luciferase 2.0.2

Helper functions for luciferase data

luciferase

Tool for plotting luciferase reporter data. Thanks due to Joshua Chiou and Mei-lin Okino for inspiration and contributions.

Installation

pip3 install luciferase

or

pip3 install --user luciferase

Command-line interface for barplots

Barplots of enhancer activity

A script called luciferase-barplot for creating bar plots from JSON-formatted data is included. After installing luciferase, you can use it like this:

luciferase-barplot --title "plot title" example.json example.pdf 

See also the help message:

luciferase-barplot -h

Examples of luciferase reporter data in JSON format:

{
  "Non-risk, Fwd": [8.354, 12.725, 8.506],
  "Risk, Fwd": [5.078, 5.038, 5.661],
  "Non-risk, Rev": [9.564, 9.692, 12.622],
  "Risk, Rev": [10.777, 11.389, 10.598],
  "Empty": [1.042, 0.92, 1.042]
}

{
  "Alt, MIN6": [5.47, 7.17, 6.15],
  "Ref, MIN6": [3.16, 3.04, 4.34],
  "Empty, MIN6": [1.07, 0.83, 0.76],
  "Alt, ALPHA-TC6": [2.50, 3.47, 3.33],
  "Ref, ALPHA-TC6": [2.01, 1.96, 2.31],
  "Empty, ALPHA-TC6": [1.042, 0.92, 1.042]
}

The input JSON should contain either five, six, or twelve entries. If it contains five entries, the bars of the resulting plot will have a 2-2-1 style. If it contains six entries, the bars will have a 2-1-2-1 style. If twelve, the syle will be as with six entries but doubled.

Significance indicators will be written above the bars: *** if p<0.001, ** if p<0.01, * if p<0.05, ns otherwise.

Here is an example of a plot in the 2-1-2-1 style:

Barplots of allelic ratio

A second script called luciferase-ratioplot takes the same input data and produces a comparative plot of allelic ratios:

luciferase-ratioplot --title "plot title" example.json example.pdf

For this script, the number of entries in the input JSON should be a multiple of 3. The resulting plot shows the estimated allelic ratio of enhancer activity with confidence intervals (95% by default). Here is an example input dataset and plot:

{
  "Alt, dex": [44.6, 37.6, 37.7],
  "Ref, dex": [149.4, 99.7, 124.5],
  "Empty, dex": [1.1, 1.0, 0.9],
  "Alt, untreated": [19.7, 16.2, 18.3],
  "Ref, untreated": [33.2, 30.3, 33.3],
  "Empty, untreated": [1.0, 1.0, 1.0]
}

Meta-analysis

It may be that we have performed two or more experiments (from separate minipreps) and wish to meta-analyze the results. As an example, let's consider the results of two identical experiments on a regulatory variant at the SIX3 locus: SIX3-MP0 and SIX3-MP1. First we'll plot both datasets separately:

luciferase-barplot six3-mp0.json six3-mp0.png --light-colors '#DECBE4' '#FED9A6' '#FBB4AE' --dark-colors '#984EA3' '#FF7F00' '#E41A1C' --title 'SIX3-MP0'
luciferase-barplot six3-mp1.json six3-mp1.png --light-colors '#DECBE4' '#FED9A6' '#FBB4AE' --dark-colors '#984EA3' '#FF7F00' '#E41A1C' --title 'SIX3-MP1'

We can see that the results are fairly consistent in character, but checking the y-axis tells us that they are on different scales. Intuitively, we might conclude from these results that there are allelic effects under all three conditions. Ideally though, we would like to use all of the data at once for one plot to get the most accurate conclusions about allelic effects.

We might simply combine the data into one dataset, (as here) and plot it:

luciferase-barplot six3-meta-nobatch.json six3-meta-nobatch.png --light-colors '#DECBE4' '#FED9A6' '#FBB4AE' --dark-colors '#984EA3' '#FF7F00' '#E41A1C'

The bar heights look reasonable, and the allelic effects appear clear from looking at them, but all of the hypothesis tests returned non-significant results. What gives?

The answer is that combining data from experiments with different scales breaks the assumptions of the significance test (a t-test). To meta-analyze these data in a useful way, we first need to re-normalize the two experiments to put both of them on the same scale. luciferase-barplot will re-normalize the data automatically if the dataset includes an additional entry ("Batch") indicating the batch of each data point, as in this example: SIX3-META.

{
  "Alt, untreated": [19.7, 16.2, 18.3, 6.5, 8.0, 4.4],
  "Ref, untreated": [33.2, 30.3, 33.3, 8.4, 13.6, 17.1],
  "Empty, untreated": [1.0, 1.0, 1.0, 1.1, 1.0, 0.9],
  "Alt, hi_cyt_noTNFA": [11.0, 8.8, 10.1, 3.2, 3.7, 3.3],
  "Ref, hi_cyt_noTNFA": [17.1, 16.7, 18.8, 7.6, 6.7, 5.5],
  "Empty, hi_cyt_noTNFA": [1.1, 0.9, 1.0, 1.1, 0.9, 1.0],
  "Alt, hi_cyt": [10.8, 10.9, 9.1, 3.1, 2.7, 4.0],
  "Ref, hi_cyt": [17.8, 16.1, 18.0, 7.7, 7.0, 7.1],
  "Empty, hi_cyt": [1.0, 1.0, 1.0, 1.0, 1.0, 1.1],
  "Batch": [0, 0, 0, 1, 1, 1]
}

Here is what the results look like when they're re-normalized to correct for batch

luciferase-barplot six3-meta.json six3-meta.png --light-colors '#DECBE4' '#FED9A6' '#FBB4AE' --dark-colors '#984EA3' '#FF7F00' '#E41A1C' --title 'SIX3-META'