SeqSizzle is a pager for viewing FASTQ and FASTA files with fuzzy matching, allowing different adaptors to be colored differently.

Installation

Pre-built binary

You can simply download and run the binary from Github Actions.

Conda

SeqSizzle is also available on bioconda:

conda install -c bioconda -c conda-forge seqsizzle

Cargo (crates.io)

If you already have a Rust environment set up, you can use the cargo install command:

cargo install seqsizzle

Cargo will build the seqsizzle binary and place it in $HOME/.local/share/cargo/bin/seqsizzle.

Cargo (git)

If you already have a Rust environment set up, you can use the cargo install command in your local clone of the repo:

git clone https://github.com/ChangqingW/SeqSizzle
cd SeqSizzle
cargo install --path .

Cargo will build the seqsizzle binary and place it in $HOME/.cargo.

Usage

seqsizzle -h:

A pager for viewing FASTQ and FASTA files with fuzzy matching, allowing different adaptors to be colored differently.

Usage: seqsizzle [OPTIONS] <FILE> [COMMAND]

Commands:
  summarize  Summarize the reads with patterns specified by the --patterns argument or the adapter flags. Make sure you supply the flags BEFORE the subcommand, e.g. `./SeqSizzle my.fastq -p my_patterns.csv --adapter-3p summarize`. '..' indicats unmatched regions of positive length, '-' indicates the patterns are overlapped, print the number of reads that match each pattern combination in TSV format. To be moved to the UI in the future
  enrich     Find enriched k-mers in the reads. This can be used to identify potential adapter/primer sequences
  help       Print this message or the help of the given subcommand(s)

Arguments:
  <FILE>  The FASTQ or FASTA file to view (supports .fastq, .fasta, .fa, .fq and their .gz variants)

Options:
      --adapter-3p
          Start with 10x 3' kit adaptors:
           - Patrial Read1: CTACACGACGCTCTTCCGATCT (and reverse complement)
           - Partial TSO: CCCATGTACTCTGCGTTGATACCA (and reverse complement)
           - Poly(>10)A/T
      --adapter-5p
          Start with 10x 5' kit adaptors
           - Patrial Read1: CTACACGACGCTCTTCCGATCT (and reverse complement)
           - Patrial Read2: AGATCGGAAGAGCACACGTCTGAA (and reverse complement)
           - TSO: TTTCTTATATGGG (and reverse complement)
           - Poly(>10)A/T
  -p, --patterns <PATTERNS_PATH>
          Start with patterns from a CSV file
          Must have the following header:
          pattern,color,editdistance,comment
  -s, --save-patterns <SAVE_PATTERNS_PATH>
          Save the search panel to a CSV file before quitting. To be removed in the future since you can now hit Ctrl-S in the search panel to save the patterns
      --quality-italic
          Enable italic styling for low quality bases (enabled by default)
      --no-quality-italic
          Disable italic styling for low quality bases
      --quality-threshold <QUALITY_THRESHOLD>
          Quality threshold for styling [default: 10]
      --quality-colors
          Enable background color styling based on quality scores. You will probably have a hard time distinguishing forground colors from background colors, so this is disabled by default
  -h, --help
          Print help
  -V, --version
          Print version

Navigation

Viewer mode

Up / down arrow (or j / k) to scroll by one line, Ctrl+U / Ctrl+D to scoll half a screen.
/ (or Ctrl+F) to toggle search panel, q to quit.
i to toggle Italics for low quality bases (threshold define by --quality-threshold, default 10).
b to toggle Background color styling based on quality scores
Viewer mode with background color styling enabled would make forground colors hard to distinguish: Make sure your terminal supports 256 colors (e.g. terminal emulators like iterm2, kitty, etc.) and your font support italics and bold styles otherwise it may look less appealing.

search panel mode

Left / right arrow (or Tab / Shift-Tab) to cycle through different input fields and the patterns list.
When on the patterns list field, up / down arrows cycle through patterns, Backspace (or Delete, d) to delete the selected pattern and Return to pop the pattern into the input fields for editing.
Return to add current inputs into the search pattern list (when focusing on any of the input boxes, rather than the patterns list).
Use Shift + arrow keys to move cursor within an input field (as arrow keys alone are bind to cycling input fields).
/ or Esc to close the search panel.

Subcommands

enrich

seqsizzle enrich --help:

Find enriched k-mers in the reads. This can be used to identify potential adapter/primer sequences

Usage: seqsizzle <FILE> enrich [OPTIONS] --output <OUTPUT>

Options:
  -o, --output <OUTPUT>
          Path to write the output CSV file
      --max-reads <MAX_READS>
          Limit the total number of reads used for enrichment. Set to 0 to use all reads [default: 10000]
      --sample
          If set, randomly sample `--max-reads` reads from the file instead of taking the first N. Requires `--max-reads`
      --k-min <K_MIN>
          Minimum k-mer length to check [default: 8]
      --k-max <K_MAX>
          Maximum k-mer length to check [default: 12]
      --k-step <K_STEP>
          Step size between k-values (arithmetic progression) [default: 2]
      --top-kmers <TOP_KMERS>
          Number of top k-mers to keep per k value [default: 400]
      --substring-count-ratio-threshold <SUBSTRING_COUNT_RATIO_THRESHOLD>
          Substring filtering counts ratio threshold. For k-mers that are contained within longer k-mers, those with (shorter k-mer count) / (longer k-mer count) >= this threshold will be removed. For homopolymer k-mers, the threshold is lowered to threshold^4 [default: 0.8]
      --min-count <MIN_COUNT>
          Minimum counts per read threshold for k-mers (overrides z-score if provided). Accepts fractional values (e.g., 0.01 for 1 count per 100 reads)
      --z-score-threshold <Z_SCORE_THRESHOLD>
          Z-score threshold for k-mer enrichment (default: 5.0) [default: 5]
      --skip-assemble
          Perform assembly with k_max k-mers
      --detect-reverse-complement
          Detect and merge reverse complement k-mers
  -h, --help
          Print help

Example output CSV file: seqsizzle test.fastq enrich -o enrichment.csv

sequence,length,estimated_count,counts_per_read,source_k,sqrt_deviance,log_fold_enrichment
TTTTTTTTTTTT,12,179912,17.99,12,2041.4,18.2
AAAAAAAAAAAA,12,94008,9.40,12,1433.7,17.2
CCCATGTACTCTGCGTTGATACCACTGCTT,30,6190,0.62,assembled from k=12,640.8,49.3
CTACACGACGCTCTTCCGATCT,22,6440,0.64,assembled from k=12,533.7,33.3
AAGCAGTGGTATCAACGCAGAGTACATGGG,30,3298,0.33,assembled from k=12,463.3,48.4
AGATCGGAAGAGCGTCGTGTAG,22,3441,0.34,assembled from k=12,384.5,32.4
...

summarize

seqsizzle summarize --help:

Summarize the reads with patterns specified by the --patterns argument or the adapter flags. Make sure you supply the flags BEFORE the subcommand, e.g. `./SeqSizzle my.fastq -p my_patterns.csv --adapter-3p summarize`. '..' indicats unmatched regions of positive length, '-' indicates the patterns are overlapped, print the number of reads that match each pattern combination in TSV format. To be moved to the UI in the future

Usage: seqsizzle <FILE> summarize [OPTIONS]

Options:
      --counts  Print the counts of each summarized catagory instead of the percentage
  -h, --help    Print help

Example output: seqsizzle test.fastq --adapter-3p summarize > summarize.txt

tail summarize.txt
1%	..TGGTATCAACGCAGAGTACATGGG..AAAAAAAAAAAA..AAAAAAAAAAAA..AAAAAAAAAAAA..AGATCGGAAGAGCGTCGTGTAG
1%	CTACACGACGCTCTTCCGATCT..TTTTTTTTTTTT..TTTTTTTTTTTT..TTTTTTTTTTTT..CCCATGTACTCTGCGTTGATACCA..
1%	..TGGTATCAACGCAGAGTACATGGG..AGATCGGAAGAGCGTCGTGTAG
1%	CTACACGACGCTCTTCCGATCT..CCCATGTACTCTGCGTTGATACCA..
3%	CTACACGACGCTCTTCCGATCT..TTTTTTTTTTTT..AAAAAAAAAAAA..CCCATGTACTCTGCGTTGATACCA..
3%	..TGGTATCAACGCAGAGTACATGGG..TTTTTTTTTTTT..AAAAAAAAAAAA..AGATCGGAAGAGCGTCGTGTAG
6%	..TGGTATCAACGCAGAGTACATGGG..AAAAAAAAAAAA..AAAAAAAAAAAA..AGATCGGAAGAGCGTCGTGTAG
6%	CTACACGACGCTCTTCCGATCT..TTTTTTTTTTTT..TTTTTTTTTTTT..CCCATGTACTCTGCGTTGATACCA..
34%	..TGGTATCAACGCAGAGTACATGGG..AAAAAAAAAAAA..AGATCGGAAGAGCGTCGTGTAG
36%	CTACACGACGCTCTTCCGATCT..TTTTTTTTTTTT..CCCATGTACTCTGCGTTGATACCA..

The output indicates 36% of reads contains the R1 adaptor, followed by a polyT stretch and the TSO sequence. The line above (files sorted by percentage) indicates that 34% of reads are the reverse complement of that. The .. indicates an insertion of unmatched sequence.

Roadmap

functionality

• Gzip (fastq.gz) support
• FASTA support
• Styling mismatches and low quality bases
• Built-in k-mer enrichment to identify primers and adaptors
• Filter reads by match
• Counting reads with match

UI

• Make elements in the search panel clickable, try implementations discussed in ratatui repo