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For this control, we generated the random sequences by scrambling V1R peak alignments (with end-gaps trimmed) in order to preserve base composition.
NEUROD2 peaks were identified by MACS (Model-based analysis of ChIP-Seq) [ 19] and GFP peak alignments were used as input control dataset for signal normalization (cutoff p-value of < 10−5).
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For peak alignment, only the (recommended) option of the "fast aligner" was tested as the other alignment procedure resulted in frequent crashes of the computer.
Although we believe the strategy of correcting for peak fragment lengths before peak alignment can increase the accuracy of peak alignment and make visual evaluation of aligned peak sets easier, some researchers might not agree.
Smith, C. A., Want, E. J., O'Maille, G., Abagyan, R. & Siuzdak, G. XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification.
Dorran, D., Lawlor, R. & Coyle, E. High quality time-scale modification of speech using a peak alignment overlap-add algorithm (PAOLA).
The raw peaks extraction, data baselines filtering and calibration, peak alignment, deconvolution analysis, peak identification, and integration of the peak area were operated using the Chroma TOF4.3X software (LECO) and LECO-Fiehn Rtx5 database.
Chroma TOF4.3× software (LECO, St. Joseph, MI, USA) was used for raw data analysis, including raw peak extraction, baseline data filtering, calibration of the baseline, peak alignment, deconvolution analysis, peak identification and integration of the peak area.
The GC-FID data analyses was based on automatic peak alignment and integration, enabling extraction of the area of 140 peaks from the gas chromatograms, as opposed to the 31 fatty acids usually considered for fish oil characterisation.
A MATLAB implementation of the software package, called WaveSpect0, is presented including processing procedures of step-interval unification, adaptive stationary discrete wavelet denoising, baseline correction using splines, normalization, peak detection, and a newly designed peak alignment method using clustering techniques.
After gas chromatography mass spectrometry (GC MS) analysis, data processing, including retention time correction, spectral deconvolution, peak alignment, and normalization prior to statistical analysis, is an important step in metabolomics.
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