One color low input quick amp labeling kit
The One-color Low Input Quick Amp Labeling Kit is a laboratory product designed for the amplification and labeling of low-input RNA samples. The kit provides a streamlined workflow for preparing samples for microarray analysis.
Lab products found in correlation
54 protocols using one color low input quick amp labeling kit
MSCs-TCs Interaction Gene Expression
Marigold SFE Transcriptome Analysis
Genome-wide Microarray Analysis of Cell Differentiation
Data were analyzed using Gene-Spring GX12.0 software (Agilent) after applying two normalization procedures. First, signal intensities of less than 1 were set to 1, and then each chip was normalized to the 75th percentile of all measurements from that chip. Baseline transformation of these data was not performed. Genes with a flag value of “detected” or “not detected” in at least one sample were analyzed. Differentially expressed genes were selected if the average values of each sample were altered by at least 2.0-fold. Early differentiation marker genes for the heat map were selected as previously described [21 (link)]. GO terms enriched with a p-value cut-off of 0.01 were extracted.
Microarray Transcriptional Profiling of Mouse Colon
Gene Expression Profiling of Tumor Samples
Microarray Analysis of Tumor Tissue
Assessing Gene Expression in Radiation Exposure
Transcriptomic Analysis of Human Cells
Comprehensive lncRNA and mRNA Profiling using Microarray
Approximately 30,000 lncRNAs were collected from authoritative data sources, including NCBI_refseq, NCBI_other, Ensembl, UCSC, LNCRNA-DB, Agilent, ncRNA-SCAN, and published papers. Moreover, the correlations between approximately 31,000 mRNAs and lncRNAs were analyzed using this array. After 17 hours of hybridization, slides were washed in staining dishes using a Gene Expression Wash Buffer Kit (Agilent Technologies), and all slides were scanned on an Agilent Microarray Scanner with the following default settings: 1) channel: green, 2) scan resolution: 3 μm, 20 bit. All data were extracted using Feature Extraction Software 10.7 (Agilent Technologies), and dates were normalized using a quantile algorithm via Gene Spring Software 11.0 (Agilent Technologies).
Transcriptomic Analysis of P. tricornutum
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