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توضیحات

Mutational Signature Simulation

ویژگی	مقدار
سیستم عامل	OS Independent
نام فایل	SomaticSiMu-3.0.0
نام	SomaticSiMu
نسخه کتابخانه	3.0.0
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	David Chen
ایمیل نویسنده	dchen362@uwo.ca
آدرس صفحه اصلی	https://github.com/HillLab/SomaticSiMu
آدرس اینترنتی	https://pypi.org/project/SomaticSiMu/
مجوز	-

# SomaticSiMu SomaticSiMu generates single and double base pair substitutions, and single base pair insertions and deletions of biologically representative mutation signature probabilities and combinations. SomaticSiMu_GUI is the GUI version of SomaticSiMu. ## Description Simulated genomes with imposed known mutational signatures associated with cancer can be useful for benchmarking machine learning-based classifiers of genomic sequences and finetuning model hyperparameters. SomaticSiMu extracts known signature data from reference signature data, generates novel mutations on an input sequence with respect to a series of user-specified parameters, and outputs the simulated mutated sequence as a machine readable FASTA file and metadata about the position, frequency and local sequence context of each mutation. The simulation can also model temporal directed evolution across early and late stages of 37 cancer types. SomaticSiMu is developed as a lightweight, stand alone, and massively parallel software tool with a graphical user interface, built in documentation and visualization functions of mutation signature plots. The rich selection of input parameters and graphical user interface make SomaticSiMu both an easy to use application and effective as part of a wide range of experimental scenarios. ## Installation SomaticSiMu is implemented in Python. As long as Python is installed on your system, SomaticSiMu should run directly on your system. $ git clone https://github.com/HillLab/SomaticSiMu\ ## File Structure ``` ├── DBS_Expected_Frequency ├── Documentation ├── Frequency_Table ├── ID_Expected_Frequency ├── Mutation_Metadata ├── Reference ├── Reference_genome ├── Sample ├── Signature_Combinations ├── kmer_ref_count │ ├── 1-mer │ ├── 2-mer │ ├── 3-mer │ ├── 4-mer │ ├── 5-mer │ ├── 6-mer ├── SomaticSiMu.py ├── SomaticSiMu_CC.py ``` ## Quick Start Simulate 100 sequences by imposing known mutation signatures associated with Biliary-AdenoCA onto the entire length of reference Human chromosome 22. ```python cd SomaticSiMu python SomaticSiMu_GUI.py Input Simulation Parameters: cancer_type = Biliary-AdenoCA reading_frame = 1 std_outlier = 3 number_of_lineages = 100 simulation_type = end sequence_abs_path = Homo_sapiens.GRCh38.dna.chromosome.22.fasta slice_start = 0 slice_end = 50818467 power=1 syn_rate=1 non_syn_rate=1 ``` ## Parameter List ```python "--generation", "-g", help="number of simulated sequences", default=10 "--cancer", "-c", help="cancer type" "--reading_frame", "-f", help="index start of reading frame", default=1 "--std", "-s", help="exclude signature data outside of n std from the mean", default=3 "--simulation_type", "-v", help="simulation type", default="end" "--slice_start", "-a", help="start of the slice of the input sequence, default=None (start at first base)" "--slice_end", "-b", help="end of the slice of the input sequence, default=None (end at first base)" "--power", "-p", help="multiplier of mutation burden from burden observed in in vivo samples", default=1 "--syn_rate", "-x", help="proportion of synonymous mutations out of all simulated mutations kept in the output simulated sequence", default=1 "--non_syn_rate", "-y", help="proportion of non-synonymous mutations out of all simulated mutations kept in the output simulated sequence", default=1 "--reference", "-r", help="full file path of reference sequence used as input for the simulation" ``` ## Output Sample: Simulated sequences output into directory named after the type of cancer simulated. Mutation_Metadata: CSV file output of each mutation simulated; the mutation type and index location on the reference input sequence. One file for each simulated sequence. Frequency_Table: CSV file output of summarized counts of each mutation type and local context. One file for each simulated sequence. Signature_Combinations: CSV file output of the signature combinations used for each iteration of the simulation. Different combinations of signatures are found operative in the same cancer type and are incorporated into the simulation. One file for each cancer type simulated. ## Contributing Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Please make sure to update tests as appropriate. ## License Creative Commons Creative Commons Attribution 4.0 International license ## PyPi Hosting https://pypi.org/project/SomaticSiMu/3.0.0/

نیازمندی

مقدار	نام
-	pandas
-	numpy
-	tqdm
-	pillow

زبان مورد نیاز

مقدار	نام
>=3.8	Python

نحوه نصب

نصب پکیج whl SomaticSiMu-3.0.0:

pip install SomaticSiMu-3.0.0.whl

نصب پکیج tar.gz SomaticSiMu-3.0.0:

pip install SomaticSiMu-3.0.0.tar.gz