MolecBio.jl documentation

A simple constrained-scope Julia utility to automate relative quantification of mRNA from thermocycler cycle threshold (ct) data. Takes as input raw ct values for target and reference genes from experiment and control conditions and returns as output the fold changes in gene expression using the Δ Δ ct method. Useful automation for repeatitive QPCR analyses for life science grad students and postdocs.

Installation:

$ julia -e  'using Pkg; pkg"add https://github.com/pkmklong/MolecBio";'

Entry point:

$ julia runner.jl --h
usage: runner.jl -f FILE_PATH -c CONTROL -t TARGET -n NORMALIZER [-h]

optional arguments:
  -f, --file_path FILE_PATH
                        The path to raw ct data (csv) for relative RNA
                        quantification
  -c, --control CONTROL
                        The name of your control group (default:
                        "control")
  -t, --target TARGET   The name of your target transcript
  -n, --normalizer NORMALIZER
                        The name of your normalizing reference
                        transcript
  -h, --help            show this help message and exit

Input data dictionary:

{column:                            type      description}
"group":                            String    Names of comparison groups
user defined target column:         Float64   ct values of target transcript
user defined normalizing column:    Float64   ct values of normalizing reference transcript

Fold change:

delta delta CT

Demo:

$ julia src/runner.jl -f "data/demo_data.csv" -c "control" -t "egf1r" -n "rpl19"
Parsed args:
  normalizer  =>  rpl19
  target  =>  egf1r
  control  =>  control
  file_path  =>  data/demo_data.csv
┌ Info: Loading CT values table
└   args["file_path"] = "data/demo_data.csv"
┌ Info: Computing fold change with delta delta ct
│   first(ddct_table, 5) =
│    5×6 DataFrame
│    │ Row │ group   │ egf1r   │ rpl19   │ delta_ct │ delta_delta_ct │ fold_change │
│    │     │ String  │ Float64 │ Float64 │ Float64  │ Float64        │ Float64     │
│    ├─────┼─────────┼─────────┼─────────┼──────────┼────────────────┼─────────────┤
│    │ 1   │ control │ 25.6    │ 17.5    │ -8.1     │ 0.4665         │ 1.38175     │
│    │ 2   │ control │ 25.8    │ 16.9    │ -8.9     │ -0.3335        │ 0.793609    │
│    │ 3   │ control │ 26.0    │ 17.4    │ -8.6     │ -0.0335        │ 0.977047    │
│    │ 4   │ control │ 25.4    │ 17.7    │ -7.7     │ 0.8665         │ 1.82323     │
└    │ 5   │ control │ 25.45   │ 17.2    │ -8.25    │ 0.3165         │ 1.24531     │
┌ Info: Saving output table to
└   ddct_table_path = "data/demo_data_processed.csv"
┌ Info: Saving output figure to
└   ddct_figure_path = "data/demo_data_processed.svg"
Demo visualization

Note

Currently assumes perfect amplification efficiency and unpaired samples.

License

MIT License

Copyright (c) 2020 Patrick Long

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Indices and tables