Array

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Using of the Affymetrix Axiom ASI 1 array (Affymetrix, CA, USA) in accordance with the manufacturer’s instructions, we genotyped a total of 600,307 SNPs for the three individuals. Genotype calls were determined using the Genotyping Console 4.1.4 software with the Birdseed v2 algorithm provided by the manufacture. In addition to data from the patient and her parents, we also used 474 Japanese individuals to ensure reliable genotype calling. Signal intensities for alleles A and B were observed by using Affymetrix Power Tools [14 ]. B allele frequency was calculated by using of the intensities of both alleles: BAF = B / (A + B).

Tamura M., Isojima T., Kawashima M., Yoshida H., Yamamoto K., Kitaoka T., Namba N., Oka A., Ozono K., Tokunaga K, & Kitanaka S. (2015). Detection of Hereditary 1,25-Hydroxyvitamin D-Resistant Rickets Caused by Uniparental Disomy of Chromosome 12 Using Genome-Wide Single Nucleotide Polymorphism Array. PLoS ONE, 10(7), e0131157.

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Gene Expression Profiling by Affymetrix Array

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For gene expression profiling, total RNA was extracted and hybridized to Affymetrix Human Transcriptome Array 2.0. Background correction and normalization were done using RMA (Robust Multichip Average) algorithm [45 (link)] using Affymetrix Power Tools. After quality assessment, a filtering process was performed to eliminate low-expression probe sets. Applying the criterion of an expression value > 16 in two samples for each experimental condition, 41,697 probe sets were selected for statistical analysis. R and Bioconductor were used for preprocessing and statistical analysis. LIMMA (Linear Models for Microarray Data) [46 (link)] was used to find out the probe sets that showed significant differential expression between experimental conditions. Genes were selected as significant using a P value > 0.01. The biological knowledge extraction was complemented through the use of Ingenuity Pathway Analysis (QIAGEN Inc., https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis).

Marín-Béjar O., Mas A.M., González J., Martinez D., Athie A., Morales X., Galduroz M., Raimondi I., Grossi E., Guo S., Rouzaut A., Ulitsky I, & Huarte M. (2017). The human lncRNA LINC-PINT inhibits tumor cell invasion through a highly conserved sequence element. Genome Biology, 18, 202.

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Neuroblastoma Affymetrix Exon Array Analysis

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Neuroblastoma Affymetrix Human Exon Array data of 219 primary tumor specimens from patients with high-risk disease were obtained through the NCI Therapeutically Applicable Research to Generate Effective Treatments (TARGET) Consortium (see https://ocg.cancer.gov/programs/target/research). Data were normalized by quantile normalization and summarized using robust multichip average (Affymetrix Power Tools software package, version 1.12). The transcript level data of core probe sets for each sample were averaged based on gene symbol annotations provided by the manufacturer (17,422 unique genes). Spearman correlation analysis between αFAP, FSP-1 and CD163 and was performed on all samples and stratified by MYCN status.

Borriello L., Nakata R., Sheard M.A., Fernandez G.E., Sposto R., Malvar J., Blavier L., Shimada H., Asgharzadeh S., Seeger R.C, & DeClerck Y.A. (2017). Cancer-Associated Fibroblasts Share Characteristics and Pro-tumorigenic Activity with Mesenchymal Stromal Cells. Cancer research, 77(18), 5142-5157.

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Genotyping of F2 Chicken Samples

Cited 1 time

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DNA was extracted from blood tissue with a standard protocol. Genotyping analyses of 1534 samples from F2 generation were performed with a Affymetrix^® Axiom^® 600 K Chicken Genotyping Array (Affymetrix, Inc., Santa Clara, CA, USA). More details on the genotyping array are described by Kranis et al.42 (link). The quality of array data was evaluated with Affymetrix Power Tools and PLINK software43 (link). SNPs were excluded if they had a minor-allele frequency <1%. SNPs that deviated from the Hardy–Weinberg equilibrium (HWE) (P value < 1e−6) were removed. SNPs on sex chromosomes were removed. Samples with call rates <95% were removed. This led to the removal of 22 samples from the data set. Phasing analyses were performed with Beagle software (version 4.0)44 (link). Finally, 435,867 autosomal SNPs and 1512 samples passed the quality control.

Guo J., Sun C., Qu L., Shen M., Dou T., Ma M., Wang K, & Yang N. (2017). Genetic architecture of bone quality variation in layer chickens revealed by a genome-wide association study. Scientific Reports, 7, 45317.

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Copy Number Variation Analysis

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Raw CEL signal intensity files (Generated using the Affymetrix Genome-Wide Human SNP 6.0 Array) were processed with Affymetrix power tools and BIRDSUITE (Version 1.5.5)^{28 ,75 (link)}. Segmented copy-number calls were log2 transformed and further processed with GISTIC 2.0^{24 (link)} using an amplification and deletion threshold of 0.1. Samples with NSD1 copy number calls meeting the GISTIC 2.0 (Version 2.0.0) threshold and designated at least −1 or +1 were considered to have NSD1 deletions and amplifications, respectively.

Brennan K., Shin J.H., Tay J.K., Prunello M., Gentles A.J., Sunwoo J.B, & Gevaert O. (2017). NSD1 inactivation defines an immune cold, DNA hypomethylated subtype in squamous cell carcinoma. Scientific Reports, 7, 17064.

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Prostate Cancer Tissue Procurement and Analysis

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After histopathologic review of formalin-fixed, paraffin-embedded (FFPE) tumor blocks from each case by 2 expert genitourinary pathologists, the tumor block with the index lesion was selected for specimen processing. The index lesion was identified as the prostatectomy FFPE block with the highest pathologic Gleason grade, regardless of its volume. Two [x] 0.6-mm diameter tissue biopsy punch tool cores were sampled to enrich for tumor cells from the highest Gleason grade in the index lesion and placed in a microfuge tube for RNA extraction. The RNA extraction and microarray expression data generation were as previously described (10 (link)). After microarray quality control using the Affymetrix Power Tools packages (Santa Clara, CA) (15 (link)), probeset summarization and normalization were performed by the SCAN algorithm (16 (link)), which normalizes each batch individually by modeling and removing probe-and array-specific background noise using only data from within each array (15 (link)).

Den R.B., Feng F.Y., Showalter T.N., Mishra M.V., Trabulsi E.J., Lallas C.D., Gomella L.G., Kelly W.K., Birbe R.C., McCue P.A., Ghadessi M., Yousefi K., Davicioni E., Knudsen K.E, & Dicker A.P. (2014). Genomic Prostate Cancer Classifier Predicts Biochemical Failure and Metastases in Patients After Postoperative Radiation Therapy. International journal of radiation oncology, biology, physics, 89(5), 1038-1046.

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Whole Transcriptome Expression Analysis

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RNA was amplified from 300 ng of total RNA, and single-strand sense cDNA was reverse transcribed, biotinylated, and hybridized to the GeneChip Human Gene 1.0 ST Arrays (Affymetrix, Santa Clara, CA, USA) after fragmentation. The arrays were washed and stained on a GeneChip Fluidics Station 450; scanning was carried out with the GeneChip Scanner 3000 and image analysis was done with the Affymetrix GeneChip Command Console (AGCC) software. Resulting CEL files were processed with Affymetrix Power Tools for probe set summarization, normalization, and log2-transformation (RMA with sketch quantile normalization). Ingenuity Pathway Analysis software (Ingenuity Systems, Redwood City, CA, USA) and Toppgene Suite were used for functional interpretation of gene expression data.

Goswami M., Prince G., Biancotto A., Moir S., Kardava L., Santich B.H., Cheung F., Kotliarov Y., Chen J., Shi R., Zhou H., Golding H., Manischewitz J., King L., Kunz L.M., Noonan K., Borrello I.M., Smith B.D, & Hourigan C.S. (2017). Impaired B cell immunity in acute myeloid leukemia patients after chemotherapy. Journal of Translational Medicine, 15, 155.

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