DEMINING

DEMINING: a stepwise computational framework to directly detect expressed DNA and RNA mutations in RNA deep sequencing data (DEMINING).

Version: 1.0 2023/12/15

Author: Zhi-Can Fu ([email protected])

1. Installation

1.1 Download DEMINING git repo and decompress DEMINING.zip with password

    git clone [email protected]:fuzhican/DEMINING.git
    cd DEMINING; unzip DEMINING.zip

1.2 Create conda environment and activate

    conda env create -f environment.yml 
    conda activate ~/DEMINING_env

2. Usage

    Usage: DEMINING -f Function -1 Path_of_fastq1 -2 Path_of_fastq2 -o Output_path -n Output_name -c Path_of_config_file -t Maximum_threads -g Genome_build_version [ -s Site_list_file -b BAM_file ]

    Arguments:
            [-f Function, "Read_mapping", "Variant_classification" or "All_steps"(default "All_steps")]
            [-1 Path of fastq1]
            [-2 Path of fastq2]
            [-o Output directory (default current directory)]
            [-n Output name]
            [-c Path of config file]
            [-t Maximum_threads]
            [-g Genome build version, "hg38" or "mm10"]
            [-s Site list file (No column name, only required when Function == "Variant_classification")]
            [-b BAM file (Only required when Function == "Variant_classification")]
            [-h show this help message and exit]
            [-v version for DEMINING]

3. Example

• Distinguish DNA and RNA mutations directly from RNA-seq fastq files

    ./DEMINING -f "All_steps" -1 Test_data/HG00145_chr22_R1.fastq.gz -2 Test_data/HG00145_chr22_R2.fastq.gz -o DEMINING_test -c Test_data/DEMINING_test.conf -n HG00145_chr22 -t 2 -g hg38
  

4. Output

DEMINING_test/
├── HG00145_chr22_DEMINING.tsv      # Predict result
└── HG00145_chr22_DEMINING_tmp      # Internal files of DEMINING 

• HG00145_chr22_DEMINING.tsv

  Field	Discription
  Site	Genomic coordinates
  DeepDDR_rawScore	Probability of RNA mutation from DEMINING
  DeepDDR_DM(DNA_mutation)_or_RM(RNA_mutation)	Predict label of site (DM: DNA mutation; RM: RNA mutation)

5. Citation

Fu, Z.C.#, Gao, B.Q.#, Nan, F., Ma, X.K., and Yang, L.* (2024). DEMINING: a deep learning model embedded framework to distinguish RNA editing from DNA mutations in RNA sequencing data.

6. License

Copyright ©2023 Fudan University. All Rights Reserved.

Licensed GPLv3 for open source use or contact YangLab ([email protected]) for commercial use.

Permission to use, copy, modify, and distribute this software and its documentation for educational, research, and not-for-profit purposes, without fee and without a signed licensing agreement, is hereby granted, provided that the above copyright notice in all copies, modifications, and distributions.

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.