Learn append sample modifier in peppy

This vignette will show you how and why to use the append functionality of the pepr package.


The example below demonstrates how to use the constant attributes to define the samples attributes in the read_type column of the sample_table.csv file. This functionality is extremely useful when there are many samples that are characterized by identical values of certain attribute (here: value SINGLE in read_type attribute). Please consider the example below for reference:

examples_dir = "../tests/data/example_peps-cfg2/example_append/"
sample_table_ori = examples_dir + "sample_table_pre.csv"
%cat $sample_table_ori | column -t -s, | cat

frog_1h      frog      1     SINGLE


As the name suggests the attributes in the specified attributes (here: read_type) can be defined as constant ones. The way how this process is carried out is indicated explicitly in the project_config.yaml file (presented below). The name of the column is determined in the sample_modifiers.append key-value pair. Note that definition of more than one constant attribute is possible.

project_config_file = examples_dir + "project_config.yaml"
%cat $project_config_file
pep_version: "2.0.0"
sample_table: sample_table.csv

    read_type: SINGLE

Let's introduce a few modifications to the original sample_table.csv file to use the sample_modifiers.append section of the config. Simply skip the attributes that are set constant and let the pepr do the work for you.

sample_table = examples_dir + "sample_table.csv"
%cat $sample_table | column -t -s, | cat


Import peppy and read in the project metadata by specifying the path to the project_config.yaml:

from peppy import Project
p = Project(project_config_file)

And inspect it:

Project 'example_append' (/Users/mstolarczyk/Uczelnia/UVA/code/peppy/tests/data/example_peps-cfg2/example_append/project_config.yaml)
4 samples: pig_0h, pig_1h, frog_0h, frog_1h
Sections: pep_version, sample_table, sample_modifiers

organism read_type sample_name time
pig_0h pig SINGLE pig_0h 0
pig_1h pig SINGLE pig_1h 1
frog_0h frog SINGLE frog_0h 0
frog_1h frog SINGLE frog_1h 1

As you can see, the resulting samples are annotated the same way as if they were read from the original annotations file with attributes in the last column manually determined.