0x01 安装环境

安装Rust/Cargo

curl --proto '=https' --tlsv1.2 -sSf <https://sh.rustup.rs> | sh

或者升级，推荐升级到1.87.0

rustup update stable

0x02 编译

已编译可多平台/跨平台使用

因为用到了SIMD加速，所以在不同CPU上会有差异：

在Intel/AMD x86 架构CPU上

修改Cargo.toml

[package.metadata.docs.rs]
features = ["simd_avx2"]

[target.'cfg(target_arch = "aarch64")'.dependencies]
block-aligner = { version = "0.5", features = ["simd_avx2"] }

编译：

cargo build --features simd_avx2 --release

理论上只要内存吃得消读入FASTQ或线程数 * batch_reads所需要的内存，不必担心内存溢出的问题，因此可以尽可能大量使用线程数处理。

0x03 CLI 命令参数说明

Algorithmic ideas of SegPE:
    - Exact match search: This is a more direct method for finding exact matches of artificial sequences.
    Regular expression matching and Hamming distance:
    This is suitable for detecting and locating index sequences, especially when mismatches of a certain length are taken into account.

    - Process and classify PE/SE sequences: After removing the adapter and index sequences, classify the PE/SE sequences and create new PE/SE FASTQ files.

    - Remove low-quality reads: This is a common step in bioinformatics to ensure that the data used for analysis is of high quality.

    - Use Multi-threads, SIMD and AsyncIO to handle large amounts of data.
    

Usage: segpe [OPTIONS] --five-art-fa <FIVE_ART_FA> --three-art-fa <THREE_ART_FA> --five-idx-fa <FIVE_IDX_FA> --pe1-fastq <PE1_FASTQ>

Options:
      --five-art-fa <FIVE_ART_FA>
          Path of 5' artificial fasta file

      --three-art-fa <THREE_ART_FA>
          Path of 3' artificial fasta file

      --five-idx-fa <FIVE_IDX_FA>
          Path of 5‘ index fasta file

      --three-idx-fa <THREE_IDX_FA>
          Path of 3’ index fasta file
          
          [default: ]

      --idx-loc <IDX_LOC>
          Location of index, 1: PE1 2: PE2 3: both
          
          [default: 1]

      --pe1-fastq <PE1_FASTQ>
          Path of PE1 fastq file

      --pe2-fastq <PE2_FASTQ>
          Path of PE1 fastq file
          
          [default: ]

  -s, --seed-len <SEED_LEN>
          Number of seed length, not allow to longer than index length
          
          [default: 6]

      --merge-pe
          Merged overlapped PE

      --error-tolerance <ERROR_TOLERANCE>
          Number of error tolerance
          
          [default: 1]

  -m, --match-score <MATCH_SCORE>
          Number of alignment macth score
          
          [default: 1]

      --error-score <ERROR_SCORE>
          Number of alignment mismacth score
          
          [default: -1]

      --gap-open-score <GAP_OPEN_SCORE>
          Number of alignment gap open score
          
          [default: -5]

      --gap-extend-score <GAP_EXTEND_SCORE>
          Number of alignment gap extend score
          
          [default: -1]

      --qual-trim <QUAL_TRIM>
          Low quality pruning threshold (Phred score, automatic ASCII recognition), no pruning if not set
          
          [default: 0]

      --quality-ascii-offset <QUALITY_ASCII_OFFSET>
          quality ASCII offset
          
          [default: 33]

      --n-trim
          Whether to trim N/non-ACGT at both ends

      --length-offset <LENGTH_OFFSET>
          The minimum retention length after removing low quality values. If it is shorter than this length, it will be classified as low quality
          
          [default: 50]

      --poly-trim <POLY_TRIM>
          Whether to trim poly-A/C/G/T at both ends
          
          [default: 0]

  -n, --num-threads <NUM_THREADS>
          Number of cucurrency threads
          
          [default: 8]

  -b, --batch <BATCH>
          batch size of reads, which every thread need to handle
          
          [default: 10000]

      --train <TRAIN>
          pretrain size of reads
          
          [default: 0]

      --trim-name
          add trim info in reads_name

  -o, --outdir <OUTDIR>
          Path of output directory
          
          [default: ./]

  -h, --help
          Print help (see a summary with '-h')

  -V, --version

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0x04 准备数据