Agilent Technologies

About: Agilent Technologies is a company organization based out in Santa Clara, California, United States. It is known for research contribution in the topics: Signal & Mass spectrometry. The organization has 7398 authors who have published 11518 publications receiving 262410 citations. The organization is also known as: Agilent Technologies, Inc..

The fundamental aspects and applications of Agilent HPLC‐Chip

Abstract: It has been over 3 years since the first publication of the polymer microfluidic HPLC-Chip technology and more than 1 year since this technology became commercially available. Here, we summarize the design principle and fabrication processes of the Agilent HPLC-Chip and review the applications published so far.

Systematic evaluation of variability in ChIP-chip experiments using predefined DNA targets

Abstract: The most widely used method for detecting genome-wide protein–DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and “spike-ins” comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols, and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated.

Optimization of the high-frequency contactless conductivity detector for capillary electrophoresis

Abstract: Two constructions of the high-frequency contactless conductivity detector that are fitted to the specific demands of capillary zone electrophoresis are described. The axial arrangement of the electrodes of the conductivity cell with two cylindrical electrodes placed around the outer wall of the capillary column is used. We propose an equivalent electrical model of the axial contactless conductivity cell, which explains the features of its behavior including overshooting phenomena. We give the computer numerical solution of the model enabling simulation of real experimental runs. The role of many parameters can be evaluated in this way, such as the dimension of the separation channel, dimension of the electrodes, length of the gap between electrodes, influence of the shielding, etc. The conception of model allows its use for the optimization of the construction of the conductivity cell, either in the cylindrical format or in the microchip format. The ability of the high-frequency contactless conductivity detector is demonstrated on separation of inorganic ions.

Utilizing Ethnic-Specific Differences in Minor Allele Frequency to Recategorize Reported Pathogenic Deafness Variants

Abstract: Ethnic-specific differences in minor allele frequency impact variant categorization for genetic screening of nonsyndromic hearing loss (NSHL) and other genetic disorders. We sought to evaluate all previously reported pathogenic NSHL variants in the context of a large number of controls from ethnically distinct populations sequenced with orthogonal massively parallel sequencing methods. We used HGMD, ClinVar, and dbSNP to generate a comprehensive list of reported pathogenic NSHL variants and re-evaluated these variants in the context of 8,595 individuals from 12 populations and 6 ethnically distinct major human evolutionary phylogenetic groups from three sources (Exome Variant Server, 1000 Genomes project, and a control set of individuals created for this study, the OtoDB). Of the 2,197 reported pathogenic deafness variants, 325 (14.8%) were present in at least one of the 8,595 controls, indicating a minor allele frequency (MAF) >0.00006. MAFs ranged as high as 0.72, a level incompatible with pathogenicity for a fully penetrant disease like NSHL. Based on these data, we established MAF thresholds of 0.005 for autosomal-recessive variants (excluding specific variants in GJB2) and 0.0005 for autosomal-dominant variants. Using these thresholds, we recategorized 93 (4.2%) of reported pathogenic variants as benign. Our data show that evaluation of reported pathogenic deafness variants using variant MAFs from multiple distinct ethnicities and sequenced by orthogonal methods provides a powerful filter for determining pathogenicity. The proposed MAF thresholds will facilitate clinical interpretation of variants identified in genetic testing for NSHL. All data are publicly available to facilitate interpretation of genetic variants causing deafness.