Microarray technology in your lab Microarray technology enables the flexible throughput analysis of genotyping, chromosome copy number variations and gene expression. It can be applied to various applications such as predictive genomics, reproductive health and oncology research. Stay up to date with the...
High-resolution, whole-genome microarray analysis is becoming the standard for hematological cancer sample profiling and and may one day replace traditional cytogenetic techniques. Read white paper For Research Use Only. Not for use in diagnostic procedures. ...
Bioinformatics analysis plays an important part of processing the information embedded in large-scale expression profiling studies and for laying the foundation for biological interpretation. Over the past years, numerous tools have emerged for microarray data analysis. One of the most popular platforms ...
GeneDx benefits from Hybrid-SNP arrays Dr. Jeanne Mack and Stephanie Warren from GeneDx discuss saving time and money with a more efficient microarray platform. Learn more For Research Use Only. Not for use in diagnostic procedures. Gene Expression (Transcriptome Profiling) ...
7)样本间关系(An exploratory analysis of data with PCA) 1 2 3 4 5 6 myData <-ReadAffy(celfile.path="F:/R/bioinformation with R cookbook")#读取所有CEL文件,返回的是AffyBatch object myData.pca <-exprs(myData) myPca <-prcomp(myData.pca, scale=TRUE)#prcomp函数计算主成分 ...
In this study, the expression profiles and potential functions of lncRNAs and mRNAs were investigated by microarray and bioinformatics analysis in PTC tissues and paired adjacent noncancerous thyroid tissues. We found that 338 lncRNAs and 304 mRNAs with various functions were differentially expressed in...
Microarrays permit the analysis of gene expression, DNA sequence variation, protein levels, tissues, cells and other biological and chemical molecules in a massively parallel format. Robust microarray manufacture, hybridization, detection and data analysis technologies permit novice users to adapt this exci...
The dataset was downloaded by the publically available server GEO database, the raw data file was normalized, clustered using the R scripts, the output of the files that is the normalized files were loaded in MeV for the analysis of Gene expression. The normalized file has a set of 22,284...
Despite differences in sample selection as well as in the number of microRNAs analyzed, there is good agreement between the overlapping aspects of the two datasets. Our strategy has the potential to be highly scalable, allowing high-throughput analysis of samples with limiting starting material. ...
Downstream analysis of pathways regulating gene expression We ran PLIER24 to identify pathways significantly associated with at least one latent variable in gene expression data derived from a single platform (microarray only or RNA-seq only) or mixed-platform (combination of microarray and RNA-seq)...