SegPE使用文档
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SegPE使用文档
SegPE使用文档
飞书用户99985月21日修改
0x01 安装环境
安装Rust/Cargo
代码块
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
或者升级，推荐升级到1.87.0
代码块
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
代码块
[package.metadata.docs.rs]
features = ["simd_avx2"]
[target.'cfg(target_arch = "aarch64")'.dependencies]
block-aligner = { version = "0.5", features = ["simd_avx2"] }
编译：
代码块
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
代码块
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