{
 "tool": "mmseqs2_seqseq",
 "name": "MMseqs2",
 "kind": "aligns amino-acid letters",
 "compares": "Amino-acid letters: it first keeps target proteins that share similar short words with the query, then aligns only those, which makes it much faster than aligning every pair.",
 "needs": {
  "sequence only": true,
  "3D structure prediction": false,
  "GPU": false
 },
 "reference": "The relative's proteome (Quest for Orthologs reference proteomes, release 2020_04), as an MMseqs2 database.",
 "score": "Bit score: higher ranks first. The E-value cutoff was 10.",
 "failure_modes": [
  "At most 1,000 target proteins are kept per query (--max-seqs 1000), so a query from a very large family can lose hits. How often: not measured."
 ],
 "version": "MMseqs2 18.8cc5c",
 "licence": "MIT",
 "commercial_use": "Yes.",
 "licence_url": "https://github.com/soedinglab/MMseqs2",
 "container": "quay.io/biocontainers/mmseqs2:18.8cc5c--hd6d6fdc_0 (sha256:3503bfe576d560e550df2872af86a1ad1bcc1c06cfb7caadd3e7a95649f5f0ef)",
 "command": "mmseqs search \\\n    human-38fdd87d_mmdb/db zebrafish_mmdb/db result mmseqs_tmp \\\n    --threads 16 \\\n    -s 7 \\\n    --max-seqs 1000 \\\n    -e 10.0",
 "numbers_from": {
  "repo": "seanome/2024-kmerseek-analysis",
  "commit": "4a4b11714ddb740f8a7e324058b26bee8fb35af4",
  "filters": "pfam, raw, zebrafish"
 },
 "best_setting": "s7",
 "strong": [
  {
   "axis": "identity",
   "stratum": "40-60%",
   "fmax": 0.2488954726053097,
   "n": 563,
   "other_tool": "hmmer3_phmmer",
   "other_setting": "default",
   "other_fmax": 0.25193530617302773,
   "margin": -0.003039833567718031
  },
  {
   "axis": "plddt",
   "stratum": "90-100",
   "fmax": 0.47975974573333247,
   "n": 186,
   "other_tool": "mmseqs2_iterative",
   "other_setting": "s7",
   "other_fmax": 0.4844368729216556,
   "margin": -0.004677127188323138
  }
 ],
 "weak": [
  {
   "axis": "feature_length_bin",
   "stratum": "16-30",
   "fmax": 0.026877712663125667,
   "n": 271,
   "other_tool": "kmerseek",
   "other_setting": "wwmj5_k11_lcFalse",
   "other_fmax": 0.3297506857792661,
   "margin": -0.3028729731161404
  },
  {
   "axis": "feature_length_bin",
   "stratum": "31-60",
   "fmax": 0.089048513172538,
   "n": 420,
   "other_tool": "kmerseek",
   "other_setting": "gbmr4_k21_lcFalse",
   "other_fmax": 0.23209537155652643,
   "margin": -0.14304685838398845
  }
 ],
 "cost_per_1000_queries": {
  "core_h_reserved_per_relative": 0.02523565649818155,
  "n_relatives": 15,
  "database_build_core_h": 0.008888888888888889,
  "database_build_gpu_h": null,
  "peak_rss_gb": 1.1,
  "hardware": "Stanford Sherlock, SLURM partition hns"
 },
 "questions": [
  "Is the closest same-family domain in the relative you will search at least 40% identical, for most of your proteins? If yes, Fmax here is 40\u201360% 0.249 (n = 563), 60\u2013100% 0.297 (n = 1,289). If no, 20\u201330% 0.325 (n = 93), 30\u201340% 0.188 (n = 165). (Pfam truth set, raw calls, zebrafish (430 Mya) as the relative searched, setting sensitivity 7; subsets with at least 30 true instances.)",
  "Are the features you care about longer than 60 residues? If yes, Fmax here is 61\u2013120 aa 0.243 (n = 963), 121\u2013250 aa 0.305 (n = 504), 251 aa or more 0.462 (n = 277). If no, 16\u201330 aa 0.027 (n = 271), 31\u201360 aa 0.089 (n = 420). (Pfam truth set, raw calls, zebrafish (430 Mya) as the relative searched, setting sensitivity 7.)",
  "Can you spend about 0.0252 core-hours per 1,000 proteins for each relative you search? That is the measured mean per relative; see \"Cost per 1,000 queries\" below."
 ],
 "markdown": "mmseqs2_seqseq.md"
}