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In the "shift" transformation, we added varied quantities (with variations as one fifth of the added values) of read counts into the selected transcripts in either group.
Median values of read counts for edgeR-normalized mRNA and ribosome footprint read counts were used to represent each gene in each stage.
In order to see the effects of these factors, we conducted a series of experiments by changing the values of read length and fragment length mean/standard deviation during the simulation data preparation.
Scatter plots and Pearson correlations with Pearson p-values were obtained by calculating the log2 values of read densities normalized to the control at the given peaks or around ENSEMBL transcription start sites.
If five out of seven or more sequential 200 bp overlapping windows in a region had values of read depth that were significantly different from the mean depth in that chromosomes (more than mean + 2 standard deviations), the region was defined as CNV gain region.
Within each group of "comparable" SNPs, we identify SNPs with AEI signal by fitting a mixture of folded Skellam distributions to the absolute values of read differences.
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Because each student responded to only a portion of the test items, a multiple imputation technique was used to create five sets of plausible values of reading scores for the whole sample (Foy et al. [2007]).
Differential expression tools are used to quantify the expression values of reads.
*Counts are normalized values of reads uniquely mapped to the genomic loci corresponding to each wheat transporter gene.
(A ) RPKM values of reads uniquely mapped to either 5′ UTR or CDS of transcripts (same list of transcripts as in Figure 1 source data 1 ).
Genes are classified into "active" or "inactive", based on a sound statistical evaluation and not on arbitrarily chosen threshold values of reads or RPKM.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com