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The collected microarray datasets were standardized by using quantile normalization.
We then normalized between all egg-producing arrays and between all eggless arrays by using quantile normalization as recommended by Agilent, averaging signals between replicate probes.
We began by using quantile normalization (across arrays for the same epigenetic mark) and then conservatively smoothing each array dataset using a three point median smooth.
Probe-set summary and background correction of expression values were performed by using the RMA algorithm (ArrayAssist ExonRMA), and chip-to-chip variation was corrected by using quantile normalization.
Probe-set summarization and background correction of expression values was performed by using the RMA algorithm (ArrayAssist ExonRMA), and chip-to-chip variation was corrected by using quantile normalization.
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Normalization and probe averaging of raw microarray data were carried out by Roche Nimblegen using quantile normalization [ 60], and the robust multichip average algorithm [ 61].
Single-channel normalization of two-color cDNA was done as proposed by [ 30], using quantile normalization.
The raw data was preprocessed using methylumi [ 93] and normalized using quantile normalization followed by beta-mixture quantile normalization (BMIQ).
The raw microRNA array data was normalized using quantile normalization, followed by a robust multi-array average (RMA; [ 46]) with Bioconductor [ 47].
In brief, background-corrected data were normalized using quantile normalization and summarized by median polish.
Raw data was processed with the RMA algorithm (Robust Multiarray Average) developed by Irizarry et al. [ 29] and normalized using quantile normalization [ 30].
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