| Name | MarkerCount JSON |
| Version |
0.7.1
JSON |
| download |
| home_page | None |
| Summary | Cell-type identification toolkit for single-cell RNA-Seq experiments. |
| upload_time | 2024-09-23 16:02:27 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | None |
| license | MIT License Copyright (c) 2023 Seokhyun Yoon Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
single-cell omics
bioinformatics
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
## MarkerCount update
- Sept 01, 2022: Added HiCAT, an updated version of MarkerCount.
- Dec. 06, 2021: Now, MarkerCount can be used in R. Please see the instruction below.
- June 27, 2021: Slight modification was made to improve the identification performance.
## HiCAT
 
- HiCAT is a marker-based, hierarchical cell-type annotation tool for single-cell RNA-seq data.
- It was developed using python3, but also run in R as well.
- HiCAT works in marker-based mode utilizing only the existing lists of markers.
- Github page: https://github.com/combio-dku/HiCAT
- Please refer to "Hierarchical cell-type identifier accurately distinguishes immune-cell subtypes enabling precise profiling of tissue microenvironment with single-cell RNA-sequencing", Briefings in Bioinformatics, available at https://doi.org/10.1093/bib/bbad006, https://doi.org/10.1101/2022.07.27.501701
### Installation using pip and importing HiCAT in Python
HiCAT can be installed using pip command. With python3 installed in your system, simply use the follwing command in a terminal.
`pip install MarkerCount`
Once it is installed using pip, you can import two functions using the following python command.
`from MarkerCount.hicat import HiCAT, show_summary`
where `show_summary` is used to check the annotation results.
Please check HiCAT github page https://github.com/combio-dku/HiCAT for its usage and example jupyter notebook.
### HiCAT marker file format
Marker file must be a tap-separated-value file (.tsv) with 5 columns, "cell_type_major", "cell_type_minor", "cell_type_subset", "exp" and "markers".
- The first three columns define the 3-level taxonomy tree to be used for hierarchical identification.
- "exp" is type of marker, which can be "pos", "neg", or "sec".
- "markers" is a list of gene symbols separated by comma.
- The markers in "cell_markers_rndsystems_rev.tsv", were reproduced from [R&D systems](https://www.rndsystems.com/resources/cell-markers)
If you want to use your own markers, please refer to the [tips for prepareing markers db](https://github.com/combio-dku/HiCAT/blob/main/PreparingMarkersDB.md).
## MarkerCount and MarkerCount-Ref (Previous version)
- MarkerCount is a python3 cell-type identification toolkit for single-cell RNA-Seq experiments.
- MarkerCount works both in reference and marker-based mode, where the latter utilizes only the existing lists of markers, while the former required pre-annotated dataset to train the model.
- Please refer to the preprint manuscript "MarkerCount: A stable, count-based cell type identifier for single cell RNA-Seq experiments" available at https://www.researchsquare.com/article/rs-418249/v2 DOI: https://doi.org/10.21203/rs.3.rs-418249/v2
### Installation and importing MarkerCount
All the functions to implement MarkerCount are defined in the python3 script, `marker_count.py`, where the two key functions are
1. `MarkerCount()`: marker-based cell-type identifier
1. `MarkerCount_Ref()`: reference-based cell-type identifier
One can import the function by adding a line in your script, i.e., `from marker_count import MarkerCount_Ref, MarkerCount`
Please check MarkerCount github page https://github.com/combio-dku/MarkerCount for its usage and example jupyter notebook.
## Contact
Send email to syoon@dku.edu for any inquiry on the usages.
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