genedataset 1.0.0a4

Store and access gene expression datasets and gene definitions.

genedataset is a package to store and access gene expression datasets and gene definitions. It consists of two main classes, geneset and dataset.

Changes in version 1.0

Some significant changes have been made in this version: 1. “MedianTranscriptLength” property of Geneset has been replaced with “TranscriptLengths”, which holds a list of transcript lengths, one per transcript (eg. [2000,1530]). Note that the value contained is a string, so convert into a list of integers before using the value. 2. The Gene annotation has been upgraded to Ensembl version 88. 3. Dataset no longer supports microarrays, so it’s been simplified, so related methods are deprecated. 4. The package supports both python 3 and 2 - tested on 2.7.14 and 3.6.3.

Installation

pip install genedataset

# If this installs the old version 0.6 instead of the latest, explicitly specify the version:
pip install genedataset==[latest_version_number]

geneset

geneset stores gene information combined from both Ensembl and NCBI/Entrez (mouse and human only), so that you can query it:

from genedataset import geneset
gs = geneset.Geneset().subset(queryStrings='ccr3')
print(gs.geneIds())
 ['ENSG00000183625', 'ENSMUSG00000035448']
gs.dataframe()

 | EnsemblId          | Species     | EntrezId | GeneSymbol | Synonyms                     | Description                      | TranscriptLengths                             | Orthologue              |
 |--------------------|:-----------:|---------:|-----------:|-----------------------------:|---------------------------------:|----------------------------------------------:|------------------------:|
 | ENSG00000183625    | HomoSapiens | 1232     | CCR3       | CC-CKR-3|CD193|CKR3|CMKBR3   | C-C motif chemokine receptor 3   | [2000, 1581, 400, 436, 212, 1284, 1201, 1786] | ENSMUSG00000035448:Ccr3 |
 | ENSMUSG00000035448 | MusMusculus | 12771    | Ccr3       | CC-CKR3|CKR3|Cmkbr1l2|Cmkbr3 | chemokine (C-C motif) receptor 3 | [3272]                                        | ENSG00000183625:CCR3    |

dataset

dataset can store gene expression data so that it can be queried. The stored data consists of expression values (usually rna-seq) and sample data packaged into HDF5 format.

from genedataset import dataset
ds = dataset.Dataset("genedataset/data/testdata.1.0.h5")
ds
 <Dataset name:testdata 4 samples>
ds.expressionMatrix()

 | featureId | s01  | s02  | s03  | s04  |
 |---------|------|------|------|------|
 | gene1  | 3.45 | 4.65 | 2.65 | 8.23 |
 | gene2  | 5.54 | 0.00 | 1.43 | 6.43 |
 | gene3  | 0.00 | 0.00 | 4.34 | 5.44 |

ds.sampleTable()

 | sampleId | celltype | tissue |
 |----------|----------|--------|
 | s01      | B1       | BM     |
 | s02      | B1       | BM     |
 | s03      | B2       | BM     |
 | s04      | B2       | BM     |

Dataset creation example

Here is an example to create a Dataset file from text files. Once the file has been created, it can be accessed through the Dataset instance. The advantage of this is to store all related information for a dataset in one file, and gives you a python object that can be used for analyses and for application development.

import pandas
from genedataset import dataset
attributes = {"name": "testdata",
              "fullname": "Test Dataset",
              "version": "1.0",
              "description": "This dataset comes with the package for testing purposes.",
              "expression_data_keys": ["counts","cpm"],
              "pubmed_id": None,
              "species": "MusMusculus"}
samples = pandas.DataFrame([['B1', 'BM'], ['B1', 'BM'], ['B2', 'BM'], ['B2', 'BM']],
                           index=['s01','s02','s03','s04'],
                           columns=['celltype','tissue'])
samples.index.name = "sampleId"
counts = pandas.DataFrame([[35, 44, 21, 101], [50, 0, 14, 62], [0, 0, 39, 73]],
                          index=['gene1', 'gene2', 'gene3'], columns=['s01', 's02', 's03', 's04'])
counts.index.name = "geneId"
cpm = pandas.DataFrame([[3.45, 4.65, 2.65, 8.23], [5.54, 0.0, 1.43, 6.43], [0.0, 0.0, 4.34, 5.44]],
                       index=['gene1', 'gene2', 'gene3'], columns=['s01', 's02', 's03', 's04'])
cpm.index.name = "geneId"
dataset.createDatasetFile("/datasets", attributes=attributes, samples=samples, expressions=[counts,cpm])

Contact

Jarny Choi, University of Melbourne

• e-mail: [e-mail]

Changes

• v1.0 - Major upgrade.

• v0.1.x - Initial release with minor adjustments to test pypi and github upload/download.

License

MIT License