TRAINPHD(1)

💖 TRAINPHD — the manual page, bestie edition 💖

okay so you opened trainphd(1) and it's a User Commands situation, which means it's a real one, a genuine little utility living in section 1 of your man pages. no cap. let's get into it 🫶

✨ NAME ✨

trainphd — interpretation of DNA Sanger sequencing data 🧬🌸

like, it reads your sequencing data and makes sense of it. that's the whole vibe.

🎀 DESCRIPTION 🎀

okay bestie, this is where it gets juicy. trainphd is flag city. every single one of these is a little knob you can turn, so let's go one by one, no skipping, we don't do that here 💅

• -h — (Help) this message. the "help me please" button. iconic behaviour honestly 🙈
• -C <consensusfile> — tells it the name of the FASTA file that holds the consensus sequence. you're basically handing it the blueprint ✨
• -V <vector> — name of the FASTA file with the vector sequence. vectors get their own file, as they should 👑
• -P <primer> — name of the FASTA file with the primer sequence. primers are the little starters, love that for them 🧚
• -S <site> — name of the FASTA file with the restriction site sequence. 🍓
• -M <match> — the match premium. default is 10. when things match, it's a whole celebration 💖
• -X <mismatch> — the mismatch penalty. default is 20. mismatches get punished, sorry, it's giving strict 💀
• -G <gap_penalty > — the gap initiation or extension penalty. default is 40. gaps? penalised. heavily. 😭
• -r <repeat_fraction> — sets the repeat_fraction. default is 0.85. 🌈
• -f <max_frac_of_err> — the allowable fraction of errors inside the best alignment region. default is 0.1. and listen: if the actual fraction of errors goes over this value, the fragment gets rejected, meaning it is not used in the training process. so it doesn't just get a bad grade, it gets dropped entirely 🚫
• -a <min_portion_aligned> — tells trainphd to ignore a read if less than the specified portion of its bases is aligned with the reference sequence. default is 0. lowkey a "you must be at least this aligned to ride" situation 🎢
• -l <min_read_length> — tells trainphd to ignore any read shorter than the number of basepairs you give it. 0 by default, so by default nothing is too short. glow-up mode: set it higher ✂️
• -o <output_file> — name of the output file. and by default? the output goes to stdout, so it just vibes straight into your terminal 💻
• -t <tab_dir> — tells trainphd to extract alternative base calls from TAB files stored in the directory tab_dir, and to output those calls together with the quality value for each alternative call. extra data, extra slay 📊
• -d <dir> — read the input PHD files from the specified directory. point it at the folder, it goes and gets them 🗂️
• -j <projectfile> — name of the projectfile, which is made of two columns: the full path to the FASTA file containing the consensus sequence, then the full path to the sample file. two columns, one file, very efficient of it 📋

ngl some of these defaults are doing a lot of heavy lifting, so if your output looks weird, check -M, -X, -G, -r and -f first. that's where the algorithm's whole personality lives 🧠

💜 AUTHOR 💜

this manpage was written by Andreas Tille for the Debian distribution, and it can be used for any other usage of the program. so like, it's free to travel, we love a flexible icon 🫶

and that's the whole page, bestie!! 🎉 this was trainphd version 3.0.6~beta, dated October 2018 — a certified classic, still serving. go read your DNA, ily, bye 💅✨🌈