This page shows what each SEGUL feature does with your data. Each diagram uses a small example; the same rules apply to datasets with thousands of loci. Under each feature, the guide links open its step-by-step instructions for the GUI, CLI, and Python API, or say when an interface does not support it yet. The Rust and R APIs use the SEGUL library directly.
SEGUL groups its features by the kind of input they take. In the GUI, each group is a button in the navigation bar or rail. In the CLI, each group is a command.
SEGUL task groups Three task groups. Alignments takes aligned files or partitions and offers concatenation, conversion, distance, filtering, partition conversion, splitting, summary, trimming, and unalignment. Genomic takes FASTQ reads, FASTA contigs, or MAF whole-genome alignments and offers read and contig summaries plus MAF conversion and summary. Sequences takes aligned or unaligned files and offers addition, ID extraction, mapping, renaming, sequence extraction, filtering, removal, translation, and transposition. Alignments Input Aligned files or partitions Concatenation Conversion Distance Filtering Partition conversion Splitting Summary Trimming Unalignment segul align … Genomic Input Reads, contigs, or MAF Sequence read summary Contig summary MAF conversion MAF summary segul read|contig|maf … Sequences Input Aligned or unaligned files Addition ID extraction ID mapping ID renaming Extraction Filtering Removal Translation Transposition segul sequence … Each task group is a button in the GUI navigation and a command group in the CLI. The CLI splits the genomic group into three commands: read for FASTQ files, contig for FASTA contigs, and maf for Multiple Alignment Format (MAF) files. The GUI keeps all three in one group.
Alignment tasks need alignments : every sequence in a file has the same length. Partition conversion is the exception and takes partition files, such as RAxML or NEXUS partitions. SEGUL checks only lengths, so it cannot detect misaligned sequences that happen to share a length.
Sequence tasks take aligned or unaligned files and do not check lengths. The documentation calls these standard sequence files .
Aligned and unaligned sequences An aligned file has three sequences that are all ten characters long, using gaps to fill the difference. The same sequences unaligned have no gaps and lengths of eight, ten, and nine. Alignment tasks need aligned input; sequence tasks accept both. Aligned seq1 A G T C C C C A - - seq2 A G T C C C C A A T seq3 A G T C - C C T T A Every row has 10 sites; gaps (–) pad shorter ones. ✓ Alignment tasks ✓ Sequence tasks Unaligned seq1 A G T C C C C A seq2 A G T C C C C A A T seq3 A G T C C C T T A Rows can differ in length. ✓ Sequence tasks Alignment tasks need every sequence in a file to have the same length. Sequence tasks accept either kind. SEGUL accepts many input files at once. Alignment Splitting is the exception: it takes one concatenated alignment.
Supported file extensions Alignment and sequence tasks read NEXUS (.nex, .nexus, .nxs), FASTA (.fasta, .fa, .fna, .fsa, .fas), and relaxed PHYLIP (.phy, .phylip, .ph). Genomic tasks read FASTQ reads (.fastq, .fq, .fastq.gz, .fq.gz), FASTA contigs (.fasta, .fa, .fna, .fsa, .fas, and gzipped such as .fasta.gz), MAF whole-genome alignments (.maf, .maf.gz), and BED loci for MAF conversion (.bed, .bed.gz). Alignment and sequence tasks NEXUS .nex .nexus .nxs FASTA .fasta .fa .fna .fsa .fas Relaxed PHYLIP .phy .phylip .ph Genomic tasks Reads .fastq .fq .fastq.gz .fq.gz Contigs .fasta .fa .fna .fsa .fas .fasta.gz MAF .maf .maf.gz BED loci .bed .bed.gz Compressed files end in .gz. SEGUL reads them directly, without decompressing them first. :::note SEGUL supports relaxed PHYLIP, not strict PHYLIP. Strict PHYLIP limits sample names to 10 characters and splits sequences into blocks with spaces:
Seq1 ATCGATCGAT ATCGATCGAT
Seq2 ATCGATCGAT ATCGATCGAT
Seq3 ATCGATCGAT ATCGATCGAT
Relaxed PHYLIP allows longer names and writes each sequence without spaces:
genus_species_museumNo1 ATCGATCGATATCGATCGAT
genus_species_museumNo2 ATCGATCGATATCGATCGAT
genus_species_museumNo3 ATCGATCGATATCGATCGAT
:::
Joins many alignments into one and writes a partition that records where each locus starts and ends. Sequences are matched by sample name, so a typo or inconsistent name leaves a sequence unmatched.
Alignment concatenation locus_1 has 10 sites and locus_2 has 8 sites for samples seq1 to seq3. Concatenation joins each sample's sequences into one 18-site alignment, with locus_1 at sites 1 to 10 and locus_2 at sites 11 to 18, and writes the partition in RAxML or NEXUS format. locus_1 seq1 A G T C C C C A - - seq2 A G T C C C C A A T seq3 A G T C - C C T T A locus_2 seq1 G G C T A A - T seq2 G G C T A A C T seq3 G G - T A A C T concatenate concatenated seq1 A G T C C C C A - - G G C T A A - T seq2 A G T C C C C A A T G G C T A A C T seq3 A G T C - C C T T A G G - T A A C T locus_1 = 1–10 locus_2 = 11–18 Plus a partition file in the format you choose: RAxML partition DNA, locus_1 = 1-10 DNA, locus_2 = 11-18 NEXUS partition #NEXUS begin sets; charset locus_1 = 1-10; charset locus_2 = 11-18; end; Rows are matched by sample name, and loci are joined in alphanumeric order. Changes the file format of alignments.
Alignment conversion A batch of FASTA files such as locus_1.fasta is converted to NEXUS as locus_1.nex or to relaxed PHYLIP as locus_1.phy. File names stay the same; only the format and extension change. locus_1.fasta FASTA convert locus_1.nex NEXUS locus_1.phy Relaxed PHYLIP Converts one file or a whole folder. Output can be NEXUS, relaxed PHYLIP, or FASTA, sequential or interleaved. Computes pairwise genetic distances between samples in each alignment. Optionally averages the distances within and between populations or species, using groups from sample names, a regular expression, or a group file, and writes all distances as long tables.
Guides → → not yet supported Alignment distance Four aligned samples are compared pair by pair to give a 4 by 4 matrix of p-distances. seq1: 0.00, 0.10, 0.33, 0.50; seq2: 0.10, 0.00, 0.22, 0.40; seq3: 0.33, 0.22, 0.00, 0.22; seq4: 0.50, 0.40, 0.22, 0.00. Supported models are p-distance, JC69, K2P, TN93, and Poisson for amino acids. locus_1 seq1 A G T C C C C A T A seq2 A G T C C G C A T A seq3 A G T A C G C T T - seq4 G G T A C G T T T A compare p-distance seq1 seq2 seq3 seq4 0.00 0.10 0.33 0.50 0.10 0.00 0.22 0.40 0.33 0.22 0.00 0.22 0.50 0.40 0.22 0.00 seq1 seq2 seq3 seq4 Models p-distance JC69 K2P TN93 Poisson (amino acid) Gaps and missing or ambiguous sites are skipped for each pair. SEGUL writes one matrix per locus and a summary table. Keeps the alignments that meet a criterion and drops the rest.
Alignment filtering With a minimum length of 500 bp, locus_1 (1240 bp) is kept, locus_2 (380 bp) is removed, locus_3 (860 bp) is kept, locus_4 (450 bp) is removed, locus_5 (1020 bp) is kept. Other criteria are matrix completeness, parsimony-informative sites, missing data, minimum taxa, and taxon ID. Example: minimum alignment length 500 bp locus_1 1240 bp ✓ kept locus_2 380 bp ✕ removed locus_3 860 bp ✓ kept locus_4 450 bp ✕ removed locus_5 1020 bp ✓ kept Other ways to filter Alignment length Matrix completeness Parsimony-informative sites Missing data Minimum taxa Taxon ID Filtering keeps or drops whole alignments. To drop single sequences instead, use Sequence Filtering. Converts partitions between RAxML and NEXUS formats.
Partition conversion A RAxML partition listing DNA, locus_1 = 1-100, locus_2 = 101-150, and locus_3 = 151-200 converts to and from a NEXUS sets block with the same charsets. RAxML DNA, locus_1 = 1-100 DNA, locus_2 = 101-150 DNA, locus_3 = 151-200 NEXUS begin sets; charset locus_1 = 1-100; charset locus_2 = 101-150; charset locus_3 = 151-200; end; Converts single or multiple partition files, and extracts partitions embedded in NEXUS alignments. Splits a concatenated alignment back into separate loci using its partition.
Alignment splitting A concatenated 18-site alignment and a partition defining locus_1 at sites 1 to 10 and locus_2 at sites 11 to 18 are split back into two separate alignments, locus_1 and locus_2. concatenated seq1 A G T C C C C A - - G G C T A A - T seq2 A G T C C C C A A T G G C T A A C T seq3 A G T C - C C T T A G G - T A A C T 1–10 11–18 partition.txt or NEXUS in-file charset split locus_1 seq1 A G T C C C C A - - seq2 A G T C C C C A A T seq3 A G T C - C C T T A locus_2 seq1 G G C T A A - T seq2 G G C T A A C T seq3 G G - T A A C T Splitting is the reverse of concatenation. It takes one concatenated alignment and its partition. Computes summary statistics for a set of alignments at three levels: the whole dataset, each alignment, and each sample.
Alignment summary A folder of alignments produces three outputs: an alignment summary text file for the whole dataset, a locus summary CSV with one row per alignment, and a taxon summary CSV with one row per sample. alignments DNA or amino acid Alignment summary Whole dataset · TXT Locus summary One row per alignment · CSV Taxon summary One row per sample · CSV Statistics differ for DNA and amino acid alignments; DNA is the default. Removes sites, not whole alignments, that have too much missing data or that fall below a count of parsimony-informative characters.
Guides → → not yet supported Alignment trimming With a missing data threshold of 0.5, sites 4 and 5 have more than half of the samples missing and are removed. The trimmed alignment: AGTC?ATG, AGTCTA-G, AGT-CATG, A-TCTATG. Missing data ≤ 50% per site ✕ ✕ seq1 A G T - - C ? A T G seq2 A G T - - C T A - G seq3 A G T C - - C A T G seq4 A - T - - C T A T G trim seq1 A G T C ? A T G seq2 A G T C T A - G seq3 A G T - C A T G seq4 A - T C T A T G Sites with more missing data than the threshold are removed. Trimming can also keep only parsimony-informative sites. Removes the gaps from every aligned sequence, so you can align the sequences again with a different aligner or settings.
Guides → → not yet supported Unalign alignments Gaps are removed from each aligned sequence: seq1 AGTCCATG, seq2 AGTCACCTG, seq3 ATCAATG. aligned seq1 A G T - - C C A T G seq2 A G T C A C C - T G seq3 A - T C A - - A T G unalign unaligned seq1 A G T C C A T G seq2 A G T C A C C T G seq3 A T C A A T G The output is FASTA with gaps removed, ready for a new alignment. Computes summary statistics for raw sequence reads in FASTQ format, plain, gzip, or BGZF-compressed. The read summary uses every CPU core, even for a single large file. Its complete mode reports quality by read position, read length, quality, and GC distributions, duplication across every read, overrepresented sequences, and adapter content, which SEGUI shows as an interactive report.
Read summary FASTQ read files, plain, gzip, or BGZF-compressed, produce a read summary table with read counts, lengths, and N50, GC content, base quality, and Q20 and Q30 bases. Complete mode adds per-position quality, duplication across every read, overrepresented sequences, and adapter content. sample.fq.gz FASTQ reads Read summary CSV table • Read count, length, and N50 • GC content, base quality, Q20 and Q30 • Duplication and adapters (complete) Modes: minimal · default · complete Accepts many files at once and writes one CSV table. Complete mode also writes a report that SEGUI shows as interactive charts. Computes summary statistics for assembled contigs in FASTA format, such as contig counts, lengths, N50, N75, N90, and GC content.
Contig summary FASTA contig files, plain or gzip-compressed, produce a contig summary table with contig counts and lengths, N50, N75, N90, and GC content. sample.fasta FASTA contigs Contig summary CSV table • Contig count and lengths • N50, N75, N90 • GC content, base counts Counts of contigs ≥ 750, 1000, 1500 bp Accepts many files at once and writes one CSV table. Whole-genome aligners, such as Progressive Cactus and LASTZ with MULTIZ, write Multiple Alignment Format (MAF) files: blocks that align a stretch of a reference genome to other genomes. MAF conversion turns the blocks into alignments that phylogenetic software can read. With a BED file of loci, each block is clipped to every locus it overlaps, and blocks of the same locus are joined across files. Without a BED file, each block, or each reference chromosome, becomes its own alignment.
Guides → → not yet supported MAF conversion Two MAF blocks on chr1 overlap the BED locus geneA (chr1:100–115). SEGUL joins them into one alignment named geneA-chr1-100-115. panTro6 is missing from block 2, so its part is filled with gaps: hg38 ACGT--ACGTACGGCCA, panTro6 ACGTTTACGTAC-----, mm10 ACGA--ACGTACGGCTA. genome.maf block 1 · chr1:100–110 hg38 A C G T - - A C G T A C panTro6 A C G T T T A C G T A C mm10 A C G A - - A C G T A C block 2 · chr1:110–115 hg38 G G C C A mm10 G G C T A loci.bed: geneA chr1:100–115 clip, join geneA-chr1-100-115 block 1 block 2 hg38 A C G T - - A C G T A C G G C C A panTro6 A C G T T T A C G T A C - - - - - mm10 A C G A - - A C G T A C G G C T A Blocks are clipped to each BED locus they overlap and joined in reference order. Species missing from a block are filled with gaps. Reports the number of blocks, the alignment length, and how much of the reference genome each species covers, so you can check a whole-genome alignment before converting it.
Guides → → not yet supported MAF summary genome.maf has 2 blocks, 3 species, 17 aligned columns, 15 reference bases. Reference coverage: hg38 100% in 2 of 2 blocks, mm10 100% in 2 of 2 blocks, panTro6 67% in 1 of 2 blocks. genome.maf 2 blocks 3 species 17 aligned columns 15 reference bases Reference coverage hg38 100% 2 of 2 blocks · reference mm10 100% 2 of 2 blocks panTro6 67% 1 of 2 blocks One CSV row per file and one per species. Coverage is the share of reference bases aligned to a base of the species. Lists every unique sample name across your files.
Sequence ID extraction Three alignments containing seq1, seq2, seq3; seq2, seq3; seq1, seq3, seq4 give one alphabetical list of unique IDs: seq1, seq2, seq3, seq4. locus_1 seq1 seq2 seq3 locus_2 seq2 seq3 locus_3 seq1 seq3 seq4 unique ID list seq1 seq2 seq3 seq4 Use the list to check for typos or inconsistent names before concatenation. Shows which samples are present in each file.
Sequence ID mapping Three alignments are mapped into a table of samples present in each: locus_1 has seq1, seq2, seq3; locus_2 has seq2, seq3; locus_3 has seq1, seq3, seq4. Present samples are TRUE and absent ones FALSE. locus_1 seq1 seq2 seq3 locus_2 seq2 seq3 locus_3 seq1 seq3 seq4 seq1 seq2 seq3 seq4 locus_1 TRUE TRUE TRUE FALSE locus_2 FALSE TRUE TRUE FALSE locus_3 TRUE FALSE TRUE TRUE The map is a CSV table of TRUE and FALSE values, written alongside the unique ID list. Replaces sample names across all files using a table of original and new names.
Guides → → not yet supported Sequence ID renaming An alignment with IDs sample_1, sample_2, sample_3 and a two-column table of original and new names give the same alignment with IDs Genus_species1_V01, Genus_species2_V02, Genus_species3_V03. locus_1 sample_1 sample_2 sample_3 + names.csv sample_1,Genus_species1_V01 sample_2,Genus_species2_V02 sample_3,Genus_species3_V03 rename locus_1 Genus_species1_V01 Genus_species2_V02 Genus_species3_V03 The table is a CSV or TSV file with a header row: original IDs in the first column and new IDs in the second. Adds sequences to existing files that share the same file name, such as new samples to a set of loci, or collects every sequence into one file. The output is unaligned, ready to realign.
Guides → → not yet supported Sequence addition seq4 from new/locus_1.fas is added to aligned/locus_1.nex because the file names match. The output locus_1.fas is unaligned: seq1 AGTCCATG, seq2 AGTCACCTG, seq3 ATCAATG, seq4 AGTCCATG. new/locus_1.fas seq4 A G T C C A T G aligned/locus_1.nex seq1 A G T - - C C A T G seq2 A G T C A C C - T G seq3 A - T C A - - A T G add locus_1.fas seq1 A G T C C A T G seq2 A G T C A C C T G seq3 A T C A A T G seq4 A G T C C A T G Sequences go to the destination file with the same name. Use a single destination file to collect every sequence in one place. Keeps only the sequences you select by ID, by a list in a text file, or by a regular expression.
Keep IDs: seq1; seq3 locus_1 seq1 A G T C C C C A T A seq2 A G T C C G C A T A seq3 A G T A C G C T T - seq4 G G T A C G T T T A ✓ ✕ ✓ ✕ extract result seq1 A G T C C C C A T A seq3 A G T A C G C T T - Extraction keeps the selected sequences. Removal is its opposite. Drops single sequences that fail a criterion, such as too few non-gap sites or too many gaps, and keeps the rest of each file. To drop whole alignments instead, use Alignment Filtering .
Guides → → not yet supported Sequence filtering Minimum length: 6 non-gap sites. Of seq1, seq2, seq3, seq4, the result keeps seq1, seq3. Minimum length: 6 non-gap sites locus_1 seq1 A G T C C C C A T A seq2 A G T C - - - - - - seq3 A G T A C G C T T - seq4 G G - - - - - - - - ✓ ✕ ✓ ✕ filter result seq1 A G T C C C C A T A seq3 A G T A C G C T T - Each sequence is checked on its own, so a file keeps every sequence that passes. Deletes the sequences you select by ID or by a regular expression. Removing a few sequences is faster than extracting the rest.
Sequence removal Remove IDs: seq2. Of seq1, seq2, seq3, seq4, the result keeps seq1, seq3, seq4. Remove IDs: seq2 locus_1 seq1 A G T C C C C A T A seq2 A G T C C G C A T A seq3 A G T A C G C T T - seq4 G G T A C G T T T A ✓ ✕ ✓ ✓ remove result seq1 A G T C C C C A T A seq3 A G T A C G C T T - seq4 G G T A C G T T T A Removal is the opposite of extraction. Translates DNA sequences to amino acids.
Sequence translation The DNA sequence ATG GCT TGG AAA TAA is read three bases at a time with the standard code to give the protein M A W K followed by a stop codon. DNA A T G G C T T G G A A A T A A M Met A Ala W Trp K Lys * Stop Protein Defaults to NCBI table 1, the standard code, in reading frame 1. You can choose another table or frame. Turns locus alignments into one file per sample. Each file holds one sequence for every locus where the sample is present, named after that locus, with gaps and missing data removed.
Guides → → not yet supported Sequence transposition Two loci become one file per sample. seq1 gets locus_1 and locus_2; seq2 gets locus_1; seq3 gets locus_1 and locus_2. Gaps and missing data are removed. locus_1 seq1 A G T C C C C A - - seq2 A G T C C C C A A T seq3 A G T C - C C T T A locus_2 seq1 G G C T A A - T seq3 G G - T A A C T transpose seq1 locus_1 A G T C C C C A locus_2 G G C T A A T seq2 locus_1 A G T C C C C A A T seq3 locus_1 A G T C C C T T A locus_2 G G T A A C T Each output sequence is named after its locus. Samples missing from a locus simply have no sequence for it. 