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deepnano-blitz:非常快的ONT基本呼叫者
共77个文件
fast5:48个
rs:8个
txt:6个
需积分: 9 0 下载量 148 浏览量
2021-05-05
06:12:13
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超快速ONT呼叫者 这是一个非常快的基本选择器,它可以像普通笔记本电脑上的MinION一样快速地进行基本调用读取。 如果您觉得这项工作有用,请引用(即将发布有关他的更新的预印本): 局限性 仅在64位linux上进行了测试(外部各方使其可在MacOS上运行,请参见下文)。 现在只有R9.4.1。 建议在AMD CPU上使用: export MKL_DEBUG_CPU_TYPE=5 您需要python3(经过python 3.9测试)。 PyO3包至少需要python3.5。 在某些情况下,您可能需要export OMP_NUM_THREADS=1 安装方式 安装Rust(编程语言,而不是游戏语言,此外您应该已经拥有;))。 您可以在此处查看说明: : curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs |
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收起资源包目录
deepnano-blitz-master.zip (77个子文件)
deepnano-blitz-master
deepnano2
gpu_model.py 1KB
__init__.py 25B
weights
rnn256.txt 21.63MB
weightsbig520.pt 9.11MB
rnn56.txt 749KB
rnn64.txt 970KB
rnn80.txt 1.46MB
rnn48.txt 556KB
rnn96.txt 2.09MB
.gitignore 7B
README.md 10KB
Cargo.toml 489B
LICENSE 1KB
test_sample
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch106_read1668_strand.fast5 700KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch109_read2117_strand.fast5 245KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch106_read1476_strand.fast5 164KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch102_read3746_strand.fast5 154KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch10_read142_strand.fast5 150KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch10_read2958_strand.fast5 333KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch106_read2020_strand.fast5 484KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch107_read1818_strand.fast5 269KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch106_read2899_strand.fast5 269KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch106_read2364_strand.fast5 277KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch107_read1769_strand.fast5 101KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch109_read3428_strand.fast5 256KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch100_read3899_strand.fast5 267KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch109_read5337_strand.fast5 182KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch104_read2263_strand.fast5 397KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch10_read1418_strand.fast5 124KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch109_read1428_strand.fast5 101KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch108_read1260_strand.fast5 586KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch100_read1644_strand.fast5 294KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch100_read3576_strand.fast5 146KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch101_read7336_strand.fast5 132KB
expected.fastq 1.89MB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch100_read2767_strand.fast5 102KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch100_read1603_strand.fast5 222KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch103_read2127_strand.fast5 143KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch107_read4185_strand.fast5 266KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch106_read2535_strand.fast5 586KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch102_read310_strand.fast5 163KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch106_read1576_strand.fast5 199KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch106_read1362_strand.fast5 142KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch105_read2445_strand.fast5 139KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch102_read1700_strand.fast5 122KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch107_read3515_strand.fast5 185KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch106_read3235_strand.fast5 117KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch103_read2164_strand.fast5 213KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch10_read2398_strand.fast5 227KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch108_read1798_strand.fast5 106KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch106_read926_strand.fast5 757KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch102_read1511_strand.fast5 320KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch101_read6819_strand.fast5 117KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch102_read3217_strand.fast5 113KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch101_read7106_strand.fast5 344KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch107_read3487_strand.fast5 103KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch10_read6191_strand.fast5 166KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch106_read1722_strand.fast5 533KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch100_read3421_strand.fast5 182KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch102_read3384_strand.fast5 104KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch105_read2568_strand.fast5 133KB
5210_N125509_20170424_FN2002039725_MN19691_sequencing_run_klebs_033_75349_ch103_read854_strand.fast5 206KB
dist
deepnano2-0.1-cp36-cp36m-linux_x86_64.whl 39.51MB
build.rs 1KB
src
models.rs 17KB
matrix_load.rs 2KB
lib.rs 5KB
approx.rs 1KB
conv_layer.rs 3KB
beam_search.rs 4KB
gru_layer.rs 5KB
scripts
deepnano2_caller.py 6KB
deepnano2_caller_gpu.py 6KB
MANIFEST.in 43B
pyproject.toml 69B
setup.py 1KB
Cargo.lock 10KB
共 77 条
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