Pegasus 0.17 for Single Cell Analysis

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Pegasus is a tool for analyzing transcriptomes of millions of single cells. It is a command line tool, a python package and a base for Cloud-based analysis workflows.

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Version 0.17.2 June 26, 2020

  • Make Pegasus compatible with umap-learn v0.4+.

  • Use louvain 0.7+ for Louvain clustering.

  • Update tutorial.

Version 0.17.1 April 6, 2020

  • Improve pegasus command-line tool log.

  • Add human lung markers.

  • Improve log-normalization speed.

  • Provide robust version of PCA calculation as an option.

  • Add signature score calculation API.

  • Fix bugs.

Version 0.17.0 March 10, 2020

  • Support anndata 0.7 and pandas 1.0.

  • Better loom format output writing function.

  • Bug fix on mtx format output writing function.

  • Update human immune cell markers.

  • Improve pegasus scp_output command.

Version 0.16.11 February 28, 2020

  • Add --remap-singlets and --subset-singlets options to ‘cluster’ command.

  • Allow reading loom file with user-specified batch key and black list.

Version 0.16.9 February 17, 2020

Allow reading h5ad file with user-specified batch key.

Version 0.16.8 January 30, 2020

Allow input annotated loom file.

Version 0.16.7 January 28, 2020

Allow input mtx files of more filename formats.

Version 0.16.5 January 23, 2020

Add Harmony algorithm for data integration.

Version 0.16.3 December 17, 2019

Add support for loading mtx files generated from BUStools.

Version 0.16.2 December 8, 2019

Fix bug in ‘subcluster’ command.

Version 0.16.1 December 4, 2019

Fix one bug in clustering pipeline.

Version 0.16.0 December 3, 2019

  • Change options in ‘aggregate_matrix’ command: remove ‘–google-cloud’, add ‘–default-reference’.

  • Fix bug in ‘–annotation’ option of ‘annotate_cluster’ command.

  • Fix bug in ‘net_fle’ function with 3-dimension coordinates.

  • Use fisher package version 0.1.9 or above, as modifications in our forked fisher-modified package has been merged into it.

Version 0.15.0 October 2, 2019

Rename package to PegasusPy, with module name pegasus.

Version 0.14.0 September 17, 2019

Provide Python API for interactive analysis.

Version 0.10.0 January 31, 2019

Added ‘find_markers’ command to find markers using LightGBM.

Improved file loading speed and enabled the parsing of channels from barcode strings for cellranger aggregated h5 files.

Version 0.9.0 January 17, 2019

In ‘cluster’ command, changed ‘–output-seurat-compatible’ to ‘–make-output-seurat-compatible’. Do not generate output_name.seurat.h5ad. Instead, output_name.h5ad should be able to convert to a Seurat object directly. In the seurat object, slot refers to the filtered count data, data slot refers to the log-normalized expression data, and refers to the variable-gene-selected, scaled data.

In ‘cluster’ command, added ‘–min-umis’ and ‘–max-umis’ options to filter cells based on UMI counts.

In ‘cluster’ command, ‘–output-filtration-results’ option does not require a spreadsheet name anymore. In addition, added more statistics such as median number of genes per cell in the spreadsheet.

In ‘cluster’ command, added ‘–plot-filtration-results’ and ‘–plot-filtration-figsize’ to support plotting filtration results. Improved documentation on ‘cluster command’ outputs.

Added ‘parquet’ command to transfer h5ad file into a parquet file for web-based interactive visualization.

Version 0.8.0 November 26, 2018

Added support for checking index collision for CITE-Seq/hashing experiments.

Version 0.7.0 October 26, 2018

Added support for CITE-Seq analysis.

Version 0.6.0 October 23, 2018

Renamed scrtools to scCloud.

Added demuxEM module for cell/nuclei-hashing.

Version 0.5.0 August 21, 2018

Fixed a problem related AnnData.

Added support for BigQuery.

Version 0.4.0 August 2, 2018

Added mouse brain markers.

Allow aggregate matrix to take ‘Sample’ as attribute.

Version 0.3.0 June 26, 2018

scrtools supports fast preprocessing, batch-correction, dimension reduction, graph-based clustering, diffusion maps, force-directed layouts, and differential expression analysis, annotate clusters, and plottings.