Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.
Raw data from .cel files with fluorescence signals were analyzed using Affymetrix Expression Console software to normalize them and obtain quality control data. We used Robust Multichip Analysis (RMA) to adjust signal to noise ratio and to generate .chp files for further analysis. In .chp files two types of data were obtained for each probe or miRNA in the array: 1) detection call data, categorizing each miRNA as ‘present’ or ‘absent’ and 2) log2 intensity signal data.