LBMC » NucleoMiner

Python and R Common Configuration File

--------------------------------------

First of all we define in one place some configuration variables that will be launch by python and R scripts. This file is **configurator.py**. The execution of this python script dumps variables into the **nucleo_miner_config.json** that will be launch by both kind of scriopts (R and puython).

To do this launch at the root of your project the following command line:

.. code:: bash

  python src/current/configurator.py

$$$ other python script to describe:

- libcoverage.py

- wf.py

Dataset and Configuration Variables

-----------------------------------

In order to simplify the design of experiment, we considere Mnase as a marker. 

For some reasons (manipulation efficiency, e.g. PCR...), we remove samples 33, 45, 48 and 55.

^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

The second part of the tutorial uses `R` (http://http://www.r-project.org). It consists in a set of R scripts taht will be sourced in an R console launched at the root of your project. the R srcipts are:

  - headers.R

The Script headers.R

^^^^^^^^^^^^^^^^^^^^

The script header.R is included in each other scripts. It is in charge of: 

  - launching libraries used in thes scripts

  - launching configuration (design, strain, marker...)

  - computing and caching CURs

In your R console, run the following command line:

  R CMD BATCH src/current/header.R

The Script extract_maps.R

^^^^^^^^^^^^^^^^^^^^^^^^^

This script is in charge of extracting Maps for well positioned and fuzzy nucleosomes. First of all, this script computed intra and inter strain nucleosome maps for each CUR. This step is executed in parallel on many cores using the BoT library. Next, it collects results and produces well positioned, fuzzy and UNR maps.

The well-positioned map for BY is collected in the result directory and is called **BY_wp.tab**. It is composed of following columns:

 - chr, the number of the chromosome 

 - lower_bound, the lower bound of the nucleosome

 - upper_bound, the upper bound of the nucleosome 

 - cur_index, index of the CUR

 - index_nuc, the index of the nucleosome in the CUR

 - wp, 1 if it is a well positioned nucleosome, 0 else

 - nb_reads, the number of reads that supports this nucleosome

 - nb_nucs, the number of TemplateFilter nucleosome across replicates (= the number of replicates if it is a well-positioned nucleosome)

 - llr_1, for a well-positioned nucleosome, it is the LLR1 between the first and the second TemplateFilter nucleosome.

 - llr_2, for a well-positioned nucleosome, it is the LLR1 between the second and the first TemplateFilter nucleosome.

 - wp_llr, for a well-positioned nucleosome, it is the LLR2 overall TemplateFilter nucleosomes.

 - wp_pval, for a well-positioned nucleosome, it is the p-value chi square test obtained with the LLR2 (**1-pchisq(2.LLR2, df=4)**)

 - dyad_shift, for a well-positioned nucleosome, it is shift between the two extreme TemplateFilter nucleosome dyad positions. 

The fuzzy map for BY is collected in the result directory and is called **BY_fuzzy.tab**. It is composed of following columns:

 - chr, the number of the chromosome 

 - lower_bound, the lower bound of the nucleosome

 - upper_bound, the upper bound of the nucleosome 

 - cur_index, index of the CUR

The common well-position map for BY and RM strains is collected in the result directory and is called **BY_RM_common_wp.tab**. It is composed of following columns:

 - cur_index, the index of the CUR

 - index_nuc_BY, the index of the BY nucleosome in the CUR

 - index_nuc_RM,the index of the RM nucleosome in the CUR

 - llr_score, the LLR3 score between th eBy and RM nucleosomes

 - common_wp_pval,  the p-value chi square test obtained with the LLR3 (**1-pchisq(2.LLR3, df=2)**)

The common UNR map for BY and RM strains is collected in the result directory and is called **BY_RM_common_unr.tab**. It is composed of following columns:

 - cur_index, the index of the CUR

 - index_nuc_BY, the index of the BY nucleosome in the CUR

 - index_nuc_RM,the index of the RM nucleosome in the CUR

To execute this script, run the following command line in your R console:

  source("src/current/extract_maps.R")

The Script compare_common_wp.R

^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

This script is used to compare inter strain distances between common well-positioned nucleosomes. 

For example, it compute the file **BY_RM_common_wp_diff.tab** that contains dyad shifts between two well-positioned nucleosomes. It is composed of following columns:

 - cur_index, the index of the CUR

 - index_nuc_BY, the index of the BY nucleosome in the CUR

 - index_nuc_RM,the index of the RM nucleosome in the CUR

 - llr_score, the LLR3 score between th eBy and RM nucleosomes

 - common_wp_pval,  the p-value chi square test obtained with the LLR3 (**1-pchisq(2.LLR3, df=2)**)

 - diff, the dyad shifts between two well-positioned nucleosomes

It also translates well-positioned nucleosome maps from a strain to an other strain and stores it into a table. 

For example, the file **results/2014-04/RM_wp_tr_2_BY.tab** contains RM well-positioned nucleosome translated into the BY genome referential. It is composed of following columns:

 - strain_ref, the reference genome (in which positioned are defined)

 - begin, the translated lower bound of the nucleosome

 - end, the translated upper bound of the nucleosome

 - chr, the number of chromosome for the reference genome (in which positioned are defined)

 - length, the length of the nucleosome (could be negative)

 - cur_index, the index of the CUR

 - index_nuc, the index of the nucleosome in the CUR

To execute this script, run the following command line in your R console:

positioned nucleosomes, fuzzy nucleosomes or both for SNEP computation.