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  2. RNA-Seq - Wikipedia

    en.wikipedia.org/wiki/RNA-Seq

    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.

  3. Normalization (statistics) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(statistics)

    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.

  4. Template:Parts per million - Wikipedia

    en.wikipedia.org/wiki/Template:Parts_per_million

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  5. Template:Parts per million/doc - Wikipedia

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  6. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]

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  8. Read (biology) - Wikipedia

    en.wikipedia.org/wiki/Read_(biology)

    Sequencing technologies vary in the length of reads produced. Reads of length 20-40 base pairs (bp) are referred to as ultra-short. [2] Typical sequencers produce read lengths in the range of 100-500 bp. [3] However, Pacific Biosciences platforms produce read lengths of approximately 1500 bp. [4] Read length is a factor which can affect the results of biological studies. [5]

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