### Setup Plotting Script

Source: https://isoseq.how/umi/cell-calling.html

Downloads the plotting utility and installs necessary Python dependencies.

```bash
# Download plotting script
$ wget https://downloads.pacbcloud.com/public/dataset/MAS-Seq/PLOT-scripts/plot_knees.py

# Install dependencies for plot_knees.py
$ conda install numpy
$ conda install matplotlib

# See help for plotting
$ python3 plot_knees.py --help
usage: plot_knees.py [-h] --tsv TSV --output OUTPUT [--max_cells MAX_CELLS] [--estimate_percentile ESTIMATE_PERCENTILE]

options:
  -h, --help            show this help message and exit
  --tsv TSV, -t TSV     Output tsv file from bcstats (can be gzipped)
  --output OUTPUT, -o OUTPUT
                        Output png prefix (`.knee.png` gets added)
  --max_cells MAX_CELLS, -m MAX_CELLS
                        Force an x axis maximum instead of the mpl default
  --estimate_percentile ESTIMATE_PERCENTILE, -e ESTIMATE_PERCENTILE
                        Calculates 99th through Nth (inclusive) percentiles for real cell cutoff [None]
```

--------------------------------

### Lima output file naming examples

Source: https://isoseq.how/clustering/cli-workflow.html

Examples of output file naming conventions based on primer pairs.

```text
movieX.fl.NEB_5p--NEB_Clontech_3p.bam
```

```text
movieX.fl.primer_5p--brain_3p.bam
movieX.fl.primer_5p--liver_3p.bam
```

--------------------------------

### Abundance file format

Source: https://isoseq.how/classification/isoseq-collapse

Example content of the *.abundance.txt output file.

```text
  pbid	count_fl	fl_assoc	cell_barcodes
  PB.1.1	2	2	ATCCATTCACCTCTGT,ATCGGCGCAGAGATGC
  PB.2.1	1	1	CGGACACCATTGCCGG
  PB.3.1	1	1	ACTTCGCGTCTAACTG
```

--------------------------------

### Group file format

Source: https://isoseq.how/classification/isoseq-collapse

Example content of the *.group.txt output file.

```text
  PB.1.1	molecule/7343975,molecule/7738347
  PB.2.1	molecule/14601188
  PB.3.1	molecule/3998518
```

--------------------------------

### Filtered Reasons File Example

Source: https://isoseq.how/classification/pigeon-output.html

Example content of a filtered reasons file showing isoform IDs and their corresponding filter criteria.

```text
# classification: sample_classification.txt
# isoform: ????????
# intrapriming cutoff: 0.6
# min_cov cutoff: 3
filtered_isoform,filter
PB.1.1,IntraPriming
PB.1.6,LowCoverage/Non-Canonical
PB.1.7,IntraPriming
PB.5.1,LowCoverage/Non-Canonical
PB.6.1,LowCoverage/Non-Canonical
```

--------------------------------

### Output file naming convention

Source: https://isoseq.how/umi/cli-workflow.html

Example of the output file naming structure for single sample libraries.

```text
<movie>.fl.5p--3p.bam
```

--------------------------------

### Primer FASTA examples

Source: https://isoseq.how/clustering/cli-workflow.html

Examples of primer FASTA file formats for different Iso-Seq applications, including MAS-Seq and standard cDNA primers.

```text
>IsoSeqX_bc01_5p
CTACACGACGCTCTTCCGATCTACTACACGCAATGAAGTCGCAGGGTTGGG
>IsoSeqX_bc02_5p
CTACACGACGCTCTTCCGATCTACTAGTAGCAATGAAGTCGCAGGGTTGGG
>IsoSeqX_bc03_5p
CTACACGACGCTCTTCCGATCTAGTGTACGCAATGAAGTCGCAGGGTTGGG
>IsoSeqX_bc04_5p
CTACACGACGCTCTTCCGATCTATCACTAGCAATGAAGTCGCAGGGTTGGG
>IsoSeqX_bc05_5p
CTACACGACGCTCTTCCGATCTCAGCTGTGCAATGAAGTCGCAGGGTTGGG
>IsoSeqX_bc06_5p
CTACACGACGCTCTTCCGATCTCAGTCACGCAATGAAGTCGCAGGGTTGGG
>IsoSeqX_bc07_5p
CTACACGACGCTCTTCCGATCTCATGTATGCAATGAAGTCGCAGGGTTGGG
>IsoSeqX_bc08_5p
CTACACGACGCTCTTCCGATCTCGTATGTGCAATGAAGTCGCAGGGTTGGG
>IsoSeqX_bc09_5p
CTACACGACGCTCTTCCGATCTGACATGTGCAATGAAGTCGCAGGGTTGGG
>IsoSeqX_bc10_5p
CTACACGACGCTCTTCCGATCTGAGTCTAGCAATGAAGTCGCAGGGTTGGG
>IsoSeqX_bc11_5p
CTACACGACGCTCTTCCGATCTGTAGATAGCAATGAAGTCGCAGGGTTGGG
>IsoSeqX_bc12_5p
CTACACGACGCTCTTCCGATCTGTATGACGCAATGAAGTCGCAGGGTTGGG
IsoSeqX_3p
AAGCAGTGGTATCAACGCAGAGTAC
```

```text
>NEB_5p
GCAATGAAGTCGCAGGGTTGGG
>Clontech_5p
AAGCAGTGGTATCAACGCAGAGTACATGGGG
>NEB_Clontech_3p
GTACTCTGCGTTGATACCACTGCTT
```

```text
>primer_5p
AAGCAGTGGTATCAACGCAGAGTACATGGGG
>brain_3p
CGCACTCTGATATGTGGTACTCTGCGTTGATACCACTGCTT
>liver_3p
CTCACAGTCTGTGTGTGTACTCTGCGTTGATACCACTGCTT
```

--------------------------------

### Configure Cell Calling Method

Source: https://isoseq.how/umi/cell-calling.html

Examples of using the percentile method for cell calling with default and custom percentile cutoffs.

```bash
isoseq correct --method percentile ...
isoseq bcstats --method percentile ...
```

```bash
isoseq correct --method percentile --percentile 97 ...
isoseq bcstats --method percentile --percentile 97 ...
```

--------------------------------

### Install lima

Source: https://isoseq.how/clustering/cli-workflow.html

Installs the lima tool via bioconda.

```bash
conda install lima
```

--------------------------------

### FLNC count file format

Source: https://isoseq.how/classification/isoseq-collapse

Example content of the *.flnc_count.txt output file.

```text
  id	BioSample1	BioSample2
  PB.1.1	2	2
  PB.2.1	1	2
  PB.3.1	1	1
```

--------------------------------

### Read statistics file format

Source: https://isoseq.how/classification/isoseq-collapse

Example content of the *.read_stat.txt output file.

```text
  id	pbid
  m64012_220421_000242/120719489/ccs/10460_11196	PB.1.1
  m64012_220421_000242/17565024/ccs/13918_14203	PB.1.1
  m64012_220421_000242/161089449/ccs/1955_2888	PB.2.1
  m64012_220421_000242/158664505/ccs/2488_2901	PB.3.1
```

--------------------------------

### Specify UMI and Barcode Design Strings

Source: https://isoseq.how/umi/umi-barcode-design.html

Examples of design strings for various UMI and barcode configurations using the isoseq tag syntax.

```text
T-8U-12B
```

```text
T-10U-16B
```

```text
8G-T
```

```text
6U-T-13U
```

--------------------------------

### Info CSV File Format

Source: https://isoseq.how/classification/pigeon-output.html

Example content of the info.csv file containing molecule metadata.

```csv
id	UMI	UMIrev	BC	BCrev	length	count
molecule/0	CCGCTCTCCT	AGGAGAGCGG	AAACCTGAGACATAAC	GTTATGTCTCAGGTTT	3718	1
```

--------------------------------

### Pigeon-compatible annotation format

Source: https://isoseq.how/classification/pigeon-annotation

Example of a manually modified annotation file structure required for Pigeon compatibility.

```text
Pf3D7_13_v3     VEuPathDB       gene    21364   28787   .       +       .       gene_id "PF3D7_1300100"; transcript_id "PF3D7_1300100.1"; gene_name "
PF3D7_1300100"; transcript_name "PF3D7_1300100.1"; biotype "test";
Pf3D7_13_v3     VEuPathDB       transcript      21364   28787   .       +       .       gene_id "PF3D7_1300100"; transcript_id "PF3D7_1300100.1"; gen
e_name "PF3D7_1300100"; transcript_name "PF3D7_1300100.1"; biotype "test";
Pf3D7_13_v3     VEuPathDB       exon    21364   26538   .       +       .       gene_id "PF3D7_1300100"; transcript_id "PF3D7_1300100.1"; gene_name "
PF3D7_1300100"; transcript_name "PF3D7_1300100.1"; biotype "test";
Pf3D7_13_v3     VEuPathDB       exon    27474   28787   .       +       .       gene_id "PF3D7_1300100"; transcript_id "PF3D7_1300100.1"; gene_name "
PF3D7_1300100"; transcript_name "PF3D7_1300100.1"; biotype "test";
Pf3D7_13_v3     VEuPathDB       CDS     21364   26538   .       +       0       Parent=PF3D7_1300100.1
Pf3D7_13_v3     VEuPathDB       CDS     27474   28787   .       +       0       Parent=PF3D7_1300100.1
Pf3D7_13_v3     VEuPathDB       gene    30605   31881   .       -       .       gene_id "PF3D7_1300200"; transcript_id "PF3D7_1300200.1"; gene_name "
PF3D7_1300200"; transcript_name "PF3D7_1300200.1"; biotype "test";
Pf3D7_13_v3     VEuPathDB       transcript      30605   31881   .       -       .       gene_id "PF3D7_1300200"; transcript_id "PF3D7_1300200.1"; gen
e_name "PF3D7_1300200"; transcript_name "PF3D7_1300200.1"; biotype "test";
Pf3D7_13_v3     VEuPathDB       exon    30605   31597   .       -       .       gene_id "PF3D7_1300200"; transcript_id "PF3D7_1300200.1"; gene_name "
PF3D7_1300200"; transcript_name "PF3D7_1300200.1"; biotype "test";
Pf3D7_13_v3     VEuPathDB       exon    31828   31881   .       -       .       gene_id "PF3D7_1300200"; transcript_id "PF3D7_1300200.1"; gene_name "
PF3D7_1300200"; transcript_name "PF3D7_1300200.1"; biotype "test";
Pf3D7_13_v3     VEuPathDB       CDS     30605   31597   .       -       0       Parent=PF3D7_1300200.1
Pf3D7_13_v3     VEuPathDB       CDS     31828   31881   .       -       0       Parent=PF3D7_1300200.1
```

--------------------------------

### GTF record hierarchy example

Source: https://isoseq.how/classification/pigeon-annotation

Visual representation of the required hierarchical organization for gene, transcript, and exon records.

```text
gene
transcript_1
  exon_1_1
  exon_1_2
transcript_2
  exon_2_1
  exon_2_2
```

--------------------------------

### CellTypist classification results

Source: https://isoseq.how/umi/tertiary-analysis

Example output table showing cell type counts generated by CellTypist.

```text
             CD16+ NK cells    168
        Classical monocytes    721
                        DC2     38
                    HSC/MPP     15
             Memory B cells     71
                   NK cells     68
              Naive B cells    145
    Non-classical monocytes    250
Tcm/Naive cytotoxic T cells     98
   Tcm/Naive helper T cells   1504
Tem/Effector helper T cells    356
Tem/Temra cytotoxic T cells    279
  Tem/Trm cytotoxic T cells    227
                        pDC     26
```

--------------------------------

### Annotated Info CSV File Format

Source: https://isoseq.how/classification/pigeon-output.html

Example content of the annotated.info.csv file including classification and filter status.

```csv
id	pbid	length	transcript	gene	category	ontarget	ORFgroup	UMI	UMIrev	BC	BCrev	pass_pigeon_filter
molecule/1856656	PB.10002.69	1201	ENST00000263918.9	STRN	incomplete-splice_match	NA	NA	GCATTACTGT	ACAGTAATGC	ACCGTAAAGAAGATTC	GAATCTTCTTTACGGT	PASS
```

--------------------------------

### Replicate legacy collapse logic

Source: https://isoseq.how/classification/isoseq-collapse

Command to run the collapse tool using parameters that mimic the behavior of versions prior to v3.8.0.

```bash
isoseq collapse --do-not-collapse-extra-5exons --max-5p-diff 5 --max-3p-diff 5 <mapped.bam> <collapsed.gff>
```

--------------------------------

### Configure collapse junction parameters

Source: https://isoseq.how/classification/isoseq-collapse

Displays the available command-line parameters for adjusting fuzzy junctions and 5p/3p differences in isoseq3 v4.0.0.

```bash
  --max-fuzzy-junction            INT    Ignore mismatches or indels shorter than or equal to N. [5]
  --max-5p-diff                   INT    Maximum allowed 5' difference if on same exon. [50]
  --max-3p-diff                   INT    Maximum allowed 3' difference if on same exon. [100]
```

--------------------------------

### Cluster isoforms with legacy cluster

Source: https://isoseq.how/clustering/cli-workflow.html

Runs the legacy clustering tool with verbose output and QV-guided consensus.

```bash
$ isoseq cluster flnc.fofn clustered.bam --verbose --use-qvs
```

--------------------------------

### End-to-end Iso-Seq command-line workflow

Source: https://isoseq.how/umi/examples.html

A complete sequence of commands to process HiFi reads, from downloading input files to generating deduplicated output.

```bash
# Download HiFi reads
$ wget https://downloads.pacbcloud.com/public/dataset/Kinnex-single-cell-RNA/TUTORIAL-DATA-PBMC-single-cell-mini/ccs.bam
$ wget https://downloads.pacbcloud.com/public/dataset/Kinnex-single-cell-RNA/TUTORIAL-DATA-PBMC-single-cell-mini/ccs.bam.pbi

# Download cDNA primers
$ wget https://downloads.pacbcloud.com/public/dataset/Kinnex-single-cell-RNA/TUTORIAL-DATA-PBMC-single-cell-mini/primers.fasta

# Download cell barcode include list
$ wget https://downloads.pacbcloud.com/public/dataset/Kinnex-single-cell-RNA/REF-10x_barcodes/3M-february-2018-REVERSE-COMPLEMENTED.txt.gz

# Check lima version to be >= 2.6.0
$ lima --version
lima 2.6.0

# Check isoseq version to be >= 4.0.0
$ isoseq --version
isoseq 4.0.0 

# cDNA primer removal and read orientation
$ lima --per-read --isoseq ccs.bam primers.fasta output.bam

# Clip UMI and cell barcode
$ isoseq tag output.5p--3p.bam flt.bam --design T-12U-16B

# Remove poly(A) tails and concatemer
$ isoseq refine flt.bam primers.fasta fltnc.bam --require-polya

# Correct single cell barcodes based on an include list
$ isoseq correct -B 3M-february-2018-REVERSE-COMPLEMENTED.txt.gz fltnc.bam corrected.bam

# Deduplicate reads based on UMIs
$ samtools sort -t CB corrected.bam -o corrected.sorted.bam
$ isoseq groupdedup corrected.sorted.bam dedup.bam 
```

--------------------------------

### Run isoseq bcstats with percentile method

Source: https://isoseq.how/umi/isoseq-bcstats.html

Ensures consistency by using the same percentile parameters as the preceding isoseq correct command.

```bash
isoseq correct --method percentile --percentile 90 ...
isoseq bcstats --method percentile --percentile 90
```

--------------------------------

### Prepare data and directory for CellTypist

Source: https://isoseq.how/umi/tertiary-analysis

Prepares the gene names file and creates a directory to store CellTypist output.

```bash
cut -f2 genes.tsv > genes_names.tsv
# Create a directory for celltypist result
mkdir celltypist_results
```

--------------------------------

### Prepare reference files with pigeon

Source: https://isoseq.how/classification/workflow

Sorts and indexes reference files. Can accept individual files or a file of file names (fofn).

```bash
pigeon prepare <gencode.annotation.gtf> <reference.fa> <cage.bed> <intropolis.tsv>
```

```bash
pigeon prepare files.fofn
```

--------------------------------

### 10x 5' kit primer sequences

Source: https://isoseq.how/umi/cli-workflow.html

FASTA format primer sequences for the 10x 5' kit.

```fasta
>5p
CTACACGACGCTCTTCCGATCT
>3p
GTACTCTGCGTTGATACCACTGCTT
```

--------------------------------

### SIRV Control GTF Annotation

Source: https://isoseq.how/classification/pigeon-annotation

Example of a GTF file format for SIRV control data. Ensure the gene and transcript IDs match your specific experimental requirements.

```GTF
SIRV1	LexogenSIRVData	gene	1001	11643	.	-	0	gene_name "SIRV1"; gene_id "SIRV1";
SIRV1	LexogenSIRVData	transcript	1001	10786	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV101";
SIRV1	LexogenSIRVData	exon	1001	1484	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV101"; exon_assignment "SIRV101_0";
SIRV1	LexogenSIRVData	exon	6338	6473	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV101"; exon_assignment "SIRV101_1";
SIRV1	LexogenSIRVData	exon	6561	6813	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV101"; exon_assignment "SIRV101_2";
SIRV1	LexogenSIRVData	exon	7553	7814	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV101"; exon_assignment "SIRV101_3";
SIRV1	LexogenSIRVData	exon	10283	10366	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV101"; exon_assignment "SIRV101_4";
SIRV1	LexogenSIRVData	exon	10445	10786	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV101"; exon_assignment "SIRV101_5";
SIRV1	LexogenSIRVData	transcript	1007	10366	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV102";
SIRV1	LexogenSIRVData	exon	1007	1484	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV102"; exon_assignment "SIRV102_0";
SIRV1	LexogenSIRVData	exon	6338	6813	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV102"; exon_assignment "SIRV102_1";
SIRV1	LexogenSIRVData	exon	7553	7814	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV102"; exon_assignment "SIRV102_2";
SIRV1	LexogenSIRVData	exon	10283	10366	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV102"; exon_assignment "SIRV102_3";
SIRV1	LexogenSIRVData	transcript	1001	10791	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV103";
SIRV1	LexogenSIRVData	exon	1001	1484	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV103"; exon_assignment "SIRV103_0";
SIRV1	LexogenSIRVData	exon	6338	6473	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV103"; exon_assignment "SIRV103_1";
SIRV1	LexogenSIRVData	exon	6561	6813	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV103"; exon_assignment "SIRV103_2";
SIRV1	LexogenSIRVData	exon	7553	7814	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV103"; exon_assignment "SIRV103_3";
SIRV1	LexogenSIRVData	exon	10283	10366	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV103"; exon_assignment "SIRV103_4";
SIRV1	LexogenSIRVData	exon	10648	10791	.	-	0	gene_name "SIRV1"; gene_id "SIRV1"; transcript_id "SIRV103"; exon_assignment "SIRV103_5";
```

--------------------------------

### Run isoseq correct

Source: https://isoseq.how/umi/isoseq-correct.html

Execute the barcode correction tool on a BAM file using a provided whitelist file.

```bash
isoseq correct --barcodes barcodes.txt[.gz] input.bam output.bam
```

--------------------------------

### 10x 3' kit primer sequences

Source: https://isoseq.how/umi/cli-workflow.html

FASTA format primer sequences for the 10x 3' kit.

```fasta
>5p
AAGCAGTGGTATCAACGCAGAGTACATGGG
>3p
AGATCGGAAGAGCGTCGTGTAG
```

--------------------------------

### Gencode annotation reference

Source: https://isoseq.how/classification/pigeon-annotation

A sample snippet of a Gencode annotation file demonstrating the expected tab-delimited structure and attribute formatting.

```text
chr1    ENSEMBL gene    17369   17436   .       -       .       gene_id "ENSG00000278267.1"; gene_type "miRNA"; gene_status "KNOWN"; gene_name "MIR68
59-1"; level 3;
chr1    ENSEMBL transcript      17369   17436   .       -       .       gene_id "ENSG00000278267.1"; transcript_id "ENST00000619216.1"; gene_type "mi
RNA"; gene_status "KNOWN"; gene_name "MIR6859-1"; transcript_type "miRNA"; transcript_status "KNOWN"; transcript_name "MIR6859-1-201"; level 3; tag "
basic"; transcript_support_level "NA";
chr1    ENSEMBL exon    17369   17436   .       -       .       gene_id "ENSG00000278267.1"; transcript_id "ENST00000619216.1"; gene_type "miRNA"; ge
ne_status "KNOWN"; gene_name "MIR6859-1"; transcript_type "miRNA"; transcript_status "KNOWN"; transcript_name "MIR6859-1-201"; exon_number 1; exon_id
 "ENSE00003746039.1"; level 3; tag "basic"; transcript_support_level "NA";
chr1    HAVANA  gene    29554   31109   .       +       .       gene_id "ENSG00000243485.3"; gene_type "lincRNA"; gene_status "KNOWN"; gene_name "RP1
1-34P13.3"; level 2; tag "ncRNA_host"; havana_gene "OTTHUMG00000000959.2";
chr1    HAVANA  transcript      29554   31097   .       +       .       gene_id "ENSG00000243485.3"; transcript_id "ENST00000473358.1"; gene_type "li
ncRNA"; gene_status "KNOWN"; gene_name "RP11-34P13.3-001"; transcript_type "lincRNA"; transcript_status "KNOWN"; transcript_name "RP11-34P13.3-001"; leve
l 2; tag "not_best_in_genome_evidence"; tag "basic"; transcript_support_level "5"; havana_gene "OTTHUMG00000000959.2"; havana_transcript "OTTHUMT0000
0002840.1";
chr1    HAVANA  exon    29554   30039   .       +       .       gene_id "ENSG00000243485.3"; transcript_id "ENST00000473358.1"; gene_type "lincRNA";
gene_status "KNOWN"; gene_name "RP11-34P13.3"; transcript_type "lincRNA"; transcript_status "KNOWN"; transcript_name "RP11-34P13.3-001"; exon_number
1; exon_id "ENSE00001947070.1"; level 2; tag "not_best_in_genome_evidence"; tag "basic"; transcript_support_level "5"; havana_gene "OTTHUMG0000000095
9.2"; havana_transcript "OTTHUMT00000002840.1";
chr1    HAVANA  exon    30564   30667   .       +       .       gene_id "ENSG00000243485.3"; transcript_id "ENST00000473358.1"; gene_type "lincRNA";
gene_status "KNOWN"; gene_name "RP11-34P13.3"; transcript_type "lincRNA"; transcript_status "KNOWN"; transcript_name "RP11-34P13.3-001"; exon_number
2; exon_id "ENSE00001922571.1"; level 2; tag "not_best_in_genome_evidence"; tag "basic"; transcript_support_level "5"; havana_gene "OTTHUMG0000000095
9.2"; havana_transcript "OTTHUMT00000002840.1";
chr1    HAVANA  exon    30976   31097   .       +       .       gene_id "ENSG00000243485.3"; transcript_id "ENST00000473358.1"; gene_type "lincRNA";
gene_status "KNOWN"; gene_name "RP11-34P13.3"; transcript_type "lincRNA"; transcript_status "KNOWN"; transcript_name "RP11-34P13.3-001"; exon_number
3; exon_id "ENSE00001827679.1"; level 2; tag "not_best_in_genome_evidence"; tag "basic"; transcript_support_level "5"; havana_gene "OTTHUMG0000000095
9.2"; havana_transcript "OTTHUMT00000002840.1";
```

--------------------------------

### Run isoseq tag command

Source: https://isoseq.how/umi/cli-workflow.html

Executes the tag command to clip UMIs and barcodes from CCS reads based on a specified design.

```bash
$ isoseq tag <mvie>.fl.5p--3p.bam <movie>.flt.bam --design XXX
```

--------------------------------

### Create ConsensusReadSet XML

Source: https://isoseq.how/umi/tertiary-analysis

Generates an XML file for importing HiFi reads into SMRT Link using the smrtcmds utility.

```bash
 ${SMRT_ROOT}/smrtcmds/bin/dataset create \
     --type ConsensusReadSet \
     --name PBMC_5k \
     m64476e_220618_014917.consensusreadset.xml \
     m64476e_220618_014917.hifi_reads.bam
```

--------------------------------

### Run isoseq refine command

Source: https://isoseq.how/umi/cli-workflow.html

Executes the refine command to trim poly(A) tails and remove concatemers from tagged reads.

```bash
$ isoseq refine <movie>.flt.5p--3p.bam primers.fasta <movie>.fltnc.bam --require-polya
```

--------------------------------

### Cluster isoforms with cluster2

Source: https://isoseq.how/clustering/cli-workflow.html

Runs the streaming clustering workflow on an FLNC file or fofn.

```bash
$ isoseq cluster2 flnc.fofn clustered.bam
```

--------------------------------

### Collapse mapped reads

Source: https://isoseq.how/classification/isoseq-collapse

Execute the collapse command for single-cell or bulk Iso-Seq data.

```bash
isoseq collapse <mapped.bam> <collapse.gff>
```

```bash
isoseq collapse --do-not-collapse-extra-5exons <mapped.bam> <flnc.bam> <collapsed.gff>
```

--------------------------------

### Prepare transcript GFF

Source: https://isoseq.how/classification/workflow

Sorts the transcript GFF file output from isoseq collapse.

```bash
pigeon prepare <collapsed.gff>
```

--------------------------------

### Create file of filenames for merged SMRT cells

Source: https://isoseq.how/clustering/cli-workflow.html

Generates a file of filenames (fofn) containing all flnc.bam files for multi-cell processing.

```bash
$ ls movie*.flnc.bam movie*.flnc.bam movie*.flnc.bam > flnc.fofn
```

--------------------------------

### Run lima for primer removal

Source: https://isoseq.how/umi/cli-workflow.html

Execute lima in --isoseq mode to remove primers and identify barcodes.

```bash
$ lima <movie>.hifi_reads.bam primers.fasta <movie>.fl.bam --isoseq
```

--------------------------------

### Collapse transcripts with isoseq

Source: https://isoseq.how/classification/workflow

Collapses redundant transcripts into unique isoforms. Bulk Iso-Seq requires the --do-not-collapse-extra-5exons flag and an optional flnc.bam input.

```bash
isoseq collapse <mapped.bam> <collapsed.gff>
```

```bash
isoseq collapse --do-not-collapse-extra-5exons <mapped.bam> <flnc.bam> <collapsed.gff>
```

--------------------------------

### Refine full-length reads

Source: https://isoseq.how/clustering/cli-workflow.html

Executes the refine command on a demultiplexed CCS file and primer fasta file.

```bash
$ isoseq refine movieX.NEB_5p--NEB_Clontech_3p.fl.bam primers.fasta movieX.flnc.bam
```

--------------------------------

### Run isoseq bcstats

Source: https://isoseq.how/umi/isoseq-bcstats.html

Generates barcode statistics from a corrected BAM file, outputting to a JSON file and a TSV file.

```bash
isoseq bcstats --json sample.bcstats.json -o sample.bcstats.tsv corrected.bam
```

--------------------------------

### Seurat Output File Structure

Source: https://isoseq.how/classification/pigeon-output.html

List of files generated by the make-seurat tool for downstream analysis.

```text
<output_dir>/annotated.info.csv
<output_dir>/annotated-prefilter.info.csv
<output_dir>/info.csv
<output_dir>/genes_seurat/barcodes.tsv
<output_dir>/genes_seurat/genes.tsv
<output_dir>/genes_seurat/matrix.mtx
<output_dir>/isoforms_seurat/barcodes.tsv
<output_dir>/isoforms_seurat/genes.tsv
<output_dir>/isoforms_seurat/matrix.mtx
```

--------------------------------

### Process Single Sample Iso-Seq Data

Source: https://isoseq.how/clustering/examples.html

Workflow for processing segmented reads from a Kinnex full-length RNA library, including primer removal, poly(A) tail refinement, and clustering.

```bash
# Download toy S-read dataset
$ wget https://downloads.pacbcloud.com/public/dataset/IsoSeq_sandbox/human_80k_Sreads.segmented.bam
$ wget https://downloads.pacbcloud.com/public/dataset/IsoSeq_sandbox/human_80k_Sreads.segmented.bam.pbi

# Download the Iso-Seq v2 cDNA primers (from Iso-Seq express 2.0 kit)
$ wget https://downloads.pacbcloud.com/public/dataset/Kinnex-full-length-RNA/REF-primers/IsoSeq_v2_primers_12.fasta

$ lima --version
lima 2.9.0

$ lima human_80k_Sreads.segmented.bam IsoSeq_v2_primers_12.fasta output.bam --isoseq --peek-guess

$ ls output.*
output.IsoSeqX_bc10_5p--IsoSeqX_3p.bam
output.IsoSeqX_bc10_5p--IsoSeqX_3p.bam.pbi
output.IsoSeqX_bc10_5p--IsoSeqX_3p.consensusreadset.xml
output.json
output.lima.clips
output.lima.counts
output.lima.guess
output.lima.report
output.lima.summary


$ isoseq refine output.IsoSeqX_bc10_5p--IsoSeqX_3p.bam IsoSeq_v2_primers_12.fasta flnc.bam --require-polya

$ ls flnc.*
flnc.bam
flnc.bam.pbi
flnc.consensusreadset.xml
flnc.filter_summary.report.json
flnc.report.csv

$ isoseq cluster2 flnc.bam transcripts.bam


$ ls transcripts*
transcripts.bam
transcripts.bam.pbi
transcripts.cluster_report.csv
```

--------------------------------

### Display Final GTF Result

Source: https://isoseq.how/classification/pigeon-annotation

Shows the final output format after conversion to GTF.

```text
ChrM	cshl_gene	transcript	444449	447142	.	-	.	transcript_id "SbiRTX436.MG005100.1"; gene_id "SbiRTX436.MG005100"; gene_name "SbiRTX436.MG005100"
ChrM	cshl_gene	exon	444449	447142	.	-	.	transcript_id "SbiRTX436.MG005100.1"; gene_id "SbiRTX436.MG005100"; gene_name "SbiRTX436.MG005100";
ChrM	cshl_gene	CDS	444449	445615	.	-	0	transcript_id "SbiRTX436.MG005100.1"; gene_id "SbiRTX436.MG005100"; gene_name "SbiRTX436.MG005100";
```

--------------------------------

### Classify isoforms with pigeon

Source: https://isoseq.how/classification/workflow

Classifies isoforms into categories. Supports supplemental reference information, pre-built reference sets, and FLNC count integration.

```bash
pigeon classify <collapsed.sorted.gff> <annotations.gtf> <reference.fa>
```

```bash
pigeon classify <collapsed.sorted.gff> <annotations.gtf> <reference.fa> --cage-peak refTSS.bed --poly-a polyA.list
```

```bash
pigeon classify <sorted.gff> --ref Human_hg38_Gencode_v39.referenceset.xml
```

```bash
pigeon classify <collapsed.sorted.gff> <annotations.gtf> <reference.fa> --fl abundance.txt
```

```bash
pigeon classify <collapsed.sorted.gff> <annotations.gtf> <reference.fa> --fl flnc_count.txt
```

--------------------------------

### Generate Seurat-compatible count matrix

Source: https://isoseq.how/classification/workflow

Creates count matrices for Seurat analysis using deduped fasta and group files.

```bash
pigeon make-seurat --dedup <dedup.fasta> --group <collapse.group.txt> -d <output_dir> <classification.filtered_lite_classification.txt>
```

```bash
Make-seurat output:
<output_dir>/annotated.info.csv
<output_dir>/info.csv
<output_dir>/genes_seurat/barcodes.tsv
<output_dir>/genes_seurat/genes.tsv
<output_dir>/genes_seurat/matrix.mtx
<output_dir>/isoforms_seurat/barcodes.tsv
<output_dir>/isoforms_seurat/genes.tsv
<output_dir>/isoforms_seurat/matrix.mtx
```

--------------------------------

### Adjusting Insert Transcript Concordance Parameters

Source: https://isoseq.how/umi/dedup-faq.html

Parameters for controlling insert alignment concordance and gap thresholds.

```bash
  --min-concordance-perc    INT   Minimum insert alignment concordance in %. [97]
  --max-insert-gaps         INT   Maximum number of insert gaps per 20 bp window. [5]
```

--------------------------------

### Map reads with pbmm2

Source: https://isoseq.how/classification/workflow

Aligns reads to a reference genome using the ISOSEQ preset.

```bash
pbmm2 align --preset ISOSEQ --sort <input.bam> <ref.fa> <mapped.bam>
```

--------------------------------

### Run bcstats for Cell Calling Analysis

Source: https://isoseq.how/umi/cell-calling.html

Generates the TSV report required for barcode rank plotting.

```bash
# Run bcstats on the corrected bam
$ isoseq bcstats --json bcstats_report.json -o bcstats_report.tsv <corrected.bam>
```

--------------------------------

### Sorting BAM by Cell Barcode for groupdedup

Source: https://isoseq.how/umi/dedup-faq.html

Required sorting step for BAM files before running isoseq groupdedup.

```bash
samtools sort –t CB corrected.bam –o corrected.sorted.bam
isoseq groupdedup corrected.bam dedup.bam
```

--------------------------------

### Process Multiplexed Iso-Seq Data

Source: https://isoseq.how/clustering/examples.html

Workflow for demultiplexing and processing regular Iso-Seq HiFi reads, including primer removal, refinement, and clustering.

```bash
# Download HiFi reads from a non-Kinnex (regular Iso-Seq) BAM file
$ wget https://downloads.pacbcloud.com/public/dataset/Kinnex-full-length-RNA/DATA-SQ2-UHRR-Monomer/1-CCS/m64307e_230628_025302.hifi_reads.bam
$ wget https://downloads.pacbcloud.com/public/dataset/Kinnex-full-length-RNA/DATA-SQ2-UHRR-Monomer/1-CCS/m64307e_230628_025302.hifi_reads.bam.pbi

# Download the Iso-Seq v2 cDNA primers (from Iso-Seq express 2.0 kit)
$ wget https://downloads.pacbcloud.com/public/dataset/Kinnex-full-length-RNA/REF-primers/IsoSeq_v2_primers_12.fasta

# Demux and primer removal
$ lima --overwrite-biosample-names --isoseq --peek-guess m64307e_230628_025302.hifi_reads.bam IsoSeq_v2_primers_12.fasta output.bam

# Combine inputs
$ ls output.IsoSeqX*bam > all.fofn

# Remove poly(A) tails and concatemer
$ isoseq refine all.fofn IsoSeq_v2_primers_12.fasta flnc.bam --require-polya

$ isoseq cluster2 flnc.bam transcripts.bam
```

--------------------------------

### Display Unmodified GFF Content

Source: https://isoseq.how/classification/pigeon-annotation

Shows the initial structure of a sorghum GFF file before any modifications are applied.

```text
ChrM	cshl_gene	gene	444449	447142	.	-	.	ID=SbiRTX436.MG005100;Name=SbiRTX436.MG005100;biotype=protein_coding
ChrM	cshl_gene	mRNA	444449	447142	.	-	.	ID=SbiRTX436.MG005100.1;Parent=SbiRTX436.MG005100;Name=SbiRTX436.MG005100.1;biotype=protein_coding
ChrM	cshl_gene	five_prime_UTR	445616	447142	.	-	.	Parent=SbiRTX436.MG005100.1;Name=5UTR.1
ChrM	cshl_gene	exon	444449	447142	.	-	.	Parent=SbiRTX436.MG005100.1;Name=exon.1
ChrM	cshl_gene	CDS	444449	445615	.	-	.	Parent=SbiRTX436.MG005100.1;Name=CDS.1
```

--------------------------------

### Adjusting Tag Mismatch and Shift Parameters

Source: https://isoseq.how/umi/dedup-faq.html

Parameters for controlling tag mismatch and shift thresholds in isoseq groupdedup.

```bash
  --max-tag-mismatches      INT   Maximum number of mismatches between tags. [1]
  --max-tag-shift           INT   Tags may be shifted by at maximum of N bases. [1]
```

--------------------------------

### Report gene saturation

Source: https://isoseq.how/classification/workflow

Determines gene and isoform-level saturation. Use --exclude-singletons for bulk Iso-Seq clustered with cluster2.

```bash
pigeon report <classification.filtered_lite_classification.txt> <saturation.txt>
```

```bash
pigeon report --exclude-singletons <classification.filtered_lite_classification.txt> <saturation.txt>
```

--------------------------------

### Generate Barcode Rank Plots

Source: https://isoseq.how/umi/cell-calling.html

Commands to generate barcode rank plots with or without percentile markers.

```bash
# Plot barcode rank plot without percentile markers
$ python3 plot_knees.py -t <bcstats_report.tsv> -o <prefix>
```

```bash
# Plot barcode rank plot with percentile markers
$ python3 plot_knees.py -t <bcstats_report.tsv> -o <prefix> --estimate_percentile 95
```

--------------------------------

### Run lima for primer removal and demultiplexing

Source: https://isoseq.how/clustering/cli-workflow.html

Executes lima to remove primers and identify cDNA barcodes. Use the --overwrite-biosample-names flag when samples are barcoded at the cDNA level.

```bash
$ lima movieX.hifi_reads.bam barcoded_primers.fasta movieX.fl.bam --isoseq --peek-guess
```

```bash
$ lima movieX.hifi_reads.bam barcoded_primers.fasta movieX.fl.bam --isoseq --peek-guess --overwrite-biosample-names
```

--------------------------------

### Convert GFF to GTF with gffread

Source: https://isoseq.how/classification/pigeon-annotation

Converts the modified GFF file into a simplified GTF format using the gffread tool.

```bash
gffread sorghum.modified.gff -T --keep-genes -o sorghum.modified.gtf
```

--------------------------------

### Refine reads with poly(A) tail filtering

Source: https://isoseq.how/clustering/cli-workflow.html

Filters for full-length reads containing a poly(A) tail of at least 20 base pairs and removes the tail.

```bash
$ isoseq refine movieX.NEB_5p--NEB_Clontech_3p.fl.bam movieX.flnc.bam --require-polya
```

--------------------------------

### Correct Cell Barcodes

Source: https://isoseq.how/umi/cli-workflow.html

Identify and correct cell barcode errors using a whitelist and the correct tool.

```bash
$ isoseq correct –barcodes barcode_set.txt fltnc.bam fltnc.corrected.bam
```