rnaf


This positional bias model was estimated in Li and Jiang (2012).
  With RNA fragmentation, reads are more likely to have come from the middle
  of the transcript than either end. The probabilities included in this
  dataset were estimated from Supplementary Figure S3 in Li and Jiang's
  manuscript. Data points from the figure were inferred and exported as CSV
  files using WebPlotDigitizer. The CSV files and the code used to process
  them and create the datasets are available in the Polyester GitHub
  repository (<a href="https://github.com/alyssafrazee/polyester">https://github.com/alyssafrazee/polyester</a>).


This package can be used to simulate RNA-seq reads from
differential expression experiments with replicates. The reads can then be
aligned and used to perform comparisons of methods for differential
expression.

Alyssa Frazee

polyester

Simulate RNA-seq reads

rnaf function

data frame with 100 rows and 2 columns. Column 1 is position along a
  transcript (in percent), while Column 2 is the probability of getting a
  fragment at that position. Column 2 sums to 1.

Format


This positional bias model was estimated in Li and Jiang (2012).
  With RNA fragmentation, reads are more likely to have come from the middle
  of the transcript than either end. The probabilities included in this
  dataset were estimated from Supplementary Figure S3 in Li and Jiang's
  manuscript. Data points from the figure were inferred and exported as CSV
  files using WebPlotDigitizer. The CSV files and the code used to process
  them and create the datasets are available in the Polyester GitHub
  repository (<a href = 'https://github.com/alyssafrazee/polyester'>https://github.com/alyssafrazee/polyester</a>).


rnaf: Model of positional bias that can arise when RNA-seq is performed using protocols relying on RNA fragmentation.

Description

Arguments

Format

References