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@@ -0,0 +1 @@ +/luciferase-2.4.5.tar.gz diff --git a/python-luciferase.spec b/python-luciferase.spec new file mode 100644 index 0000000..57c9b6a --- /dev/null +++ b/python-luciferase.spec @@ -0,0 +1,705 @@ +%global _empty_manifest_terminate_build 0 +Name: python-luciferase +Version: 2.4.5 +Release: 1 +Summary: Helper functions for luciferase data +License: MIT License +URL: https://gitlab.com/aaylward/luciferase +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/54/6d/d2564e403a1eedfa546319bc74c558fde7860b39f016617cb1fc83fb6516/luciferase-2.4.5.tar.gz +BuildArch: noarch + +Requires: python3-estimateratio +Requires: python3-matplotlib +Requires: python3-pandas +Requires: python3-scipy +Requires: python3-seaborn +Requires: python3-xlrd + +%description +# luciferase +Tool for plotting luciferase reporter data. Thanks due to Joshua Chiou and Mei-lin Okino for inspiration and contributions. + +## Installation + +To use `luciferase`, you must first have [python](https://www.python.org/downloads/) installed. Then, you can install `luciferase` using `pip`: + +```sh +pip install luciferase +``` +or +```sh +pip install --user luciferase +``` + +## Command-line interface for barplots + +## Introduction + +This introduction demonstrates a simple analysis of data in Excel format. + +Here is our [example dataset](https://github.com/anthony-aylward/luciferase/raw/master/example/example-excel.xlsx), `example-excel.xlsx`: + + + +The first row contains headers and subsequent rows contain firefly/renilla ratios normalized to the empty vector. + +We can analyze these data by running: + +```luciferase-swarmplot example-excel.xlsx example-excel-plot.pdf``` + +Here is the result: + +<img src="https://github.com/anthony-aylward/luciferase/raw/master/example/example-excel-plot.png" width="400"/> + +We can also use input data with more columns to produce plots with more bars. For example: + + + +```luciferase-swarmplot example-excel-expanded.xlsx example-excel-expanded-plot.pdf``` + +<img src="https://github.com/anthony-aylward/luciferase/raw/master/example/example-excel-expanded-plot.png" width="400"/> + +See the following sections for more details. + +### Barplots of enhancer activity + +A command-line tool called `luciferase-barplot` for creating bar plots is +included. After installing `luciferase`, you can use it like this: +```sh +luciferase-barplot example.json example.pdf +luciferase-barplot example.csv example.png +luciferase-barplot example.tsv example.svg +luciferase-barplot example.xls example.pdf +luciferase-barplot example.xlsx example.png +``` + +JSON, CSV, TSV, or Excel files may be used as inputs, and output +can be written in PDF, PNG, or SVG. + +See also the help message: +```sh +luciferase-barplot -h +``` + +Examples of luciferase reporter data in JSON format: +```json +{ + "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] +} +``` +```json +{ + "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] +} +``` +Examples of luciferase reporter data in TSV format: +``` +Non-risk, Fwd Risk, Fwd Non-risk, Rev Risk, Rev Empty +8.354 5.078 9.564 10.777 1.042 +12.725 5.038 9.692 11.389 0.92 +8.506 5.661 12.622 10.598 1.042 +``` +``` +Ref, untreated Alt, untreated Empty, untreated Ref, dex Alt, dex Empty, dex +33.2 19.7 1.0 149.4 44.6 1.1 +30.3 16.2 1.0 99.7 37.6 1.0 +33.3 18.3 1.0 124.5 37.7 0.9 +``` + +Significance indicators will be written above the bars: `***` if p<0.001, +`**` if p<0.01, `*` if p<0.05, `ns` otherwise. + +Here are the resulting plots: + +<img src="https://github.com/anthony-aylward/luciferase/raw/master/example/example-5.png" width="400"/><img src="https://github.com/anthony-aylward/luciferase/raw/master/example/example-6.png" width="400"/> + +### Barplots of allelic ratio + +A second tool called `luciferase-ratioplot` takes the same input data and +produces a comparative plot of allelic ratios: + +```sh +luciferase-ratioplot --xlab control dexamethasone --ylab "Ref:Alt ratio" --title Default ratio.json ratio.png +luciferase-ratioplot --xlab control dexamethasone --ylab "Alt:Ref ratio" --title Inverted --invert ratio.json ratio.png +``` + +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: + +JSON: +```json +{ + "Ref, untreated": [33.2, 30.3, 33.3], + "Alt, untreated": [19.7, 16.2, 18.3], + "Empty, untreated": [1.0, 1.0, 1.0], + "Ref, dex": [149.4, 99.7, 124.5], + "Alt, dex": [44.6, 37.6, 37.7], + "Empty, dex": [1.1, 1.0, 0.9] +} +``` +TSV: +``` +Alt, dex Ref, dex Empty, dex Alt, untreated Ref, untreated Empty, untreated +44.6 149.4 1.1 19.7 33.2 1.0 +37.6 99.7 1.0 16.2 30.3 1.0 +37.7 124.5 0.9 18.3 33.3 1.0 +``` + +<img src="https://github.com/anthony-aylward/luciferase/raw/master/example/ratio.png" width="200"/><img src="https://github.com/anthony-aylward/luciferase/raw/master/example/ratio-invert.png" width="200"/> + +## Meta-analysis + +For this section, we'll use another included command called +`luciferase-swarmplot`. It functions exactly like `luciferase-barplot` except +that individual data points will be plotted over the bars. + +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](https://github.com/anthony-aylward/luciferase/raw/master/example/six3-mp0.json) and [SIX3-MP1](https://github.com/anthony-aylward/luciferase/raw/master/example/six3-mp1.json). First we'll plot both datasets separately: +```sh +luciferase-swarmplot six3-mp0.json six3-mp0.png --light-colors '#DECBE4' '#FED9A6' '#FBB4AE' --dark-colors '#984EA3' '#FF7F00' '#E41A1C' --title 'SIX3-MP0' +luciferase-swarmplot six3-mp1.json six3-mp1.png --light-colors '#DECBE4' '#FED9A6' '#FBB4AE' --dark-colors '#984EA3' '#FF7F00' '#E41A1C' --title 'SIX3-MP1' +``` + +<img src="https://github.com/anthony-aylward/luciferase/raw/master/example/six3-mp0.png" width="400"/><img src="https://github.com/anthony-aylward/luciferase/raw/master/example/six3-mp1.png" width="400"/> + +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](https://github.com/anthony-aylward/luciferase/raw/master/example/six3-meta-nobatch.json)) and plot it: +```sh +luciferase-swarmplot 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` and +`luciferase-swarmplot` 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](https://github.com/anthony-aylward/luciferase/raw/master/example/six3-meta.json). +```json +{ + "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 +```sh +luciferase-swarmplot six3-meta.json six3-meta.png --light-colors '#DECBE4' '#FED9A6' '#FBB4AE' --dark-colors '#984EA3' '#FF7F00' '#E41A1C' --title 'SIX3-META' +``` + + + +See a more detailed explanation of the normalization procedure [here](https://github.com/anthony-aylward/luciferase/blob/master/example/meta-analysis.pdf) + + + + +%package -n python3-luciferase +Summary: Helper functions for luciferase data +Provides: python-luciferase +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-luciferase +# luciferase +Tool for plotting luciferase reporter data. Thanks due to Joshua Chiou and Mei-lin Okino for inspiration and contributions. + +## Installation + +To use `luciferase`, you must first have [python](https://www.python.org/downloads/) installed. Then, you can install `luciferase` using `pip`: + +```sh +pip install luciferase +``` +or +```sh +pip install --user luciferase +``` + +## Command-line interface for barplots + +## Introduction + +This introduction demonstrates a simple analysis of data in Excel format. + +Here is our [example dataset](https://github.com/anthony-aylward/luciferase/raw/master/example/example-excel.xlsx), `example-excel.xlsx`: + + + +The first row contains headers and subsequent rows contain firefly/renilla ratios normalized to the empty vector. + +We can analyze these data by running: + +```luciferase-swarmplot example-excel.xlsx example-excel-plot.pdf``` + +Here is the result: + +<img src="https://github.com/anthony-aylward/luciferase/raw/master/example/example-excel-plot.png" width="400"/> + +We can also use input data with more columns to produce plots with more bars. For example: + + + +```luciferase-swarmplot example-excel-expanded.xlsx example-excel-expanded-plot.pdf``` + +<img src="https://github.com/anthony-aylward/luciferase/raw/master/example/example-excel-expanded-plot.png" width="400"/> + +See the following sections for more details. + +### Barplots of enhancer activity + +A command-line tool called `luciferase-barplot` for creating bar plots is +included. After installing `luciferase`, you can use it like this: +```sh +luciferase-barplot example.json example.pdf +luciferase-barplot example.csv example.png +luciferase-barplot example.tsv example.svg +luciferase-barplot example.xls example.pdf +luciferase-barplot example.xlsx example.png +``` + +JSON, CSV, TSV, or Excel files may be used as inputs, and output +can be written in PDF, PNG, or SVG. + +See also the help message: +```sh +luciferase-barplot -h +``` + +Examples of luciferase reporter data in JSON format: +```json +{ + "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] +} +``` +```json +{ + "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] +} +``` +Examples of luciferase reporter data in TSV format: +``` +Non-risk, Fwd Risk, Fwd Non-risk, Rev Risk, Rev Empty +8.354 5.078 9.564 10.777 1.042 +12.725 5.038 9.692 11.389 0.92 +8.506 5.661 12.622 10.598 1.042 +``` +``` +Ref, untreated Alt, untreated Empty, untreated Ref, dex Alt, dex Empty, dex +33.2 19.7 1.0 149.4 44.6 1.1 +30.3 16.2 1.0 99.7 37.6 1.0 +33.3 18.3 1.0 124.5 37.7 0.9 +``` + +Significance indicators will be written above the bars: `***` if p<0.001, +`**` if p<0.01, `*` if p<0.05, `ns` otherwise. + +Here are the resulting plots: + +<img src="https://github.com/anthony-aylward/luciferase/raw/master/example/example-5.png" width="400"/><img src="https://github.com/anthony-aylward/luciferase/raw/master/example/example-6.png" width="400"/> + +### Barplots of allelic ratio + +A second tool called `luciferase-ratioplot` takes the same input data and +produces a comparative plot of allelic ratios: + +```sh +luciferase-ratioplot --xlab control dexamethasone --ylab "Ref:Alt ratio" --title Default ratio.json ratio.png +luciferase-ratioplot --xlab control dexamethasone --ylab "Alt:Ref ratio" --title Inverted --invert ratio.json ratio.png +``` + +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: + +JSON: +```json +{ + "Ref, untreated": [33.2, 30.3, 33.3], + "Alt, untreated": [19.7, 16.2, 18.3], + "Empty, untreated": [1.0, 1.0, 1.0], + "Ref, dex": [149.4, 99.7, 124.5], + "Alt, dex": [44.6, 37.6, 37.7], + "Empty, dex": [1.1, 1.0, 0.9] +} +``` +TSV: +``` +Alt, dex Ref, dex Empty, dex Alt, untreated Ref, untreated Empty, untreated +44.6 149.4 1.1 19.7 33.2 1.0 +37.6 99.7 1.0 16.2 30.3 1.0 +37.7 124.5 0.9 18.3 33.3 1.0 +``` + +<img src="https://github.com/anthony-aylward/luciferase/raw/master/example/ratio.png" width="200"/><img src="https://github.com/anthony-aylward/luciferase/raw/master/example/ratio-invert.png" width="200"/> + +## Meta-analysis + +For this section, we'll use another included command called +`luciferase-swarmplot`. It functions exactly like `luciferase-barplot` except +that individual data points will be plotted over the bars. + +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](https://github.com/anthony-aylward/luciferase/raw/master/example/six3-mp0.json) and [SIX3-MP1](https://github.com/anthony-aylward/luciferase/raw/master/example/six3-mp1.json). First we'll plot both datasets separately: +```sh +luciferase-swarmplot six3-mp0.json six3-mp0.png --light-colors '#DECBE4' '#FED9A6' '#FBB4AE' --dark-colors '#984EA3' '#FF7F00' '#E41A1C' --title 'SIX3-MP0' +luciferase-swarmplot six3-mp1.json six3-mp1.png --light-colors '#DECBE4' '#FED9A6' '#FBB4AE' --dark-colors '#984EA3' '#FF7F00' '#E41A1C' --title 'SIX3-MP1' +``` + +<img src="https://github.com/anthony-aylward/luciferase/raw/master/example/six3-mp0.png" width="400"/><img src="https://github.com/anthony-aylward/luciferase/raw/master/example/six3-mp1.png" width="400"/> + +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](https://github.com/anthony-aylward/luciferase/raw/master/example/six3-meta-nobatch.json)) and plot it: +```sh +luciferase-swarmplot 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` and +`luciferase-swarmplot` 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](https://github.com/anthony-aylward/luciferase/raw/master/example/six3-meta.json). +```json +{ + "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 +```sh +luciferase-swarmplot six3-meta.json six3-meta.png --light-colors '#DECBE4' '#FED9A6' '#FBB4AE' --dark-colors '#984EA3' '#FF7F00' '#E41A1C' --title 'SIX3-META' +``` + + + +See a more detailed explanation of the normalization procedure [here](https://github.com/anthony-aylward/luciferase/blob/master/example/meta-analysis.pdf) + + + + +%package help +Summary: Development documents and examples for luciferase +Provides: python3-luciferase-doc +%description help +# luciferase +Tool for plotting luciferase reporter data. Thanks due to Joshua Chiou and Mei-lin Okino for inspiration and contributions. + +## Installation + +To use `luciferase`, you must first have [python](https://www.python.org/downloads/) installed. Then, you can install `luciferase` using `pip`: + +```sh +pip install luciferase +``` +or +```sh +pip install --user luciferase +``` + +## Command-line interface for barplots + +## Introduction + +This introduction demonstrates a simple analysis of data in Excel format. + +Here is our [example dataset](https://github.com/anthony-aylward/luciferase/raw/master/example/example-excel.xlsx), `example-excel.xlsx`: + + + +The first row contains headers and subsequent rows contain firefly/renilla ratios normalized to the empty vector. + +We can analyze these data by running: + +```luciferase-swarmplot example-excel.xlsx example-excel-plot.pdf``` + +Here is the result: + +<img src="https://github.com/anthony-aylward/luciferase/raw/master/example/example-excel-plot.png" width="400"/> + +We can also use input data with more columns to produce plots with more bars. For example: + + + +```luciferase-swarmplot example-excel-expanded.xlsx example-excel-expanded-plot.pdf``` + +<img src="https://github.com/anthony-aylward/luciferase/raw/master/example/example-excel-expanded-plot.png" width="400"/> + +See the following sections for more details. + +### Barplots of enhancer activity + +A command-line tool called `luciferase-barplot` for creating bar plots is +included. After installing `luciferase`, you can use it like this: +```sh +luciferase-barplot example.json example.pdf +luciferase-barplot example.csv example.png +luciferase-barplot example.tsv example.svg +luciferase-barplot example.xls example.pdf +luciferase-barplot example.xlsx example.png +``` + +JSON, CSV, TSV, or Excel files may be used as inputs, and output +can be written in PDF, PNG, or SVG. + +See also the help message: +```sh +luciferase-barplot -h +``` + +Examples of luciferase reporter data in JSON format: +```json +{ + "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] +} +``` +```json +{ + "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] +} +``` +Examples of luciferase reporter data in TSV format: +``` +Non-risk, Fwd Risk, Fwd Non-risk, Rev Risk, Rev Empty +8.354 5.078 9.564 10.777 1.042 +12.725 5.038 9.692 11.389 0.92 +8.506 5.661 12.622 10.598 1.042 +``` +``` +Ref, untreated Alt, untreated Empty, untreated Ref, dex Alt, dex Empty, dex +33.2 19.7 1.0 149.4 44.6 1.1 +30.3 16.2 1.0 99.7 37.6 1.0 +33.3 18.3 1.0 124.5 37.7 0.9 +``` + +Significance indicators will be written above the bars: `***` if p<0.001, +`**` if p<0.01, `*` if p<0.05, `ns` otherwise. + +Here are the resulting plots: + +<img src="https://github.com/anthony-aylward/luciferase/raw/master/example/example-5.png" width="400"/><img src="https://github.com/anthony-aylward/luciferase/raw/master/example/example-6.png" width="400"/> + +### Barplots of allelic ratio + +A second tool called `luciferase-ratioplot` takes the same input data and +produces a comparative plot of allelic ratios: + +```sh +luciferase-ratioplot --xlab control dexamethasone --ylab "Ref:Alt ratio" --title Default ratio.json ratio.png +luciferase-ratioplot --xlab control dexamethasone --ylab "Alt:Ref ratio" --title Inverted --invert ratio.json ratio.png +``` + +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: + +JSON: +```json +{ + "Ref, untreated": [33.2, 30.3, 33.3], + "Alt, untreated": [19.7, 16.2, 18.3], + "Empty, untreated": [1.0, 1.0, 1.0], + "Ref, dex": [149.4, 99.7, 124.5], + "Alt, dex": [44.6, 37.6, 37.7], + "Empty, dex": [1.1, 1.0, 0.9] +} +``` +TSV: +``` +Alt, dex Ref, dex Empty, dex Alt, untreated Ref, untreated Empty, untreated +44.6 149.4 1.1 19.7 33.2 1.0 +37.6 99.7 1.0 16.2 30.3 1.0 +37.7 124.5 0.9 18.3 33.3 1.0 +``` + +<img src="https://github.com/anthony-aylward/luciferase/raw/master/example/ratio.png" width="200"/><img src="https://github.com/anthony-aylward/luciferase/raw/master/example/ratio-invert.png" width="200"/> + +## Meta-analysis + +For this section, we'll use another included command called +`luciferase-swarmplot`. It functions exactly like `luciferase-barplot` except +that individual data points will be plotted over the bars. + +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](https://github.com/anthony-aylward/luciferase/raw/master/example/six3-mp0.json) and [SIX3-MP1](https://github.com/anthony-aylward/luciferase/raw/master/example/six3-mp1.json). First we'll plot both datasets separately: +```sh +luciferase-swarmplot six3-mp0.json six3-mp0.png --light-colors '#DECBE4' '#FED9A6' '#FBB4AE' --dark-colors '#984EA3' '#FF7F00' '#E41A1C' --title 'SIX3-MP0' +luciferase-swarmplot six3-mp1.json six3-mp1.png --light-colors '#DECBE4' '#FED9A6' '#FBB4AE' --dark-colors '#984EA3' '#FF7F00' '#E41A1C' --title 'SIX3-MP1' +``` + +<img src="https://github.com/anthony-aylward/luciferase/raw/master/example/six3-mp0.png" width="400"/><img src="https://github.com/anthony-aylward/luciferase/raw/master/example/six3-mp1.png" width="400"/> + +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](https://github.com/anthony-aylward/luciferase/raw/master/example/six3-meta-nobatch.json)) and plot it: +```sh +luciferase-swarmplot 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` and +`luciferase-swarmplot` 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](https://github.com/anthony-aylward/luciferase/raw/master/example/six3-meta.json). +```json +{ + "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 +```sh +luciferase-swarmplot six3-meta.json six3-meta.png --light-colors '#DECBE4' '#FED9A6' '#FBB4AE' --dark-colors '#984EA3' '#FF7F00' '#E41A1C' --title 'SIX3-META' +``` + + + +See a more detailed explanation of the normalization procedure [here](https://github.com/anthony-aylward/luciferase/blob/master/example/meta-analysis.pdf) + + + + +%prep +%autosetup -n luciferase-2.4.5 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-luciferase -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed May 17 2023 Python_Bot <Python_Bot@openeuler.org> - 2.4.5-1 +- Package Spec generated @@ -0,0 +1 @@ +3ddd1bc93c0473daf5bef18ca3c726b5 luciferase-2.4.5.tar.gz |