Sentence examples for use the sam algorithm from inspiring English sources

When analyzing microarray data from two sets of patient-derived samples, we first use the SAM algorithm with parameters set to determine the genes significantly overexpressed or underexpressed in the patient group of interest compared with the control group [ 9].

To establish whether promoter methylation participated in the regulation of genes differentially expressed in NTERA-2 cells and ASC we analyzed the gene expression using transcriptome data and the SAM algorithm and found that 56% of the hypomethylated genes in ASC (n = 46) were overexpressed in these cells in comparison with NTERA-2, (Table S10 and Figure 4A).

Differentially expressed genes (brain versus bone relapse and brain versus lung relapse) were identified by repeated permutation testing with the SAM algorithm by using a 5% fdr.

To further reduce the risk of false positives, we chose for additional consideration those genes with a ≥2-fold difference in average expression levels and an average gene expression level > 600 in at least one of the two subsets in both Training Set A and Training Set B. The SAM algorithm 11 was used to estimate the false discovery rate.

The SAM algorithm [ 80] with a delta of 0.35 (standard cutoff used by SAM algorithm to determine differentially expressed genes) and a very stringent cut-off with the false discovery rate of 0.0001 were used to identify differentially regulated probe sets between the immature and IVM oocytes.

To identify differentially expressed genes, the SAM algorithm, which minimizes variation across arrays and incorporates an estimate of false discovery rate (FDR) [ 46], was used.

To overcome this limitation, we developed a high performance parallelized version of the SAM algorithm called ParaSAM.

The present study uses the SAM 2005 constructed by IFPRI (Dorosh and Thurlow 2009) for Bangladesh and this is the latest SAM constructed for Bangladesh economy.

The microarray GSE4757 was analyzed using Significance Analysis of Microarrays (SAM) to identify significantly expressed AD related genes in R using the SAM 5.0 package from [ 40].

However, the problem is diminished when using the SAM analysis technique.

Sex bias analysis was performed using the SAM [ 21], and P < 0.05 represented statistical significance.