2 Matching Annotations
  1. Jul 2018
    1. On 2013 Oct 25, Stephen Turner commented:

      Two of the most common questions at the beginning of an RNA-seq experiments are "how many reads do I need?" and "how many replicates do I need?". This paper describes a web application for designing RNA-seq applications that calculates an appropriate sample size and read depth to satisfy user-defined criteria such as cost, maximum number of reads or replicates attainable, etc. The power and sample size estimations are based on a t-test that the authors claim performs no worse than the negative binomial models implemented by popular RNA-seq methods, such as DESeq {1}, when there are three or more replicates present. Empirical distributions are taken from either (1) pilot data that the user can upload; or (2) built-in publicly available data. The authors find that there is substantial heterogeneity between experiments (technical variation is larger than biological variation in many cases), and that power and sample size estimation will be more accurate when the user provides their own pilot data.


      This comment, imported by Hypothesis from PubMed Commons, is licensed under CC BY.

  2. Feb 2018
    1. On 2013 Oct 25, Stephen Turner commented:

      Two of the most common questions at the beginning of an RNA-seq experiments are "how many reads do I need?" and "how many replicates do I need?". This paper describes a web application for designing RNA-seq applications that calculates an appropriate sample size and read depth to satisfy user-defined criteria such as cost, maximum number of reads or replicates attainable, etc. The power and sample size estimations are based on a t-test that the authors claim performs no worse than the negative binomial models implemented by popular RNA-seq methods, such as DESeq {1}, when there are three or more replicates present. Empirical distributions are taken from either (1) pilot data that the user can upload; or (2) built-in publicly available data. The authors find that there is substantial heterogeneity between experiments (technical variation is larger than biological variation in many cases), and that power and sample size estimation will be more accurate when the user provides their own pilot data.


      This comment, imported by Hypothesis from PubMed Commons, is licensed under CC BY.