Metadata-Version: 1.1
Name: baseqDrops
Version: 2.0
Summary: Processing Drop-seq, 10X(3prime) and inDrop RNA-seq dataset
Home-page: https://gene.pku.edu.cn
Author: Xiannian Zhang
Author-email: friedpine@gmail.com
License: UNKNOWN
Description: # baseqDrops
        A versatile pipeline for processing dataset from 10X, indrop and Drop-seq.
        
        ## Install baseqDrops
        We need python3 and a package called: baseqDrops, which could be installed by:
        
            pip install baseqDrops
        
        After install, you will have a runnable command `baseqDrops`
        
        It is recommend for the computer or server to have memory >= 30Gb and CPU cores >=8 for efficient processing;
        
        ## Configuration file
        
        The following software or resources are required:
        
        + `star`: STAR software, for fast alignment of RNA-Seq data to the genome;
        + `samtools`: For sorting the aligned bam file (version >=1.6);
        + `whitelistDir`: The barcode whitelist files for indrop and 10X should be placed under whitelistDir. These files could bed downloaded from https://github.com/beiseq/baseqDrops/tree/master/whitelist;
        + `cellranger_ref_<genome>`: The key process of read alignment and tagging to genes are inspired and borrowed from the open source cellranger pipeline(https://github.com/10XGenomics/cellranger). The references of genome index and transcriptome can be downloaded from https://support.10xgenomics.com/single-cell-gene-expression/software/downloads/latest.
        In the config file, the directory of cellranger references is named as `cellranger_<genome>`.
        
        While running command, the configures are recorded in the file called `config_drops.ini`:
        
            [Drops]
            samtools = /path/to/samtools
            star = /path/to/STAR
            whitelistDir = /path/to/whitelist_file_directory
            cellranger_ref_hg38 = /path/to/reference/refdata-cellranger-GRCh38-1.2.0/
        
        ## For Help Informations
        	
        	baseqDrops run-pipe --help
        
        ## Process Steps
        
        1. `Cell Barcode Counting`: Counting the existed barcodes in dataset. This will generate a file named: barcode_count_<sample>.csv;
        2. `Cell Barcode Correction, Aggregating and Filtering`: Correcting the cell barcodes within 1bp mismatch and then aggregating, filtering the barcode by minimum number of reads (default 5000), this will generate a valid barcode list named: barcode_stats_<sample>.csv;
        3. `Split the Reads of Valid Cell Barcodes`: The raw pair-end raw reads are splitted to 16 single-end files for multiprocessing according to the 2bp prefix of the barcode; The folder of barcode_splits contains files like: split.<sample>.<AA|AT|AC|AG...|GG>.fq;
        4. `Alignment to Genome using STAR`: Several (defined by --parallel/-p) STAR programs run at the same time, the results will be at folder named as star_align; The bam files are further sorted by sequence header;
        5. `Reads Tagging`: Tagging the reads alignment position to the corresponding gene name;
        6. `Generating Expression Table`: Both the expression table quantified by UMI (Result.UMIs.<sample>.txt) and raw read count (Result.Reads.<sample>.txt) will be generated;
        
        ## Run Pipeline
        
        These parameters should be provided: (or run: baseqDrops run-pipe --help for information)
        
        + `--outdir/-d`: Output path (default ./, the result will be stored in ./<name>);
        + `--config`: Path to the config file;
        + `--genome/-g`: Genome version [hg38/mm38/hgmm];
        + `--protocol/-p`: [10X|indrop|dropseq];
        + `--minreads`:  Minimum reads required for a barcode;
        + `--name/-n` : Name of sample, a folder of <outdir>/<name> will be created and be the main directory; 
        + `--parallel` : The number of STAR and tagging processes runs at the same time (default is 4, need more memory for larger parallel number); 
        + `--fq1/-1`: Path of Pair-end 1 sequencing file;
        + `--fq2/-2`: Path of Pair-end 2 sequencing file;
        + `--top_million_reads`: For huge dataset, you can choose to use part of the data for a quick look, the reads exceeding N million of reads will be skipped;
        
        If your data is human origin and `cellranger_ref_hg38` has been defined in configuration file, you can run:
        
            baseqDrops run-pipe --config ./config_drops.ini -g hg38 -p 10X --minreads 1000 -n 10X_test -1 10x_1.1.fq.gz -2 10x.2.fq.gz -d ./
        
        ## Run by Single Steps
        
        We also provide step-wise ways for running the pipeline, all the parameters should be provided as described above, an extra "--step" should be provided, for example:
        	
        	baseqDrops run-pipe --config ./config.ini -g hg38 -p dropseq --minreads 1000 -n dropseq2 --top_million_reads 20 -1 dropseq_1.1.fq.gz -2 dropseq.2.fq.gz --step count -d ./
        
        The steps are listed:
        
        + `Cell Barcode Counting`:  --step count
        + `Cell Barcode Correction, Aggregating and Filtering`: --step stats
        + `Split the Reads of Valid Cell Barcodes`: --step split
        + `Alignment to Genome using STAR`: --step star
        + `Reads Tagging` : --step tagging
        + `Generating Expression Table`: --step table
        
        ## Contact
        
        For any questions, please email to: friedpine@gmail.com
        
Keywords: sample setuptools development
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
