Help

How to use the programme :

When you have uncompressed the file, the programme you have to open is CGHChip.py with a terminal. 

Here, it's an help for a best understanding of our work.

Starting data:

Different kind of data are: 0(no modification), 1(duplication), -1(deletion) et 9(no data)
Meaning of the three values following the tumour name:

- stage (degree of tumourous invasion)
- rank (very differenciate, intermediate, few differenciate)
- statute of each BAC

Statistics:

Count duplicated, deleted and normal fragments for each tumour.
It also put up when just one modification has generated a tumour.
When a fragment is modified in more then 5% of the tumours or deleted or multiplied in more than 4% of the tumours, it return his index.

Washing:

Remove the "noise" (9 excess)

- Number of 9 between two 0 isn't significant.

- One 9 between two -1 can be replace by one -1.

- One 9 between two 1 can be replace by one 1.

Reliability :

For a file, say if the "washing hypothesis" is okay or not.

Quasi-Implication :

The user chooses the name of two tumours of which he wants to know the implication. He copies and pastes the fragments in the frame. The pattern is:
A group of  -1, 0, 1 et 9 separated by a gap and beginning with a gap. Example : \" -1 0 1 9\".
Starting hypothesis :
- A deleted fragment can't come out again
- A multiplied fragment can't never can't never come back in a normal stage
- A multiplied fragment can't be completely deleted
Knowledge of the succession of the health stage (from few advanced stage to terminal stage).
However, some results go against these hypothesis:
==> Definition of an implication rate.

Discussion :

For a best analysis of data.

Save as ... :

Save the results from a new file. The user can keep his results, save cleansed data and carry out his analysis from this file.

Delete :

Delete all the frame where the results are.

Chromosome counting :

- Positions in n-1 are the same.
- Positions in n are the same but are different from the positions in n-1.
- If there's a sudden change, it can be the beginning of a chromosome.
- N.B: the "noise" prevent finding all of them.

Evolution :

This function analyzes the two numbers following the name of the tumour (the stage and the rank).
- When the rank is 1 and the stage is 2, 3 or 4 : cancer is invasive, very differenciate stage, the tumour is malignant.
- When the rank is 2 and the stage is 1 : intermediate stage.
- On the other cases : cancer no invasive, the tumour is benign.

Graph :

This function put up two tables :
- The first contains a graphe which classifies the tumours according to them evolution. This filing is made according to two numbers following the name.
- The second contains un graphe a graphe which classifies the tumours according to the rate of spoiling of the fragments.
On this way, you can compare the two graphs and see if the evolution of the tumour follows the rate of spoiling.

Chip :

This function put up the data with a colour code :
- The blue spotlights represent the fragments whithout data.
- The red spotlights represent the deleted fragments.
- The yellow spotlights represent the fragments whithout modifications.
- The green spotlights represent the duplicated fragments.
Caution : for th big files, it could take a few second.