In an attempt to find such genetic markers, we combine milk production recording information and historical climatic data from a wide range of environments across Australia, with genome wide dense single nucleotide polymorphism (SNP) data on dairy sires.
In cases were studies evaluated multiple markers independently we combined the data of each assay separately following the approach used in a recent meta-analysis of CTCs in breast cancer [ 34].
Due to the lack of specific markers for different CPC populations, we combined stem cell markers with markers of early and mature lineages to identify stem cells in transition to cardiomyogenic (Hand1, Tbx5, αMHC) and mesodermal/endothelial cells (Flk1, CD31).
We combined markers using approaches that did not require statistical fitting because of the low sample sizes.
In an effort to identify potential molecular markers for AIDS-KS we combined the SAGE libraries of the two AIDS-KS tissues and compared this pooled SAGE library with a SAGE library generated from pooled samples of three different normal skin biopsies.
We combined marker pairs into distance intervals, rather than considering them individually, to reduce the influence of outliers and to obtain a better visual description of the LD decay with distance.
When we combined our markers, patients showing the worst prognosis were patients with tumors bearing 2 or 3 negative prognostic markers; patients with loss of HLA class I tumor expression, weak HLA-G tumor expression and low tumor infiltration with Foxp3+ cells.
We combined several markers into haplotypes for the genes htr1B, htr2A, and slc6A4.
In this study, we combined the markers of DcR3 and sTREM-1 into a simple score, named as "bioscore", which was proved to be a useful predictor for the diagnosis of bacterial meningitis.
We combined the markers with cytology in order to improve our test results and found that especially the combination of hTERT and cytology resulted in a sensitivity of 73.3% and a specificity of 74.1% (Table 3).
