FigureLoom Bio Command Reference

FigureLoom Bio language reference

Compiler model

FigureLoom Bio is a programming language with a lexer, grammar parser, compiled instructions, validation, and a runtime. It is not a whitelist of complete sentences.

Grammar families: 10 Vocabulary forms: 304 Learning examples: 161

Examples are examples, not a whitelist. You can write your own instruction by combining operations, targets, values, role words, comparisons, and Boolean logic in a form the grammar can resolve unambiguously.

Normal instructions end with a period. Block headers end with a colon. The current result is called the file.

Operations

Concept	Words and terms
open	open, load, read, import
keep	keep, retain, select, filter
remove	remove, delete, drop, discard, exclude
show	show, display, view, print, list
count	count, total
save	save, write, export
rename	rename, name, call
sort	sort, order, arrange, put
replace	replace, fill, change
combine	combine, merge, join, append, add
convert	convert, change, turn
calculate	calculate, compute, measure, get
find	find, detect, identify, locate, call, design
create	create, make, draw, build, plot
check	check, validate, inspect, test
compare	compare, align
trim	trim, cut, clip
normalize	normalize, scale
translate	translate
say	say, print, write
run	run, repeat
stop	stop, end, quit
continue	continue, next, skip
warn	warn, warning

Biology and data terms

Concept	Words and terms
file	file, files, data, dataset, input
result	result, results, output
program	program, programs
sample	sample, samples
recipe	recipe, recipes
folder	folder, directory
review	review
pair	pair, paired, mates
row	row, rows, record, records
column	column, columns, field, fields
sequence	sequence, sequences, read, reads
base	base, bases, nucleotide, nucleotides
name	name, names, identifier, identifiers, id, ids
quality	quality, score, scores
adapter	adapter, adapters
dna	dna
rna	rna
protein	protein, proteins, amino, peptide, peptides
gene	gene, genes
variant	variant, variants, mutation, mutations
primer	primer, primers
alignment	alignment, alignments
tree	tree, phylogeny, phylogenetic
assembly	assembly, genome, contig, contigs
organism	organism, species, taxonomy
resistance	resistance, amr, antimicrobial
virulence	virulence
plasmid	plasmid, plasmids
signal peptide	signal peptide, signal peptides
transmembrane	transmembrane, membrane region, membrane regions
histogram	histogram
bar chart	bar chart, bar plot
scatter plot	scatter plot, scatter chart
box plot	box plot, boxplot
heat map	heat map, heatmap
pca	pca, principal component analysis
volcano	volcano plot, volcano
average	average, mean
median	median
standard deviation	standard deviation, sd
minimum	minimum, smallest, lowest
maximum	maximum, largest, highest
confidence interval	confidence interval, ci
p value	p value, p-value, pvalue
gc content	gc content, gc percentage
reverse complement	reverse complement, reverse-complement
open reading frame	open reading frame, open reading frames, orf, orfs
start codon	start codon, start codons
stop codon	stop codon, stop codons
palindrome	palindrome, palindromes, palindromic
duplicate	duplicate, duplicates, repeated, identical
ambiguous	ambiguous, unknown, n bases
gap	gap, gaps
length	length, long, longer, short, shorter
warning	warning, warn

If, else, loops, and recipes

Concept	Words and terms
if	if
else	else, otherwise
else if	else if, otherwise if
for every	for every
make recipe	make a recipe called
use recipe	use the recipe
make sure	make sure
call result	call the result
stop program	stop the program
continue sample	continue with the next sample
skip sample	skip this sample
mark review	mark the sample for review
show warning	show a warning, show a warning saying

Boolean logic

Concept	Words and terms
and	and
or	or
not	not

True and false

Concept	Words and terms
true	true
false	false

Decision terms

Concept	Words and terms
count	count
remain	remain, remains
exists	exists
empty	empty, not empty
found	found, were found, no
percent	percent
has	has
contains	contains

Role words

Concept	Words and terms
under	under, in, from, using, by
with	with, as, to, into
where	where, marked, whose
containing	containing, contains, with
between	between
from	from
to	to, into, as
using	using, under, by, grouped by
called	called, named
times	time, times
first	first
last	last

Comparisons

Concept	Words and terms
greater	longer than, greater than, more than, above, over, is above
at least	at least, minimum, no less than, is at least
less	shorter than, less than, below, under, fewer than, is below
at most	at most, maximum, no more than, is at most
equal	equals, equal to, is

File types

Concept	Words and terms
fastq	FASTQ
fasta	FASTA
csv	CSV
tsv	TSV

Optional plain-English words

Concept	Words and terms
please	please
then	then
now	now
the	the
a	a
an	an
current	current
only	only
all	all

Learning examples

These examples teach common structures and feed the visual builder. They do not define all legal programs.

Program

• Say The analysis is starting.
• Run this program 3 times.
• Show a warning saying This sample needs review.
• Stop the program.
• Continue with the next sample.
• Skip this sample.
• Mark the sample for review.

Files and results

• Open the file samples.csv.
• Open the files forward.fastq and reverse.fastq as a pair.
• Open the files first.fasta and second.fasta together.
• Merge the files first.fasta and second.fasta.
• Merge the result with more-sequences.fasta.
• Add the rows from more-samples.csv.
• Call the result clean reads.
• Use the result clean reads.
• Show the result.
• Show the file.
• Save the result as output.csv.
• Save the sequences as output.fasta.
• Save the pair as clean-forward.fastq and clean-reverse.fastq.
• Save the result using the sample name.
• Check the file.
• Count the file.
• Save the file as output.fasta.
• Copy the file as copy.fasta.
• Rename the file to renamed.fasta.
• List the files.

Tables and data

• Keep only rows marked treated under condition.
• Remove rows marked failed under status.
• Keep only the columns sample and condition.
• Rename the column old_name to sample.
• Put the rows in order by sample.
• Put the largest score first.
• Put the smallest score first.
• Remove duplicate rows using sample.
• Replace empty values under status with unknown.
• Combine it with metadata.csv using sample.
• Change untreated to control under condition.
• Count the rows.

DNA, RNA, and sequences

• Count the sequences.
• Count the reads.
• Count the bases.
• Show the sequence names.
• Show the first 5 sequences.
• Show the sequences.
• Keep only sequences longer than 500 bases.
• Keep sequences at least 100 bases long.
• Remove sequences shorter than 100 bases.
• Keep only sequences containing ATG.
• Remove sequences containing N.
• Use the sequence named sample-17.
• Remove the sequence named sample-17.
• Rename the sequence old-name to new-name.
• Add sample- to the start of every sequence name.
• Add -clean to the end of every sequence name.
• Remove duplicate sequences.
• Put the shortest sequences first.
• Put the longest sequences first.
• Show the sequence lengths.
• Find the shortest sequence.
• Find the longest sequence.
• Keep bases 10 to 100.
• Convert the DNA to RNA.
• Convert the RNA to DNA.
• Find the reverse complement.
• Translate the sequences.
• Calculate the GC content.
• Compare the sequences with reference.fasta.
• Merge the sequences with more.fasta.
• Calculate sequence statistics.
• Remove gaps from the sequences.
• Keep sequences with names containing sample.
• Remove sequences with names containing failed.
• Make duplicate sequence names unique.
• Remove sequences containing ambiguous bases.
• Keep sequences with at most 2 ambiguous bases.
• Validate the sequences.
• Split the sequences into files with 100 sequences each as part.fasta.
• Find repeated sequences.
• Find palindromes.
• Find start codons.
• Find stop codons.
• Find open reading frames.
• Join the sequences.

FASTQ and read quality

• Keep reads with average quality at least 20.
• Remove reads with average quality below 20.
• Remove reads with low quality.
• Check the quality.
• Show the quality report.
• Remove adapter sequences.
• Cut 5 bases from the beginning of each read.
• Cut 5 bases from the end of each read.
• Trim 5 bases from the start.
• Trim 5 bases from the end.

Microbiology

• Prepare bacterial reads.
• Assemble the bacterial genome from forward.fastq and reverse.fastq into assembly.
• Assemble the bacterial genome from reads.fastq into assembly.
• Assemble the bacterial genome.
• Check the assembly assembly/contigs.fasta into assembly-quality.
• Annotate the bacterial genome assembly/contigs.fasta into annotation.
• Annotate the file.
• Find resistance genes in assembly/contigs.fasta using card.
• Find resistance genes in the file.
• Find virulence genes in assembly/contigs.fasta.
• Find virulence genes in the file.
• Identify the organism in reads.fastq using bacteria-reference.
• Identify the organism in the file using bacteria-reference.
• Find plasmids in assembly/contigs.fasta into plasmids.
• Find plasmids in the file.

Alignment

• Compare the sequences.
• Show the alignment.
• Save the alignment as aligned.fasta.

Variants

• Find variants.
• Count the variants.
• Show the variants.
• Save the variants as variants.csv.

Genes and annotation

• Find genes.
• Count the genes.
• Show the genes.
• Save the genes as genes.csv.

Proteins

• Find signal peptides.
• Find transmembrane regions.

PCR and primers

• Find PCR primers.
• Check the primers.
• Show the primers.

Phylogenetics

• Build a phylogenetic tree.
• Show the tree.
• Save the tree as tree.nwk.

Statistics

• Calculate the average under score.
• Calculate the median under score.
• Calculate the standard deviation under score.
• Calculate the minimum under score.
• Calculate the maximum under score.
• Normalize the counts under count.
• Compare treated and control under group.
• Calculate the average of score.
• Calculate the median of score.
• Calculate the standard deviation of score.
• Calculate the confidence interval of score.
• Calculate the p value for score between treated and control under group.

Figures

• Create a histogram from score.
• Create a bar chart from sample and score.
• Create a scatter plot from x and y.
• Create a box plot from score.
• Create a histogram of score.
• Create a bar chart of group.
• Create a scatter plot of x and y.
• Create a box plot of score.
• Create a heat map.
• Create a PCA plot.
• Create a volcano plot using effect and p_value.

Decisions, loops, and recipes

• If the result is not empty:
• Otherwise if the result is empty:
• Otherwise:
• For every sample in samples:
• Make a recipe called Clean reads:
• Use the recipe Clean reads.
• Make sure at least 4 reads remain.
• Open all FASTQ files as samples.
• Open the sample.

Installed tools

• Run the tool seqkit with stats reads.fasta.

Free-form examples compiled by the grammar

Please load samples.csv.
If true and not false:
    Retain records where condition equals treated.
Else:
    Discard records where status equals failed.
Total the records.
Display the output.
Write the output to clean.csv.

The program above does not copy the learning-example wording. The compiler resolves the words and their grammatical roles into the same runtime operations.