Demultiplex_practice

A Python script for demultiplexing sequencing reads, implemented as a learning project.

Note: The efficiency of the implementation could be significantly lower than that of widely used software.

What is demultiplexing?

It is the process of separating mixed sequencing reads from a single file into separate files for each individual sample, using unique index sequences attached to each sample to assign reads to their original source.

Installation

1. Install dependencies

I used some pre-built libraries for convenience rather than building everything from scratch, such as Biopython and RapidFuzz. These libraries help a lot with tasks like reading raw reads and matching index.

pip install -r requirements.txt

2. Local package installs

pip install -e .

Usage

Single-end

from demux import SingleEndDemux

demux = SingleEndDemux(
    index_path = "/path/to/index.txt",
    raw_path = "/path/to/rawdata.fastq.gz",
    save_dir = "/path/to/save/dir/",
    pr = "PRIMER",
    allow_mismatch = 0,
    threads = None,
    read_direction = "forward",
    dry = False
)

index_path: Path to index .TXT file, format: SAMPLE_ID<tab>INDEX

raw_path: Path to raw .FASTQ.GZ file.

save_dir: The directory to save demultiplexed .FASTQ.GZ file.

pr: The primer sequence after the index. Default is "GTCGGTAAAACTCGTGCCAGC"(MiFish-UF).

allow_mismatch: Allow mismatch for barcode matching. Default is 0.

threads: Number of CPU cores to be used for processing. If not specified, maximum number of available cores will be used. Default is None.

read_direction: forward or reverse. Default is "forward".

dry: Dry run. If True, no files will be written; only a demultiplexed report will be output. Default is False.

Paired-end

from demux import PairedEndDemux

demux = PairedEndDemux(
    index_path = "/path/to/index.txt",
    for_raw_path = "/path/to/rawdata_R1.fastq.gz",
    rev_raw_path = "/path/to/rawdata_R2.fastq.gz",
    save_dir = "/path/to/save/dir/",
    pr_5 = "FORWARD_PRIMER",
    pr_3 = "REVERSE_PRIMER",
    allow_mismatch = 0,
    threads = None,
    dry = False
)

index_path: Path to index .TXT file, format: SAMPLE_ID<tab>FORWARD_INDEX<tab>REVERSE_INDEX

for_raw_path: Path to raw _R1.FASTQ.GZ file.

rev_raw_path: Path to raw _R2.FASTQ.GZ file.

pr_5: The forward primer sequence after the forward index. Default is "GTCGGTAAAACTCGTGCCAGC"(MiFish-UF).

pr_3: The reverse primer sequence after the reverse index. Default is "CATAGTGGGGTATCTAATCCCAGTTTG"(MiFish-UR).

Example

You can use the example.ipynb notebook and the materials in the example folder to practice.