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Therefore, the total number of reads generated in a single experiment is typically normalized by converting counts to fragments, reads, or counts per million mapped reads (FPM, RPM, or CPM). The difference between RPM and FPM was historically derived during the evolution from single-end sequencing of fragments to paired-end sequencing.
NEUMA is a tool to estimate RNA abundances using length normalization, based on uniquely aligned reads and mRNA isoform models. NEUMA uses known transcriptome data available in databases like RefSeq. NOISeq NOISeq is a non-parametric approach for the identification of differentially expressed genes from count data or previously normalized count ...
In the simplest cases, normalization of ratings means adjusting values measured on different scales to a notionally common scale, often prior to averaging. In more complicated cases, normalization may refer to more sophisticated adjustments where the intention is to bring the entire probability distributions of adjusted values into alignment.
Disintegrations per minute (dpm) and disintegrations per second (dps) are measures of the activity of the source of radioactivity. The SI unit of radioactivity, the becquerel (Bq), is equivalent to one disintegration per second. This unit should not be confused with cps, which is the number of counts received by an instrument from the source.
Example of a naive Bayes classifier depicted as a Bayesian Network. In statistics, naive Bayes classifiers are a family of linear "probabilistic classifiers" which assumes that the features are conditionally independent, given the target class. The strength (naivety) of this assumption is what gives the classifier its name.
Related: 300 Trivia Questions and Answers to Jumpstart Your Fun Game Night. Ready for the answers? Scroll below this image (the image that represents your very appreciated patience!).
which shows which documents contain which terms and how many times they appear. Note that, unlike representing a document as just a token-count list, the document-term matrix includes all terms in the corpus (i.e. the corpus vocabulary), which is why there are zero-counts for terms in the corpus which do not also occur in a specific document.
In statistics, quantile normalization is a technique for making two distributions identical in statistical properties. To quantile-normalize a test distribution to a reference distribution of the same length, sort the test distribution and sort the reference distribution.