Metadata-Version: 2.1
Name: pyrwrapper
Version: 0.0.1rc4
Summary: r scripts wrapper
Home-page: https://github.com/btrspg/pyrwrapper/tree/master/
Author: Yuelong CHEN
Author-email: yuelong.chen.btr@gmail.com
License: Apache Software License 2.0
Description: # Python Wrappers for R scripts in bioinformatic analysis
        
        
        
        This file will become your README and also the index of your documentation.
        
        ## Install
        
        `pip install pyrwrapper`
        
        ## Plot Venn Diagram
        
        ```
        faker.py venn-plot tests/venn.png \
            --lists tests/list1.txt tests/list2.txt tests/list3.txt tests/list4.txt \
            --tags ALL_file withpy withdot withgo  \
            --print-mode raw
        ```
        
        Then you will get four files: `tests/venn.png`, `tests/venn.png.R`,`tests/venn.png.R.e`,`tests/venn.png.R.o`.
        
        `tests/venn.png` is the graph you want
        
        ![venn](https://cdn.jsdelivr.net/gh/btrspg/images@master/uPic/venn.png)
        
        `tests/venn.png.R` is the R script, if you want to modify and re-run the script, it will be easy.
        `tests/venn.png.R.e` and `tests/venn.png.R.o` is the stderr and stdout of running `tests/venn.png.R`.
        
        ### parameters
        
        
        ```
        
        
        faker.py venn-plot    
        
        
        usage: faker.py venn-plot [-h] -l [LISTS [LISTS ...]] --tags [TAGS [TAGS ...]]
                                  [--title TITLE] [-s SUB_TITLE]
                                  [-p [PRINT_MODE [PRINT_MODE ...]]] [-r RSCRIPT]
                                  output
        
        venn diagram plot
        
        positional arguments:
          output                figure output, the formats could be 'png','tiff','pdf'
        
        optional arguments:
          -h, --help            show this help message and exit
          -l [LISTS [LISTS ...]], --lists [LISTS [LISTS ...]]
                                lists file without title
          --tags [TAGS [TAGS ...]]
                                tags corresponding to lists, the length of lists and tags should be the same
          --title TITLE         graph title
                                (default: Venn Diagram)
          -s SUB_TITLE, --sub-title SUB_TITLE
                                graph subtitle
                                (default: )
          -p [PRINT_MODE [PRINT_MODE ...]], --print-mode [PRINT_MODE [PRINT_MODE ...]]
                                could only be 'raw' or 'percent' or ('raw' and  'percent')
                                (default: ['raw', 'percent'])
          -r RSCRIPT, --rscript RSCRIPT
                                the path of Rscript
                                (default: /usr/bin/env Rscript)
        
        ```
        
        ## Plot complex heatmap
        
        ```
        faker.py complexheatmap-plot tests/ch.pdf tests/matrix.csv tests/sample_info.csv \
                -m Geneid \
                --c-idx sample \
                -v TEST_TPM \
                --row-split-by gene_biotype \
                --col-split-by condition \
                --row-anno-point TV:transcript_version GV:gene_version \
                --row-anno-bar CS:coding_score \
                --row-anno-normal CT:classification \
                --col-anno-point age \
                --col-anno-bar BARAGE:age \
                --col-anno-normal batch condition \
                -t tests \
                --sep-mi , \
                --sep-ci , \
                --rscript '/usr/bin/env Rscript'
        ```
        
        Then you will get four files: `tests/ch.pdf`, `tests/complexheatmap.R`,`tests/complexheatmap.R.e`,`tests/complexheatmap.R.o` and two temporary files `m.csv`, `c.csv`
        
        `tests/ch.pdf` is the graph you want
        
        ![ch](https://cdn.jsdelivr.net/gh/btrspg/images@master/uPic/ch.png)
        
        
        
        
        ### parameters
        
        ```
        faker.py complexheatmap-plot
        
        usage: faker.py complexheatmap-plot [-h] -m M_IDX --c-idx C_IDX
                                            [--show-row-names] [--no-show-row-names]
                                            [--show-column-names]
                                            [--no-show-column-names] [-v VALUE_NAME]
                                            [-w WIDTH] [--height HEIGHT]
                                            [--row-split-by ROW_SPLIT_BY]
                                            [--col-split-by COL_SPLIT_BY]
                                            [--row-anno-point [ROW_ANNO_POINT [ROW_ANNO_POINT ...]]]
                                            [--row-anno-bar [ROW_ANNO_BAR [ROW_ANNO_BAR ...]]]
                                            [--row-anno-normal [ROW_ANNO_NORMAL [ROW_ANNO_NORMAL ...]]]
                                            [--col-anno-point [COL_ANNO_POINT [COL_ANNO_POINT ...]]]
                                            [--col-anno-bar [COL_ANNO_BAR [COL_ANNO_BAR ...]]]
                                            [--col-anno-normal [COL_ANNO_NORMAL [COL_ANNO_NORMAL ...]]]
                                            [--sep-mi SEP_MI] [--sep-ci SEP_CI]
                                            [-t TMP] [--rscript RSCRIPT]
                                            output matrix_in clinical_in
        
        ComplextHeatmap plot
        
        positional arguments:
          output                figure output, the formats could only be 'pdf'
          matrix_in             heatmap input data
          clinical_in           clinical input data
        
        optional arguments:
          -h, --help            show this help message and exit
          -m M_IDX, --m-idx M_IDX
                                heatmap index column name, e.g. 'geneid'
          --c-idx C_IDX         clinical index column name, which are used to identify the data columns in heatmap matrix
          --show-row-names      whether to show row names, if row number are too large, maybe not show.
                                (default: True)
          --no-show-row-names
          --show-column-names   whether to show column names, if row number are too large, maybe not show.
                                (default: True)
          --no-show-column-names
          -v VALUE_NAME, --value-name VALUE_NAME
                                value name in the matrix, e.g. 'count', 'TPM'
                                (default: TPM)
          -w WIDTH, --width WIDTH
                                width of the figure
                                (default: 10)
          --height HEIGHT       height of the figure
                                (default: 15)
          --row-split-by ROW_SPLIT_BY
                                can specific split rows into different blocks by specific column in the matrix data, e.g. 'Pathway of genes'
                                (default: None)
          --col-split-by COL_SPLIT_BY
                                can specific split columns into different blocks by specific column in the clinical data, e.g. 'condition'
                                (default: None)
          --row-anno-point [ROW_ANNO_POINT [ROW_ANNO_POINT ...]]
                                can specific annotate row by point plot, you can also specify the name of annotation by log2fc:foldchange, e.g. 'foldchange' 'pvalue'
                                (default: None)
          --row-anno-bar [ROW_ANNO_BAR [ROW_ANNO_BAR ...]]
                                can specific annotate row by bar plot,you can also specify the name of annotation by name:colname, e.g. 'flodchange' 'pvalue'
                                (default: None)
          --row-anno-normal [ROW_ANNO_NORMAL [ROW_ANNO_NORMAL ...]]
                                can specific annotate row by condition,you can also specify the name of annotation by name:colname, e.g. 'biotype'
                                (default: None)
          --col-anno-point [COL_ANNO_POINT [COL_ANNO_POINT ...]]
                                can specific annotate column by point plot, you can also specify the name of annotation by name:colname, e.g. 'age'
                                (default: None)
          --col-anno-bar [COL_ANNO_BAR [COL_ANNO_BAR ...]]
                                can specific annotate column by bar plot, you can also specify the name of annotation by name:colname,  e.g. 'age'
                                (default: None)
          --col-anno-normal [COL_ANNO_NORMAL [COL_ANNO_NORMAL ...]]
                                can specific annotate column by condition, you can also specify the name of annotation by name:colname,  e.g. 'gender'
                                (default: None)
          --sep-mi SEP_MI       separation in matirx file
                                (default:       )
          --sep-ci SEP_CI       separation in clinical file
                                (default:       )
          -t TMP, --tmp TMP     temporary direction
                                (default: ./)
          --rscript RSCRIPT     Rscript path
                                (default: /usr/bin/env Rscript)
        
        ```
        
        ## MuSiC deconvolution
        
        ```bash
        faker.py music-deconvolution \
                -c cell_type  \
                --samples sample \ 
                -t tests \
                tests/bulk_count.csv \
                tests/sc_count.csv \
                tests/bulk_info.csv \
                tests/sc_info.csv \
                tests/music.csv
        
        ```
        
        
        
        Then we will get a deconvolution results [as here](./tests/music.csv)
        
        ### parameters
        ```
        usage: faker.py music-deconvolution [-h] -c CLUSTER --samples SAMPLES
                                            [--select-ct [SELECT_CT [SELECT_CT ...]]]
                                            [--bulk-filter BULK_FILTER]
                                            [--sc-filter SC_FILTER]
                                            [--bulk-count-sep BULK_COUNT_SEP]
                                            [--sc-count-sep SC_COUNT_SEP]
                                            [--bulk-info-sep BULK_INFO_SEP]
                                            [--sc-info-sep SC_INFO_SEP] [-t TMP]
                                            [-r RSCRIPT]
                                            bulk_count sc_count bulk_info sc_info
                                            output
        
        Multi-subject Single Cell deconvolution  (MuSiC github.com/xuranw/MuSiC)
        
        positional arguments:
          bulk_count            bulk RNA-seq count data, first columns should be the gene identification(unique)
          sc_count              single-cell RNA-seq count data, first columns should be the gene identification(unique) same as bulk_count
          bulk_info             bulk RNA-seq information
          sc_info               single-cell RNA-seq information: samples, cell type ,etc. The first column should be the cell identification.
          output                will write the result out in .csv format
        
        optional arguments:
          -h, --help            show this help message and exit
          -c CLUSTER, --cluster CLUSTER
                                column name of cell type in sc_info
          --samples SAMPLES     column name of sample name in sc_info, (need to know the single cell source, from which sample)
          --select-ct [SELECT_CT [SELECT_CT ...]]
                                cell types to deconvolution
                                (default: NULL)
          --bulk-filter BULK_FILTER
                                bulk RNA-seq depth filter
                                (default: 20)
          --sc-filter SC_FILTER
                                single-cell RNA-seq depth filter
                                (default: 20)
          --bulk-count-sep BULK_COUNT_SEP
                                bulk_count file separation
                                (default: ,)
          --sc-count-sep SC_COUNT_SEP
                                single-cell count file separation
                                (default: ,)
          --bulk-info-sep BULK_INFO_SEP
                                bulk_info file separation
                                (default: ,)
          --sc-info-sep SC_INFO_SEP
                                single-cell info file separation
                                (default: ,)
          -t TMP, --tmp TMP     temporary file direction
                                (default: ./)
          -r RSCRIPT, --rscript RSCRIPT
                                Rscript path
                                (default: /usr/bin/env Rscript)
        
        ```
        
Keywords: R Python Wrapper
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/markdown
