Open your data in Excel and save it as a CSV file.

L1,L2,L3,L4,L5,GENE_NAME
Enzyme,Kinase,Protein Kinase,Ser_Thr,Cmgc,MAPK11
Enzyme,Kinase,Protein Kinase,Tyr,Tk,ABL1
Enzyme,Kinase,Protein Kinase,Tyr,Tk,PDGFRB
Enzyme,Kinase,Protein Kinase,Tyr,Tk,PDGFRA
Enzyme,Kinase,Protein Kinase,Ser_Thr,Tkl,ALK
Enzyme,Isomerase,Isomerase Other,,,gyrB
Enzyme,Oxidoreductase,Oxidoreductase Other,,,ALOX5
Enzyme,Oxidoreductase,Oxidoreductase Other,,,IMPDH1
Enzyme,Transferase,Transferase Other,,,COMT
Enzyme,Oxidoreductase,Oxidoreductase Other,,,RRM1
Enzyme,Oxidoreductase,Oxidoreductase Other,,,PTGS2
Enzyme,Lyase,Lyase Other,,,POLB
Enzyme,Lyase,Lyase Other,,,CA5B
Enzyme,Hydrolase,Hydrolase Other,,,GAA
Enzyme,Protease,Metallo,MAM,M10A,MMP8
Enzyme,Lyase,Lyase Other,,,CA5A
Enzyme,Lyase,Lyase Other,,,CA7

You can do the rest in Python:

import csv
import json
import sys

tree = {}

reader = csv.reader(open(sys.argv[1], 'rb'))
reader.next() 
for row in reader:
    subtree = tree
    for i, cell in enumerate(row):
        if cell:
            if cell not in subtree:
                subtree[cell] = {} if i<len(row)-1 else 1
            subtree = subtree[cell]

print json.dumps(tree, indent=4)

Save the script as csv2json.py and run it:

python csv2json.py test.csv

It gives you:

{
    "Enzyme": {
        "Protease": {
            "Metallo": {
                "MAM": {
                    "M10A": {
                        "MMP8": 1
                    }
                }
            }
        }, 
        "Isomerase": {
            "Isomerase Other": {
                "gyrB": 1
            }
        }, 
        "Kinase": {
            "Protein Kinase": {
                "Tyr": {
                    "Tk": {
                        "ABL1": 1, 
                        "PDGFRB": 1, 
                        "PDGFRA": 1
                    }
                }, 
                "Ser_Thr": {
                    "Tkl": {
                        "ALK": 1
                    }, 
                    "Cmgc": {
                        "MAPK11": 1
                    }
                }
            }
        }, 
        "Transferase": {
            "Transferase Other": {
                "COMT": 1
            }
        }, 
        "Lyase": {
            "Lyase Other": {
                "CA5B": 1, 
                "CA5A": 1, 
                "CA7": 1, 
                "POLB": 1
            }
        }, 
        "Oxidoreductase": {
            "Oxidoreductase Other": {
                "PTGS2": 1, 
                "ALOX5": 1, 
                "IMPDH1": 1, 
                "RRM1": 1
            }
        }, 
        "Hydrolase": {
            "Hydrolase Other": {
                "GAA": 1
            }
        }
    }
}

Here is a python script I wrote a while back to produce JSON data for D3.js sunburst diagram which is similar to protovis (same author). What's nice about python is that printing data variables as string is basically JSON. You need to get your data into tab delimited format. You might have to modify the script a little to get it to work with protovis.

import sys
dataStructure = {}
for line in open(sys.argv[1],'r'):
    data = line.strip().split()

    current = dataStructure
    for item in data[:-2]:
        if not current.has_key(item):
            current[item] = {}

        current = current[item]
    if not current.has_key(data[-2]):
        current[data[-2]] = 1
    else:
        current[data[-2]] += 1
print 'var data = ' + str(dataStructure)

Save as script.py and run by:

python script.py myData.tabdelimited > myData.json

For example, here are some sample data:

A    1    F    gene1
A    1    F    gene2
A    2    G    gene3
A    2    G    gene4
A    2    H    gene5
B    3    I    gene6
C    4    J    gene7
C    5    K    gene8
D    6    L    gene9
D    6    M    gene10
D    6    L    gene11

Here is the output of the script:

var data = {'A': {'1': {'F': 2}, '2': {'H': 1, 'G': 2}}, 'C': {'5': {'K': 1}, '4': {'J': 1}}, 'B': {'3': {'I': 1}}, 'D': {'6': {'M': 1, 'L': 2}}}

Working on a Macintosh, I found it helpful to replace the:

​ 'reader = ...'

line with:

reader = csv.reader(open("filename.csv", 'rU'), quotechar='"', delimiter = ',')

This got me past the:

new-line character seen in unquoted field - do you need to open the file in universal-newline mode?

Note this specifies the name of the csv file rather than expecting it as an argument from the command line.