RNAlysis 1.3.6

RNAlysis provides a modular analysis pipeline for RNA sequencing data. The package includes various methods for filtering, data visualisation, exploratory analyses, enrichment anslyses and clustering.

Useful links: Documentation | Source code | Bug reports | | | |

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What is RNAlysis?

RNAlysis is a Python-based modular analysis pipeline for RNA sequencing data. You can use it to normalize, filter and visualize your data, cluster genes based on their expression patterns, and perform enrichment analysis for both Gene Ontology terms and user-defined attributes.

RNAlysis allows you to perform filtering operations and analyses at any order you wish. You can save or load your progress at any given point; the operations you performed on your data and their order will be reflected in saved file’s name.

RNAlysis works with gene expression matrices and differential expression tables in general, and integrates in particular with Python’s HTSeq-count and R’s DESeq2.

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What can I do with RNAlysis?

• Filter your gene expression matrices, differential expression tables, fold change data, and tabular data in general.

• Normalize your gene expression matrices

• Visualise, explore and describe your sequencing data

• Find global relationships between sample expression profiles with clustering analyses and dimensionality reduction

• Create and share analysis pipelines

• Perform enrichment analysis with pre-determined Gene Ontology terms, or with used-defined attributes

• Perform enrichment analysis on a single ranked list, instead of a test set and a background set

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How do I install it?

You can install RNAlysis via PyPI. Use the following command in the python prompt:

pip install RNAlysis

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Dependencies

• numpy

• pandas

• scipy

• matplotlib

• seaborn

• tissue_enrichment_analysis

• statsmodels

• scikit-learn

• ipyparallel

• grid_strategy

• Distance

• pyyaml

• UpSetPlot

• matplotlib-venn

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Where to get it

Use the following command in the python prompt:

pip install RNAlysis

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Credits

How do I cite RNAlysis?

Teichman, G. (2020) RNAlysis: RNA Sequencing analysis pipeline (Python package version 2.0.0).

Development Lead

• Guy Teichman: [e-mail]

Contributors

• Or Ganon

• Netta Dunsky

• Shachar Shani

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This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

History

1.3.6 (2021-06-17)

• This version introduces minor bug fixes.

Changed

• Relinquished support for Python versions below 3.7.

Fixed

• Fixed bug with dependency collisions when installing RNAlysis in an empty Python environment.

• Fixed security vulnerability in developer test environment.

1.3.5 (2020-05-27)

• This version introduces minor bug fixes and a few more visualization options.

Added

• Added the visualization function CountFilter.box_plot().

Changed

• Updated docstrings and printouts of several functions.

• Slightly improved speed and performance across the board.

• Filter.feature_string() is now sorted alphabetically.

• Enrichment randomization functions in the enrichment module now accept a ‘random_seed’ argument, to be able to generate consistent results over multiple sessions.

• Enrichment randomization functions can now return the matplotlib Figure object, in addition to the results table.

Fixed

• Fixed DepracationWarning on parsing functions from the general module.

• Fixed bug where saving csv files on Linux systems would save the files under the wrong directory.

• Fixed a bug where UTF-8-encoded Reference Tables won’t be loaded correctly

1.3.4 (2020-04-07)

• This version fixed a bug that prevented installation of the package.

Changed

• Updated docstrings and printouts of several functions

Fixed

• Fixed a bug with installation of the previous version

1.3.3 (2020-03-28)

• First stable release on PyPI.

Added

• Added Filter.sort(), and upgraded the functionality of Filter.filter_top_n().

• Added UpSet plots and Venn diagrams to enrichment module.

• User-defined biotype reference tables can now be used.

• Filter operations now print out the result of the operation.

• Enrichment randomization tests now also support non-WBGene indexing.

• Filter.biotypes() and FeatureSet.biotypes() now report genes that don’t appear in the biotype reference table.

• Filter.biotypes() can now give a long-form report with descriptive statistics of all columns, grouped by biotype.

• Added code examples to the user guide and to the docstrings of most functions.

Changed

• Changed argument order and default values in filtering.CountFilter.from_folder().

• Changed default title in scatter_sample_vs_sample().

• Changed default filename in CountFilter.fold_change().

• Settings are now saved in a .yaml format. Reading and writing of settings have been modified.

• Changed argument name ‘deseq_highlight’ to ‘highlight’ in scatter_sample_vs_sample(). It can now accept any Filter object.

• Updated documentation and default ‘mode’ value for FeatureSet.go_enrichment().

• Updated the signature and function of general.load_csv() to be clearer and more predictable.

• Changed argument names in CountFilter.from_folder().

• Modified names and signatures of .csv test files functions to make them more comprehensible.

• Renamed ‘Filter.filter_by_ref_table_attr()’ to ‘Filter.filter_by_attribute()’.

• Renamed ‘Filter.split_by_ref_table_attr()’ to ‘Filter.split_by_attribute()’.

• Renamed ‘Filter.norm_reads_with_size_factor()’ to ‘Filter.normalize_with_scaling_factors()’. It can now use any set of scaling factors to normalize libraries.

• Renamed ‘Filter.norm_reads_to_rpm()’ to ‘Filter.normalize_to_rpm()’.

• Made some functions in the general module hidden.

Fixed

• Various bug fixes

Removed

• Removed the ‘feature_name_to_wbgene’ module from RNAlysis.

1.3.2 (2019-12-11)

• First beta release on PyPI.