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SemiBin宏基因组半监督分箱工具中GTDB数据的下载与配置_semibin用法

作者：小小林熬夜学编程 | 2024-04-30 19:39:33

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semibin用法

最近想学一学宏基因组的分箱工具使用（讲真的，感觉bin还是挺复杂的，不是我这种小白该去涉猎的），本来想看看老牌工具metaWRAP的使用细节，奈何微信推送了一条新的分箱工具——SemiBin，还是基于当下很热门的半监督+神经网络的模型构建的，感觉很新鲜，想尝尝鲜，于是就去SemiBin的github上学习一下基本用法：

GitHub - BigDataBiology/SemiBin

 该软件跟着install的引导去下载就可以了，还是比较简单，不过其中有几个较大的配置文件/软件要下载，望大家耐心等待。另外需要注意的是组装工具megahit，比对工具bowtie2以及samtools需要自己在SemiBin所在的环境中下载，具体的下载安装细节搬运一下github：

  1. # semibin的下载和安装
  2. conda create -n SemiBin
  3. conda activate SemiBin
  4. conda install -c conda-forge -c bioconda semibin
  5.  
  6. # 辅助semibin的软件下载
  7. conda install -c bioconda bowtie2
  8. conda install -c bioconda samtools
  9. conda install -c bioconda megahit
  10.  
  11. # 检查semibin是否安装好安装
  12. SemiBin check_install
  13.  
  14. # 出现下面这样就没什么问题了，表明安装成功：
  15.  
  16. Looking for dependencies...
  17.         bedtools        : /home/dell/miniconda3/envs/SemiBin/bin/bedtools
  18.         hmmsearch       : /home/dell/miniconda3/envs/SemiBin/bin/hmmsearch
  19.         mmseqs          : /home/dell/miniconda3/envs/SemiBin/bin/mmseqs
  20.         FragGeneScan    : /home/dell/miniconda3/envs/SemiBin/bin/FragGeneScan
  21.         prodigal        : /home/dell/miniconda3/envs/SemiBin/bin/prodigal
  22. Installation OK
  23. If you find SemiBin useful, please cite:
  24.  Pan, S., Zhu, C., Zhao, XM. et al. A deep siamese neural network improves metagenome-assembled genomes in microbiome datasets across different environments. Nat Commun 13, 2326 (2022). https://doi.org/10.1038/s41467-022-29843-y.

下载好后，就是实战了，从说明文档中看该软件的使用较为简单，应该是基于最理想的情况，我就以最简单的单样本、简单bin为例进行尝试：

实例文件可以在github上找：GitHub - BigDataBiology/SemiBin_tutorial_from_scratch

 点到single_sample_binning这个文件夹中，可见里面有一个样本的双端测序的文件

 ok，在linux端的操作是：

  1. # 1. 下载实例数据集，我是采用手动下载并上传的方式
  2.  
  3. # 2. cd到 single_sample_binning文件夹下
  4. cd single_sample_binning
  5.  
  6. # 3. 组装
  7. megahit -1 sample1_R1.fastq.gz \
  8. -2 sample1_R2.fastq.gz \
  9. --out-dir assembly_contig \
  10. --out-prefix R1
  11.  
  12. # 4. mapping 并进行binning前处理：
  13. bowtie2-build \
  14. -f assembly_contig/R1.contigs.fa assembly_contig/R1.contigs.fa
  15.  
  16. bowtie2 -q --fr \
  17. -x assembly_contig/R1.contigs.fa \
  18. -1 sample1_R1.fastq.gz \
  19. -2 sample1_R2.fastq.gz \
  20. -S sample1.sam \
  21. -p 64
  22.  
  23. samtools view -h -b -S sample1.sam -o sample1.bam -@ 64
  24.  
  25. samtools view -b -F 4 sample1.bam -o sample1.mapped.bam -@ 64
  26.  
  27. samtools sort \
  28. -m 1000000000 sample1.mapped.bam \
  29. -o sample1.mapped.sorted.bam -@ 64
  30.  
  31. # 5. Easy single binning mode 最简单的binning方式
  32.  
  33. SemiBin single_easy_bin \
  34. -i assembly_contig/R1.contigs.fa \
  35. -b sample1.mapped.sorted.bam \
  36. -o easy_single_sample_output 
  37.  
  38. # ========================================================
  39.  
  40. # 在这边出问题了：
  41. (SemiBin) dell 20:18:05 /home/DB/fqz/mydata/SemiBin_testdata/single_sample_binning
  42. $ SemiBin single_easy_bin \
  43. > -i assembly_contig/R1.contigs.fa \
  44. > -b sample1.mapped.sorted.bam \
  45. > -o easy_single_sample_output
  46.  
  47. 2022-08-25 20:19:36,299 - Setting number of CPUs to 112
  48. 2022-08-25 20:19:36,300 - Do not detect GPU. Running with CPU.
  49. 2022-08-25 20:19:36,315 - Generate training data.
  50. 2022-08-25 20:19:37,052 - Calculating coverage for every sample.
  51. 2022-08-25 20:19:37,057 - Processing `sample1.mapped.sorted.bam`
  52. 2022-08-25 20:19:37,805 - Processed:sample1.mapped.sorted.bam
  53. 2022-08-25 20:19:37,873 - Start generating kmer features from fasta file.
  54. 2022-08-25 20:19:39,087 - Running mmseqs and generate cannot-link file.
  55. 2022-08-25 20:19:39,149 - Downloading GTDB to /home/dell/.cache/SemiBin/mmseqs2-GTDB.  It will take a while..
  56.  
  57. # 第一使用该工具会下载软件依赖的GTDB数据库，由于放在外网所以下载速度很感人.....多次下载失败

直接使用SemiBin自带的数据库下载函数也不行，不过给了提示，该软件依赖的GTDB数据库使用的版本是v95：

 

所以，本次尝试主要遇到的问题就是SemiBin依赖的GTDB数据库下载总是失败，应该是外网限速的问题，我不会FQ，也没钱整DL，所以只能自己想办法，于是再次采用手动下载手动上传并安装GTDB v95版本的方式，首先去GTDB数据库的网站找v95版本，然后下载上传到 /home/dell/.cache/SemiBin/mmseqs2-GTDB 这个文件夹下，再次运行 SemiBin single_easy_bin 命令，结果文件被直接覆盖（即重新龟速下载），后来将手动下载的文件名命名成软件需要的名字，还是被覆盖，重复前述步骤，并将手动下载的GTDB数据库解压缩，还是被覆盖。所以得出的结论是这个文件可能不是SemiBin能够识别的文件，版本对，但是不能被识别，说明不是这个文件，同样还是中断龟速下载后，报错文件给了我提示：

 gtdb.py这个python脚本应该与下载GTBD数据库有关，于是去找github主页该文件的位置：

 

 还好作者在zenodo平台上留了一个GTDB数据库v95版本的备份，不然还真难搞

GTDB reference genome generated by MMseqs2 used in SemiBin. | Zenodo

 下载链接： https://zenodo.org/record/4751564/files/GTDB_v95.tar.gz?download=1

基于这个下载链接，使用迅雷，在保存到迅雷云盘之后本地下载的方式，我感觉比较快

下载完毕后，上传到指定位置（我的位置是~/.cache/SemiBin/mmseqs2-GTDB），然后解压缩！一定要解压缩，不然SemiBin还不识别然后将你的文件覆盖掉重新下载......

解压缩就随意了，我是使用pigz + tar的方式解压：

  1. pigz -d GTDB_v95.tar.gz
  2.  
  3. tar -xf GTDB_v95.tar
  4.  
  5. # 也可以直接 tar -zxvf GTDB_v95.tar.gz
  6.  
  7. # 验证一下是否已经下载好，semibin能够识别：
  8. SemiBin download_GTDB
  9.  
  10. 2022-08-25 20:36:01,669 - Found GTDB directory: `/home/dell/.cache/SemiBin/mmseqs2-GTDB`.
  11. If you find SemiBin useful, please cite:
  12.  Pan, S., Zhu, C., Zhao, XM. et al. A deep siamese neural network improves metagenome-assembled genomes in microbiome datasets across different environments. Nat Commun 13, 2326 (2022). https://doi.org/10.1038/s41467-022-29843-y.
  13.  
  14. # 可以继续了

查看解压后文件：

再次运行单样本简单binning，没有报错，一切正常了：

  1. (SemiBin) dell 20:36:42 /home/DB/fqz/mydata/SemiBin_testdata/single_sample_binning
  2. $ SemiBin single_easy_bin \
  3. > -i assembly_contig/R1.contigs.fa \
  4. > -b sample1.mapped.sorted.bam \
  5. > -o easy_single_sample_output
  6.  
  7. # 下面全是软件binning过程输出：
  8.  
  9. 2022-08-25 20:37:06,248 - Setting number of CPUs to 112
  10. 2022-08-25 20:37:06,249 - Do not detect GPU. Running with CPU.
  11. 2022-08-25 20:37:06,264 - Generate training data.
  12. 2022-08-25 20:37:06,920 - Calculating coverage for every sample.
  13. 2022-08-25 20:37:06,925 - Processing `sample1.mapped.sorted.bam`
  14. 2022-08-25 20:37:07,667 - Processed:sample1.mapped.sorted.bam
  15. 2022-08-25 20:37:07,721 - Start generating kmer features from fasta file.
  16. 2022-08-25 20:37:08,903 - Running mmseqs and generate cannot-link file.
  17. 2022-08-25 20:37:08,915 - Found GTDB directory: `/home/dell/.cache/SemiBin/mmseqs2-GTDB`.
  18. createdb /tmp/tmp5y44n4h6/SemiBinFiltered.fa /tmp/tmp5y44n4h6/contig_DB
  19.  
  20. MMseqs Version:         13.45111
  21. Database type           0
  22. Shuffle input database  true
  23. Createdb mode           0
  24. Write lookup file       1
  25. Offset of numeric ids   0
  26. Compressed              0
  27. Verbosity               3
  28.  
  29. Converting sequences
  30. [304] 0s 9ms
  31. Time for merging to contig_DB_h: 0h 0m 0s 19ms
  32. Time for merging to contig_DB: 0h 0m 0s 6ms
  33. Database type: Nucleotide
  34. Time for processing: 0h 0m 0s 45ms
  35. taxonomy /tmp/tmp5y44n4h6/contig_DB /home/dell/.cache/SemiBin/mmseqs2-GTDB/GTDB easy_single_sample_output/mmseqs_contig_annotation/mmseqs_contig_annotation /tmp/tmp5y44n4h6 --tax-lineage 1 --threads 112
  36.  
  37. MMseqs Version:                         13.45111
  38. ORF filter                              1
  39. ORF filter e-value                      100
  40. ORF filter sensitivity                  2
  41. LCA mode                                3
  42. Taxonomy output mode                    0
  43. Majority threshold                      0.5
  44. Vote mode                               1
  45. LCA ranks
  46. Column with taxonomic lineage           1
  47. Compressed                              0
  48. Threads                                 112
  49. Verbosity                               3
  50. Taxon blacklist                         12908:unclassified sequences,28384:other sequences
  51. Substitution matrix                     nucl:nucleotide.out,aa:blosum62.out
  52. Add backtrace                           false
  53. Alignment mode                          1
  54. Alignment mode                          0
  55. Allow wrapped scoring                   false
  56. E-value threshold                       1
  57. Seq. id. threshold                      0
  58. Min alignment length                    0
  59. Seq. id. mode                           0
  60. Alternative alignments                  0
  61. Coverage threshold                      0
  62. Coverage mode                           0
  63. Max sequence length                     65535
  64. Compositional bias                      1
  65. Max reject                              5
  66. Max accept                              30
  67. Include identical seq. id.              false
  68. Preload mode                            0
  69. Pseudo count a                          1
  70. Pseudo count b                          1.5
  71. Score bias                              0
  72. Realign hits                            false
  73. Realign score bias                      -0.2
  74. Realign max seqs                        2147483647
  75. Gap open cost                           nucl:5,aa:11
  76. Gap extension cost                      nucl:2,aa:1
  77. Zdrop                                   40
  78. Seed substitution matrix                nucl:nucleotide.out,aa:VTML80.out
  79. Sensitivity                             2
  80. k-mer length                            0
  81. k-score                                 2147483647
  82. Alphabet size                           nucl:5,aa:21
  83. Max results per query                   300
  84. Split database                          0
  85. Split mode                              2
  86. Split memory limit                      0
  87. Diagonal scoring                        true
  88. Exact k-mer matching                    0
  89. Mask residues                           1
  90. Mask lower case residues                0
  91. Minimum diagonal score                  15
  92. Spaced k-mers                           1
  93. Spaced k-mer pattern
  94. Local temporary path
  95. Rescore mode                            0
  96. Remove hits by seq. id. and coverage    false
  97. Sort results                            0
  98. Mask profile                            1
  99. Profile E-value threshold               0.001
  100. Global sequence weighting               false
  101. Allow deletions                         false
  102. Filter MSA                              1
  103. Maximum seq. id. threshold              0.9
  104. Minimum seq. id.                        0
  105. Minimum score per column                -20
  106. Minimum coverage                        0
  107. Select N most diverse seqs              1000
  108. Min codons in orf                       30
  109. Max codons in length                    32734
  110. Max orf gaps                            2147483647
  111. Contig start mode                       2
  112. Contig end mode                         2
  113. Orf start mode                          1
  114. Forward frames                          1,2,3
  115. Reverse frames                          1,2,3
  116. Translation table                       1
  117. Translate orf                           0
  118. Use all table starts                    false
  119. Offset of numeric ids                   0
  120. Create lookup                           0
  121. Add orf stop                            false
  122. Overlap between sequences               0
  123. Sequence split mode                     1
  124. Header split mode                       0
  125. Chain overlapping alignments            0
  126. Merge query                             1
  127. Search type                             0
  128. Search iterations                       1
  129. Start sensitivity                       4
  130. Search steps                            1
  131. Exhaustive search mode                  false
  132. Filter results during exhaustive search 0
  133. Strand selection                        1
  134. LCA search mode                         false
  135. Disk space limit                        0
  136. MPI runner
  137. Force restart with latest tmp           false
  138. Remove temporary files                  false
  139.  
  140. extractorfs /tmp/tmp5y44n4h6/contig_DB /tmp/tmp5y44n4h6/10505879959436434455/orfs_aa --min-length 30 --max-length 32734 --max-gaps 2147483647 --contig-start-mode 2 --contig-end-mode 2 --orf-start-mode 1 --forward-frames 1,2,3 --reverse-frames 1,2,3 --translation-table 1 --translate 1 --use-all-table-starts 0 --id-offset 0 --create-lookup 0 --threads 112 --compressed 0 -v 3
  141.  
  142. [=================================================================] 100.00% 392 0s 61ms
  143. Time for merging to orfs_aa_h: 0h 0m 0s 48ms
  144. Time for merging to orfs_aa: 0h 0m 0s 60ms
  145. Time for processing: 0h 0m 0s 299ms
  146. prefilter /tmp/tmp5y44n4h6/10505879959436434455/orfs_aa /home/dell/.cache/SemiBin/mmseqs2-GTDB/GTDB /tmp/tmp5y44n4h6/10505879959436434455/orfs_pref --sub-mat nucl:nucleotide.out,aa:blosum62.out --seed-sub-mat nucl:nucleotide.out,aa:VTML80.out -s 2 -k 0 --k-score 2147483647 --alph-size nucl:5,aa:21 --max-seq-len 65535 --max-seqs 1 --split 0 --split-mode 2 --split-memory-limit 0 -c 0 --cov-mode 0 --comp-bias-corr 1 --diag-score 0 --exact-kmer-matching 0 --mask 1 --mask-lower-case 0 --min-ungapped-score 3 --add-self-matches 0 --spaced-kmer-mode 1 --db-load-mode 0 --pca 1 --pcb 1.5 --threads 112 --compressed 0 -v 3
  147.  
  148. Query database size: 31958 type: Aminoacid
  149. Estimated memory consumption: 753G
  150. Target database size: 106052079 type: Aminoacid
  151. Index table k-mer threshold: 163 at k-mer size 7
  152. Index table: counting k-mers
  153. [=================================================================] 100.00% 106.05M 2m 3s 49ms
  154. Index table: Masked residues: 269144627
  155. Index table: fill
  156. [=================================================================] 100.00% 106.05M 2m 31s 544ms
  157. Index statistics
  158. Entries:          28079084193
  159. DB size:          170435 MB
  160. Avg k-mer size:   21.936785
  161. Top 10 k-mers
  162.     SGQQRIA     397575
  163.     GPGGKLL     319073
  164.     GGQRVAR     221105
  165.     YTGTGKG     177317
  166.     LSGQQAI     153681
  167.     GGRRVAR     125622
  168.     ALGNGKS     109876
  169.     LLGPGKT     107267
  170.     GRFVVEV     105507
  171.     TPHDFEV     88676
  172. Time for index table init: 0h 4m 54s 119ms
  173. Process prefiltering step 1 of 1
  174.  
  175. k-mer similarity threshold: 163
  176. Starting prefiltering scores calculation (step 1 of 1)
  177. Query db start 1 to 31958
  178. Target db start 1 to 106052079
  179. [=================================================================] 100.00% 31.96K 0s 537ms
  180.  
  181. 30.136279 k-mers per position
  182. 27916 DB matches per sequence
  183. 0 overflows
  184. 0 queries produce too many hits (truncated result)
  185. 0 sequences passed prefiltering per query sequence
  186. 0 median result list length
  187. 29412 sequences with 0 size result lists
  188. Time for merging to orfs_pref: 0h 0m 0s 21ms
  189. Time for processing: 0h 5m 16s 25ms
  190. rescorediagonal /tmp/tmp5y44n4h6/10505879959436434455/orfs_aa /home/dell/.cache/SemiBin/mmseqs2-GTDB/GTDB /tmp/tmp5y44n4h6/10505879959436434455/orfs_pref /tmp/tmp5y44n4h6/10505879959436434455/orfs_aln --sub-mat nucl:nucleotide.out,aa:blosum62.out --rescore-mode 2 --wrapped-scoring 0 --filter-hits 0 -e 100 -c 0 -a 0 --cov-mode 0 --min-seq-id 0 --min-aln-len 0 --seq-id-mode 0 --add-self-matches 0 --sort-results 0 --db-load-mode 0 --threads 112 --compressed 0 -v 3
  191.  
  192. [=================================================================] 100.00% 31.96K 0s 63ms
  193. Time for merging to orfs_aln: 0h 0m 0s 10ms=================>     ] 91.58% 29.27K eta 0s
  194. Time for processing: 0h 0m 5s 87ms
  195. createsubdb /tmp/tmp5y44n4h6/10505879959436434455/orfs_aln.list /tmp/tmp5y44n4h6/10505879959436434455/orfs_aa /tmp/tmp5y44n4h6/10505879959436434455/orfs_filter --subdb-mode 1 -v 3
  196.  
  197. Time for merging to orfs_filter: 0h 0m 0s 0ms
  198. Time for processing: 0h 0m 0s 22ms
  199. rmdb /tmp/tmp5y44n4h6/10505879959436434455/orfs_filter_h -v 3
  200.  
  201. Time for processing: 0h 0m 0s 2ms
  202. createsubdb /tmp/tmp5y44n4h6/10505879959436434455/orfs_aln.list /tmp/tmp5y44n4h6/10505879959436434455/orfs_aa_h /tmp/tmp5y44n4h6/10505879959436434455/orfs_filter_h --subdb-mode 1 -v 3
  203.  
  204. Time for merging to orfs_filter_h: 0h 0m 0s 0ms
  205. Time for processing: 0h 0m 0s 22ms
  206. Create directory /tmp/tmp5y44n4h6/10505879959436434455/tmp_taxonomy
  207. taxonomy /tmp/tmp5y44n4h6/10505879959436434455/orfs_filter /home/dell/.cache/SemiBin/mmseqs2-GTDB/GTDB /tmp/tmp5y44n4h6/10505879959436434455/orfs_tax /tmp/tmp5y44n4h6/10505879959436434455/tmp_taxonomy --tax-output-mode 2 --tax-lineage 0 --threads 112 --alignment-mode 1 -e 1 --max-rejected 5 --max-accept 30 -s 2 --spaced-kmer-mode 1 --min-length 30 --max-length 32734 --orf-start-mode 1
  208.  
  209. Create directory /tmp/tmp5y44n4h6/10505879959436434455/tmp_taxonomy/5836584711541975065/tmp_hsp1
  210. search /tmp/tmp5y44n4h6/10505879959436434455/orfs_filter /home/dell/.cache/SemiBin/mmseqs2-GTDB/GTDB /tmp/tmp5y44n4h6/10505879959436434455/tmp_taxonomy/5836584711541975065/first /tmp/tmp5y44n4h6/10505879959436434455/tmp_taxonomy/5836584711541975065/tmp_hsp1 --alignment-mode 1 -e 1 --max-rejected 5 --max-accept 30 --threads 112 -s 2 --spaced-kmer-mode 1 --min-length 30 --max-length 32734 --orf-start-mode 1 --lca-search 1
  211.  
  212. prefilter /tmp/tmp5y44n4h6/10505879959436434455/orfs_filter /home/dell/.cache/SemiBin/mmseqs2-GTDB/GTDB /tmp/tmp5y44n4h6/10505879959436434455/tmp_taxonomy/5836584711541975065/tmp_hsp1/10382565990596377146/pref_0 --sub-mat nucl:nucleotide.out,aa:blosum62.out --seed-sub-mat nucl:nucleotide.out,aa:VTML80.out -k 0 --k-score 2147483647 --alph-size nucl:5,aa:21 --max-seq-len 65535 --max-seqs 300 --split 0 --split-mode 2 --split-memory-limit 0 -c 0 --cov-mode 0 --comp-bias-corr 1 --diag-score 1 --exact-kmer-matching 0 --mask 1 --mask-lower-case 0 --min-ungapped-score 15 --add-self-matches 0 --spaced-kmer-mode 1 --db-load-mode 0 --pca 1 --pcb 1.5 --threads 112 --compressed 0 -v 3 -s 2.0
  213.  
  214. Query database size: 2531 type: Aminoacid
  215. Estimated memory consumption: 753G
  216. Target database size: 106052079 type: Aminoacid
  217. Index table k-mer threshold: 163 at k-mer size 7
  218. Index table: counting k-mers
  219. [=================================================================] 100.00% 106.05M 2m 4s 599ms
  220. Index table: Masked residues: 269144627
  221. Index table: fill
  222. [=================================================================] 100.00% 106.05M 2m 32s 452ms
  223. Index statistics
  224. Entries:          28079084193
  225. DB size:          170435 MB
  226. Avg k-mer size:   21.936785
  227. Top 10 k-mers
  228.     SGQQRIA     397575
  229.     GPGGKLL     319073
  230.     GGQRVAR     221105
  231.     YTGTGKG     177317
  232.     LSGQQAI     153681
  233.     GGRRVAR     125622
  234.     ALGNGKS     109876
  235.     LLGPGKT     107267
  236.     GRFVVEV     105507
  237.     TPHDFEV     88676
  238. Time for index table init: 0h 4m 54s 821ms
  239. Process prefiltering step 1 of 1
  240.  
  241. k-mer similarity threshold: 163
  242. Starting prefiltering scores calculation (step 1 of 1)
  243. Query db start 1 to 2531
  244. Target db start 1 to 106052079
  245. [=================================================================] 100.00% 2.53K 0s 910ms
  246.  
  247. 31.980804 k-mers per position
  248. 170052 DB matches per sequence
  249. 0 overflows
  250. 0 queries produce too many hits (truncated result)
  251. 235 sequences passed prefiltering per query sequence
  252. 300 median result list length
  253. 0 sequences with 0 size result lists
  254. Time for merging to pref_0: 0h 0m 0s 7ms
  255. Time for processing: 0h 5m 20s 93ms
  256. lcaalign /tmp/tmp5y44n4h6/10505879959436434455/orfs_filter /home/dell/.cache/SemiBin/mmseqs2-GTDB/GTDB /tmp/tmp5y44n4h6/10505879959436434455/tmp_taxonomy/5836584711541975065/tmp_hsp1/10382565990596377146/pref_0 /tmp/tmp5y44n4h6/10505879959436434455/tmp_taxonomy/5836584711541975065/first --sub-mat nucl:nucleotide.out,aa:blosum62.out -a 0 --alignment-mode 1 --alignment-output-mode 0 --wrapped-scoring 0 -e 1 --min-seq-id 0 --min-aln-len 0 --seq-id-mode 0 --alt-ali 0 -c 0 --cov-mode 0 --max-seq-len 65535 --comp-bias-corr 1 --max-rejected 5 --max-accept 30 --add-self-matches 0 --db-load-mode 0 --pca 1 --pcb 1.5 --score-bias 0 --realign 0 --realign-score-bias -0.2 --realign-max-seqs 2147483647 --gap-open nucl:5,aa:11 --gap-extend nucl:2,aa:1 --zdrop 40 --threads 112 --compressed 0 -v 3
  257.  
  258. Compute score only
  259. Query database size: 2531 type: Aminoacid
  260. Target database size: 106052079 type: Aminoacid
  261. [=================================================================] 100.00% 2.53K 0s 737ms
  262. Time for merging to first: 0h 0m 0s 7ms
  263. 59140 alignments calculated
  264. 54382 sequence pairs passed the thresholds (0.919547 of overall calculated)
  265. 21.486368 hits per query sequence
  266. Time for processing: 0h 0m 7s 61ms
  267. lca /home/dell/.cache/SemiBin/mmseqs2-GTDB/GTDB /tmp/tmp5y44n4h6/10505879959436434455/tmp_taxonomy/5836584711541975065/first /tmp/tmp5y44n4h6/10505879959436434455/orfs_tax --blacklist '12908:unclassified sequences,28384:other sequences' --tax-lineage 0 --compressed 0 --threads 112 -v 3
  268.  
  269. Node name 'unclassified sequences' does not match to be blocked name 'RBG-16-66-30'
  270. Node name 'other sequences' does not match to be blocked name 'B14-G1 sp003648675'
  271. [=================================================================] 100.00% 2.53K 0s 28ms
  272. Taxonomy for 0 out of 13195 entries not found
  273. Time for merging to orfs_tax: 0h 0m 0s 16ms
  274. Time for processing: 0h 0m 3s 758ms
  275. mvdb /tmp/tmp5y44n4h6/10505879959436434455/tmp_taxonomy/5836584711541975065/first /tmp/tmp5y44n4h6/10505879959436434455/orfs_tax_aln -v 3
  276.  
  277. Time for processing: 0h 0m 0s 2ms
  278. swapdb /tmp/tmp5y44n4h6/10505879959436434455/orfs_filter_h /tmp/tmp5y44n4h6/10505879959436434455/orfs_h_swapped --split-memory-limit 0 --threads 112 --compressed 0 -v 3
  279.  
  280. [=================================================================] 100.00% 2.53K 0s 12ms
  281. Computing offsets.
  282. [=================================================================] 100.00% 2.53K 0s 3ms
  283.  
  284. Reading results.
  285. [=================================================================] 100.00% 2.53K 0s 5ms
  286.  
  287. Output database: /tmp/tmp5y44n4h6/10505879959436434455/orfs_h_swapped
  288. [=================================================================] 100.00% 392 0s 105ms
  289.  
  290. Time for merging to orfs_h_swapped: 0h 0m 0s 3ms
  291. Time for processing: 0h 0m 0s 177ms
  292. aggregatetaxweights /home/dell/.cache/SemiBin/mmseqs2-GTDB/GTDB /tmp/tmp5y44n4h6/10505879959436434455/orfs_h_swapped /tmp/tmp5y44n4h6/10505879959436434455/orfs_tax /tmp/tmp5y44n4h6/10505879959436434455/orfs_tax_aln easy_single_sample_output/mmseqs_contig_annotation/mmseqs_contig_annotation --tax-lineage 1 --compressed 0 --threads 112 -v 3
  293.  
  294. [=================================================================] 100.00% 392 0s 26ms
  295. Time for merging to mmseqs_contig_annotation: 0h 0m 0s 6ms
  296. Time for processing: 0h 0m 0s 143ms
  297. createtsv /tmp/tmp5y44n4h6/contig_DB easy_single_sample_output/mmseqs_contig_annotation/mmseqs_contig_annotation easy_single_sample_output/mmseqs_contig_annotation/taxonomyResult.tsv
  298.  
  299. MMseqs Version:                         13.45111
  300. First sequence as representative        false
  301. Target column                           1
  302. Add full header                         false
  303. Sequence source                         0
  304. Database output                         false
  305. Threads                                 112
  306. Compressed                              0
  307. Verbosity                               3
  308.  
  309. Time for merging to taxonomyResult.tsv: 0h 0m 0s 4ms
  310. Time for processing: 0h 0m 0s 133ms
  311. 2022-08-25 20:48:02,164 - Training model and clustering.
  312. 2022-08-25 20:48:02,165 - Start training from one sample.
  313. 2022-08-25 20:48:02,272 - Training model...
  314.   0%|                                                                                                                 | 0/20 [00:00<?, ?it/s]2022-08-25 20:48:10,698 - Generate training data of 0:
  315. 2022-08-25 20:48:10,739 - Number of must link pair:163
  316. 2022-08-25 20:48:10,739 - Number of can not link pair:9394
  317. 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████| 20/20 [00:22<00:00,  1.14s/it]
  318. 2022-08-25 20:48:25,037 - Training finished.
  319. 2022-08-25 20:48:25,049 - Start binning.
  320. 2022-08-25 20:48:28,352 - Calculating depth matrix.
  321. 2022-08-25 20:48:28,366 - Edges:9962
  322. 2022-08-25 20:48:33,595 - Reclustering.
  323. 2022-08-25 20:48:45,490 - Binning finish.
  324. If you find SemiBin useful, please cite:
  325.  Pan, S., Zhu, C., Zhao, XM. et al. A deep siamese neural network improves metagenome-assembled genomes in microbiome datasets across different environments. Nat Commun 13, 2326 (2022). https://doi.org/10.1038/s41467-022-29843-y.

ok ，我有一个问题，不知道大家有没有解决办法，就是可不可以将这个数据库放到别的地方，然后semibin通过一个函数调用该位置的GTDB数据？希望本帖对大家有帮助！

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