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Only nuclei with clearly visible signals for all four subsequently hybridized probe panels were included in the final count. The nuclei were checked after each hybridization and were excluded if damaged or incomplete. This was easily assessed by comparison with images of the previous hybridizations. The counts for each cell and each probe were then recorded in Excel spreadsheets (Microsoft EPZ5676 cost Corp, Redmond, WA; Table 2). We recorded the results of the enumeration as raw data for DCIS and IDC separately per patient and saved those as tab-delimited text files for the various analyses described later herein. Table 2 is an example of the raw data for the IDC of case 1, which shows 20 of 59 rows of the raw data file. The first 10 columns are the signal counts of two centromere probes (CEP10 and CEP4) and eight gene probes (COX2, DBC2, MYC, CCND1, CDH1, TP53, HER2, and ZNF217). The rows were sorted in lexicographic ascending order. The eight genes are in chromosome order. Each row of 10 probe signal counts is called a signal pattern. Multiple nuclei having the same signal pattern were grouped into one row. The second to last right column reports the number of distinct nuclei having the signal pattern described by that row. Nuclei with signal patterns that have MAPK a high likelihood of resulting from truncation artifacts were filtered out as described later herein. The DCIS and the IDC lesions showed varying contributions of cells with diploid counts for all markers, presumably from stromal or immune cells. Cells with a count of two signals for all probes were eliminated from the subsequent data analysis. In addition, we used two methods to filter out signal patterns that are likely contributed by sectioned nuclei. The first method is based on counting oncogene probe signals based on the intuition that oncogenes should rarely be lost and that nuclei with subdiploid signals from oncogenes are, therefore, likely to be cut. Probabilities of signal counts expressed as percentages of signal counts for all centromere and gene probes across all cells are reported in Table 3. For each signal pattern, we multiplied the probabilities of the observed signal counts for the five oncogenes check details to obtain a likelihood of the observed count under the null hypothesis of no cut nucleus. To make the test more cautious, we heuristically multiplied this likelihood by 10 for each oncogene probe with three or more counts. We identified any nucleus with adjusted likelihood