cytoscape

checkCytoscapeVersion

Checks cytoscape version.

CheckResponse(r)

host cytoscape host address, default=cytoscape_host
port cytoscape port, defaul=cytoscape_port
returns nothing

>>> import AGEpy as age
>>> age.checkCytoscapeVersion()

cytoscapeVersion 3.6.0
apiVersion v1

cytoscape

General function for interacting with Cytoscape API.

cytoscape(namespace,command="",PARAMS={},host=cytoscape_host,port=cytoscape_port,method="POST",verbose=False)

namespace namespace where the request should be executed. eg. "string"
commnand command to execute. eg. "protein query"
PARAMs a dictionary with the parameters. Check your swagger normaly running on 'http://localhost:1234/v1/swaggerUI/swagger-ui/index.html?url=http://localhost:1234/v1/commands/swagger.json'
host cytoscape host address, default=cytoscape_host
port cytoscape port, default=cytoscape_port
method type of http call, ie. "POST" or "GET" or "HELP".
verbose print more information
returns For "POST" the data in the content's response. For "GET" None.

>>> import AGEpy as age
>>> response=age.cytoscape("string","pubmed query",{"pubmed":"p53 p21","limit":"50"})
>>> print response

{u'SUID': 37560}

result

Displays the current network.

result(filetype="PNG", saveas=None, host=cytoscape_host, port=cytoscape_port)

filetype file type, default="PNG"
saveas /path/to/non/tmp/file.prefix
host cytoscape host address, default=cytoscape_host
port cytoscape port, default=cytoscape_port
returns an image

>>> import AGEpy as age
>>> response=age.result()
>>> response

cytoscape

getTableColumns

Gets tables from cytoscape.

getTableColumns(table, columns, namespace = "default", network = "current", host=cytoscape_host,port=cytoscape_port,verbose=False)

table table to retrieve eg. node
columns columns to retrieve in list format
namespace namepsace, default="default"
network a network name or id, default="current"
host cytoscape host address, default=cytoscape_host
port cytoscape port, default=cytoscape_port
verbose print more information
returns a pandas dataframe

>>> import AGEpy as age
>>> response=age.getTableColumns('node',['display name'])
>>> print response

                     display name
9606.ENSP00000367207          MYC
9606.ENSP00000356150         MDM4
9606.ENSP00000228872       CDKN1B
9606.ENSP00000361021         PTEN
9606.ENSP00000265734         CDK6

loadTableData

Loads tables into cytoscape.

loadTableData(df, df_key='index',table="node", table_key_column = "name", network="current", namespace="default", host=cytoscape_host, port=cytoscape_port, verbose=False)

df a pandas dataframe to load
df_key key column in df, defaul="index"
table target table, default="node"
table_key_column table key column, default="name"
network a network name or id, default="current"
host cytoscape host address, default=cytoscape_host
port cytoscape port, default=cytoscape_port
verbose print more information
returns output of put request

>>> import AGEpy as age
>>> print df.head()

                     display name
9606.ENSP00000367207          MYC
9606.ENSP00000356150         MDM4
9606.ENSP00000228872       CDKN1B
9606.ENSP00000361021         PTEN
9606.ENSP00000265734         CDK6

>>> def MarkCKDs(x):
...    if "CDK" in x:
...        res="yes"
...    else:
...        res="not"
...    return res
>>> df["CDK"]=df["display name"].apply( lambda x: MarkCKDs(x) )
>>> print df.head()

                     display name  CDK
9606.ENSP00000367207          MYC  not
9606.ENSP00000356150         MDM4  not
9606.ENSP00000228872       CDKN1B  yes
9606.ENSP00000361021         PTEN  not
9606.ENSP00000265734         CDK6  yes

>>> response=age.loadTableData(df[["CDK"]])

simple_defaults

Simplifies default layouts.

simple_defaults(defaults_dic)

defaults_dic a dictionary of the form { visualProperty_A:value_A, visualProperty_B:value_B, ..}
returns a list of dictionaries with each item corresponding to a given key in defaults_dic

>>> import AGEpy as age
>>> defaults_dic={"NODE_SHAPE":"ellipse",\
                  "NODE_SIZE":60,\
                  "NODE_FILL_COLOR":"#AAAAAA",\
                  "EDGE_TRANSPARENCY":120}
>>> defaults_list=age.simple_defaults(defaults_dic)
>>> print defaults_list

[{'visualProperty': 'NODE_SIZE', 'value': 60}, \
{'visualProperty': 'NODE_FILL_COLOR', 'value': '#AAAAAA'}, \
{'visualProperty': 'NODE_SHAPE', 'value': 'ellipse'}, \
{'visualProperty': 'EDGE_TRANSPARENCY', 'value': 120}]

create_styles

Creates a new visual style.

create_styles(title,defaults=None,mappings=None,host=cytoscape_host,port=cytoscape_port)

title title of the visual style
defaults a list of dictionaries for each visualProperty
mappings a list of dictionaries for each visualProperty
host cytoscape host address, default=cytoscape_host
port cytoscape port, default=cytoscape_port
retunrs nothing

>>> import AGEpy as age
>>> print defaults_list

[{'visualProperty': 'NODE_SIZE', 'value': 60}, \
{'visualProperty': 'NODE_FILL_COLOR', 'value': '#AAAAAA'}, \
{'visualProperty': 'NODE_SHAPE', 'value': 'ellipse'}, \
{'visualProperty': 'EDGE_TRANSPARENCY', 'value': 120}]

>>> response=age.create_styles("newStyle",defaults=defaults_list)

update_style

Updates a visual style.

update_style(title, defaults=None, mappings=None, host=cytoscape_host, port=cytoscape_port, verbose=False)

title title of the visual style
defaults a list of dictionaries for each visualProperty
mappings a list of dictionaries for each visualProperty
host cytoscape host address, default=cytoscape_host
port cytoscape port, default=cytoscape_port
retunrs nothing

>>> import AGEpy as age
>>> print new_defaults_list

[{'visualProperty': 'NODE_SIZE', 'value': 80}, \
{'visualProperty': 'NODE_FILL_COLOR', 'value': '#AAAAAA'}, \
{'visualProperty': 'NODE_SHAPE', 'value': 'ellipse'}, \
{'visualProperty': 'EDGE_TRANSPARENCY', 'value': 120}]

>>> response=age.update_style("newStyle",defaults=defaults_list)

mapVisualProperty

Generates a dictionary for a given visual property

mapVisualProperty(visualProperty, mappingType, mappingColumn, lower=None,center=None,upper=None, discrete=None, network="current",table="node", namespace="default", host=cytoscape_host, port=cytoscape_port, verbose=False)

visualProperty visualProperty
mappingType mappingType
mappingColumn mappingColumn
lower for "continuous" mappings a list of the form [value,rgb_string]
center for "continuous" mappings a list of the form [value,rgb_string]
upper for "continuous" mappings a list of the form [value,rgb_string]
discrete for discrete mappings, a list of lists of the form [ list_of_keys, list_of_values ]
network a network name or id, default="current"
host cytoscape host address, default=cytoscape_host
port cytoscape port, default=cytoscape_port
retunrs a dictionary for the respective visual property

>>> import AGEpy as age
>>> import matplotlib

>>> NODE_LABEL=age.mapVisualProperty("NODE_LABEL","passthrough","display name")
>>> print NODE_LABEL

{'mappingType': 'passthrough', 'visualProperty': 'NODE_LABEL', 'mappingColumnType': u'String', 'mappingColumn': 'display name'}

>>> NODE_SHAPE=age.mapVisualProperty('NODE_SHAPE','discrete','CDK',\
                                     discrete=[ ["yes","not"], \
                                     ["DIAMOND", "ellipse"] ])

>>> NODE_SIZE=age.mapVisualProperty('NODE_SIZE','discrete','CDK',\
                                    discrete=[ ["yes","not"],\
                                    ["100.0","60.0"] ])

# imagine you have a log2(fold_change) column in your cytoscape table
>>> cmap = matplotlib.cm.get_cmap("bwr")
>>> norm = matplotlib.colors.Normalize(vmin=-4, vmax=4)
>>> min_color=matplotlib.colors.rgb2hex(cmap(norm(-4)))
>>> center_color=matplotlib.colors.rgb2hex(cmap(norm(0)))
>>> max_color=matplotlib.colors.rgb2hex(cmap(norm(4)))  
>>> NODE_FILL_COLOR=age.mapVisualProperty('NODE_FILL_COLOR','continuous','log2(fold_change)',\
                                      lower=[-4,min_color],center=[0.0,center_color],upper=[4,max_color])

aDiffCytoscape

Plots tables from aDiff/cuffdiff into cytoscape using String protein queries. Uses top changed genes as well as first neighbours and difusion fo generate subnetworks.

aDiffCytoscape(df, aging_genes, target, species="caenorhabditis elegans", limit=None, cutoff=0.4, taxon=None, cytoscape_host=cytoscape_host, cytoscape_port=cytoscape_port)

df df as outputed by aDiff for differential gene expression
aging_genes ENS gene ids to be labeled with a diagonal
target target destination for saving files without prefix. eg. "/beegfs/group_bit/home/JBoucas/test/N2_vs_daf2"
species species for string app query. eg. "caenorhabditis elegans", "drosophila melanogaster", "mus musculus", "homo sapiens"
limit limit for string app query. Number of extra genes to recover. If None, limit=N(query_genes)*.25
cuttoff confidence cuttoff for sting app query. Default=0.4
taxon taxon id for string app query. For the species shown above, taxon id will be automatically identified
cytoscape_host host address for cytoscape, default=cytoscape_host
cytoscape_port cytoscape port, defaut=cytoscape_port
returns nothing

>>> import AGEpy as age
>>> print genes[:10]

['WBGene00008288', 'WBGene00002169', 'WBGene00008733', 'WBGene00004178', 'WBGene00004178', 'WBGene00004179', 'WBGene00004179', 'WBGene00020581', 'WBGene00001877', 'WBGene00001881']

>>> print df.head()

ensembl_gene_id            gene            locus sample_1 sample_2 status  \
0  WBGene00022275        Y74C9A.1    I:43732-44677       N2     daf2     OK   
1  WBGene00004418  F53G12.9,rpl-7  I:111037-113672       N2     daf2     OK   
2  WBGene00018774  F53G12.9,rpl-7  I:111037-113672       N2     daf2     OK   
3  WBGene00018772        F53G12.4  I:134336-137282       N2     daf2     OK   
4  WBGene00018958        F56C11.6  I:171339-175991       N2     daf2     OK   

     value_1      value_2  log2(fold_change)  test_stat  p_value   q_value  \
0     0.195901     0.986634           2.332390    2.32959  0.00570  0.031216   
1  3354.820000  2463.480000          -0.445539   -2.71381  0.00005  0.000556   
2  3354.820000  2463.480000          -0.445539   -2.71381  0.00005  0.000556   
3     1.235670     2.992460           1.276040    3.16508  0.00005  0.000556   
4     2.651180     3.795600           0.517696    1.73994  0.00410  0.024157   

significant                                              GO_id  \
0         yes                                                NaN   
1         yes  GO:0003735; GO:0000463; GO:0044822; GO:0002181...   
2         yes                                                NaN   
3         yes                                                NaN   
4         yes                 GO:0016787; GO:0005615; GO:0004104   

                                           GO_term    gene_biotype  \
0                                                NaN  protein_coding   
1  structural constituent of ribosome; maturation...  protein_coding   
2                                                NaN  protein_coding   
3                                                NaN  protein_coding   
4  hydrolase activity; extracellular space; choli...  protein_coding   

  NormInt evidence  
0 -0.356904       no  
1  3.458609       no  
2  3.458609       no  
3  0.283965       no  
4  0.501360       no  

>>> age.aDiffCytoscape(df,genes,"/u/home/JBoucas/cytoscape/cyto")