The Isoform Sequencing (Iso-Seq™) Anaylsis refers to PacBio’s proprietary methods and software applications for transcriptome sequencing. The Iso-Seq application generates full-length cDNA sequences — from the 5’ end of transcripts to the poly-A tail — eliminating the need for transcriptome reconstruction using isoform-inference algorithms. The Iso-Seq method generates accurate information about alternatively spliced exons and transcriptional start sites. It also delivers information about poly-adenylation sites for transcripts up to 10 kb in length across the full complement of isoforms within targeted genes or the entire transcriptome.
This document describes the Iso-Seq software in SMRT® Analysis v3.0 release, which includes SMRT Link v1.0. Previous Iso-Seq documents can be found in its github wiki.
- Overview
- Manual
- Advanced Analysis Options
- Output Files
- Algorithm Modules
- Diff SMRT Analysis v3.0 vs v2.3
- Handling PacBio RS and PacBio RS II data
- Glossary
Analyses are performed in three stages, CCS, Classify and Cluster. Cluster employs the Iterative Clustering and Error correction (ICE) algorithm. For analyses performed on the command-line, there is an optional tool, Subset, for subsetting the IsoSeq results.
- CCS
- CCS is the first stage of an IsoSeq analysis. CCS builds circular consensus sequences (CCSs) from your subreads. More information about CCS is available here.
- Classify
- Classify is the second stage of an IsoSeq analysis. The key output of Classify is a file of full-length non-chimeric reads, and a file of non-full length reads. The key input of Classify is the circular consensus sequences generated from CCS. Classify will identify and remove polyA/T tails, remove primers, and identify read strandedness. Classify also removes artificial concatemers, but does not remove PCR chimeras.
- Cluster
- Cluster is the third stage of an IsoSeq analysis. The key outputs of Cluster is a file of polished, high-quality consensus sequences, and a file of polished, low-quality consensus sequences. The key input of clustering is the file of full-length non-chimeric reads, and a file of non-full length reads outputted by Classify.
- Subset
- Subset is an optional program which can be used to subset the output files for particular classes of sequences, such as non-chimeric reads, or non-full-length reads.
##Manual
There are three ways to run the Iso-Seq application: Using SMRT Link, on the command line, and on the command line using pbsmrtpipe so that you can run the whole Iso-Seq Analysis with one command given to pbsmrtpipe.
##Running with SMRT Link
To run the Iso-Seq application using SMRT Link, follow the usual steps for analysing data on SMRT Link. TODO: Link to document explaining SMRT Link.
##Running on the Command Line
On the command line, the analysis is performed in 3 steps:
- Run CCS on your subreads, generating a CCS BAM file. Then generate an XML from the BAM file.
- Run Classify on your CCSs with the XML as input, generating a FASTA of annotated sequences.
- Run Cluster on the FASTA produced by Classify, generating polished isoforms.
Step 1. CCS
First, convert your subreads to circular consensus sequences. You can do this with the command:
ccs --noPolish --minLength=300 --minPasses=1 --minZScore=-999 --maxDropFraction=0.8 --minPredictedAccuracy=0.8 --minSnr=4 subreads.bam ccs.bam
Where ccs.bam is where the CCSs will be output, and subreads.bam is the file containing your subreads. CCS options are described in pbccs doc. If you think that you have transcripts of interest that are less than 300 bp in length, be sure to adjust the minLength parameter.
Next, you will generate an XML file from your CCSs. You can do this with the commmand:
dataset create --type ConsensusReadSet ccs.xml ccs.bam
Where ccs.xml is the name of the XML file you are generating and ccs.bam is the name of the BAM file you generated previously using the ccs command.
Step 2. Classify
Classify can be run at the command line as follows:
pbtranscript classify [OPTIONS] ccs.xml isoseq_draft.fasta --flnc=isoseq_flnc.fasta --nfl=isoseq_nfl.fasta
Where ccs.xml is the XML file you generated in Step 1.
Where isoseq_flnc.fasta contains only the full-length, non-chimeric reads.
And where isoseq_nfl.fasta contains all non-full-length reads.
Or you can run classify creating XML files instead of FASTA files as follows:
pbtranscript classify [OPTIONS] ccs.xml isoseq_draft.fasta --flnc=isoseq_flnc.contigset.xml --nfl=isoseq_nfl.contigset.xml
Where ccs.xml is the XML file you generated in Step 1.
Where isoseq_flnc.contigset.xml contains only the full-length, non-chimeric reads.
And where isoseq_nfl.contigset.xml contains all non-full-length reads.
Note: One can always use pbtranscript subset to further subset isoseq_draft.fasta if --flnc and --nfl are not specified when you run pbtranscript classify. For example:
pbtranscript subset isoseq_draft.fasta isoseq_flnc.fasta --FL --nonChimeric
Step 3. Cluster and Polish
cluster can be run at the command line as follows:
pbtranscript cluster [OPTIONS] isoseq_flnc.fasta polished_clustered.fasta --quiver --nfl=isoseq_nfl.fasta --bas_fofn=my.subreadset.xml
Or
pbtranscript cluster [OPTIONS] isoseq_flnc.contigset.xml polished_clustered.contigset.xml --quiver --nfl=isoseq_nfl.contigset.xml --bas_fofn=my.subreadset.xml
Note: --quiver --nfl=isoseq_nfl.fasta|contigset.xml must be specified in order to get Quiver|Arrow polished consensus isoforms.
Optionally, you may call the following command to run ICE and create unpolished consensus isoforms only.
pbtranscript cluster [OPTIONS] isoseq_flnc.fasta unpolished_clustered.fasta
##Running on the Command-Line with pbsmrtpipe
###Install pbsmrtpipe
pbsmrtpipe is a part of smrtanalysis-3.0 package and will be installed
if smrtanalysis-3.0 has been installed on your system. Or you can download pbsmrtpipe and install.
You can verify that pbsmrtpipe is running OK by:
pbsmrtpipe --help
Now create an XML file from your subreads.
dataset create --type SubreadSet --generateIndices my.subreadset.xml subreads1.bam subreads2.bam ...
This will create a file called my.subreadset.xml.
Create a global options XML file which contains SGE related, job chunking and job distribution options that you may modify by:
pbsmrtpipe show-workflow-options -o global_options.xml
Create an Iso-Seq options XML file which contains Iso-Seq related options that you may modify by:
pbsmrtpipe show-template-details pbsmrtpipe.pipelines.sa3_ds_isoseq -o isoseq_options.xml
The entries in the options XML files have the format:
<option id="pbtranscript.task_options.min_seq_len">
<value>300</value>
</option>
Note: If you only want to run Iso-Seq Classify without Cluster, please create an XML for Iso-Seq Classify Only.
pbsmrtpipe show-template-details pbsmrtpipe.pipelines.sa3_ds_isoseq_classify -o isoseq_classify_options.xml
And you can modify options using your favorite text editor, such as vim.
Once you have set your options, you are ready to run the Iso-Seq software application via pbsmrtpipe:
pbsmrtpipe pipeline-id pbsmrtpipe.pipelines.sa3_ds_isoseq -e eid_subread:my.subreadset.xml --preset-xml=isoseq_options.xml --preset-xml=global_options.xml --output-dir=my_run
Where my_run is where the results of your analysis will be stored.
You may modify Iso-Seq advanced analysis parameters for SMRT Link or pbsmrtpipe as follows.
| Module | Parameter | pbsmrtpipe name | Default | Explanation |
|---|---|---|---|---|
| CCS | Max. dropped fraction | max_drop_fraction | 0.08 | Maximum fraction of subreads that can be dropped before giving up. |
| CCS | Minimum length | min_length | 300 | Sets a minimum length requirement for the median size of insert reads in order to generate a consensus sequence. If the targeted template is known to be a particular size range, this can filter out alternative DNA templates. |
| CCS | Minimum Number of Passes | min_passes | 1 | Sets a minimum number of passes for a ZMW to be emitted. This is the number of full passes. Full passes must have an adapter hit before and after the insert sequence and so does not include any partial passes at the start and end of the sequencing reaction. Additionally, the full pass count does not include any reads that were dropped by the Z-Filter. |
| CCS | Minimum Predicted Accuracy | min_predicted_accuracy | 0.8 | The minimum predicted accuracy of a read. CCS generates an accuracy prediction for each read, defined as the expected percentage of matches in an alignment of the consensus sequence to the true read. A value of 0.99 indicates that only reads expected to be 99% accurate are emitted. |
| CCS | Minimum read score | min_read_score | 0.75 | Minimum read score of input subreads. |
| CCS | Minimum SNR | min_snr | 4 | This filter removes data that is likely to contain deletions. SNR is a measure of the strength of signal for all 4 channels (A, C, G, T) used to detect basepair incorporation. The SNR can vary depending on where in the ZMW a SMRTbell™ template stochastically lands when loading occurs. SMRTbell templates that land near the edge and away from the center of the ZMW have a less intense signal, and as a result can contain sequences with more "missed" basepairs. This value sets the threshold for minimum required SNR for any of the four channels. Data with SNR < 3.75 is typically considered lower quality. |
| CCS | Minimum Z Score | min_zscore | -9999 | The minimum Z-Score for a subread to be included in the consensus generating process. |
| Classify | Ignore polyA | ignore_polya | FALSE | Full-Length criteria does not require polyA tail. By default this is off, which means that polyA tails are required for a sequence to be considered full length. When it is turned on, sequences do not need polyA tails to be considered full length. |
| Classify | Min. seq. length | min_seq_len | 300 | Minimum sequence length to output. |
| Cluster | Minimum Quiver | Arrow Accuracy | hq_quiver_min_accuracy | 0.99 |
| Cluster-Polish | Trim QVs 3' | qv_trim_3p | 30 | Ignore QV of n bases in the 3' end. |
| Cluster-Polish | Trim QVs 5' | qv_trim_5p | 100 | Ignore QV of n bases in the 5' end. |
| Maximum Length (max_length) | --maxLength=15000 | Maximum length of subreads to use for generating CCS. Default = 7000 | ||
| No Polish (no_polish) | --noPolish | Only output the initial template derived from the POA (faster, less accurate). |
Note: The Iso-Seq Classify Only protocol does not perform isoform-level clustering and only uses a subset of advanced analysis parameters.
In order to display Classify advanced options via command line: pbtranscript classify --help.
| Type | Parameter | Example | Explanation |
|---|---|---|---|
| positional | readsFN | ccs.bam,xml,fasta | First positional argument. It specifies input CCS reads in BAM, dataset XML, or FASTA format. |
| positional | outReadsFN | isoseq_draft.fasta,contigset.xml | Second positional argument. Output file which contains all classified reads in FASTA or contigset XML format. |
| optional | Help | -h, --help | This prints the help message. |
| optional | Full-Length Non-Chimeric | --flnc FLNC_FA.fasta,contigset.xml | Outputs full-length non-chimeric reads in fasta or contigset XML format. |
| optional | Output Non-Full-Length | --nfl NFL_FA.fasta | Outputs non-full-length reads in FASTA or contigset XML format. |
| HMMER | HMMER Directory | -d OUTDIR, --outDir OUTDIR | Directory to store HMMER output (default: output/). |
| HMMER | Summary | -summary out.classify_summary.txt | TXT file to output classify summary (default: out.classify_summary.txt). |
| HMMER | Primers File | -p primers.fa, --primer primers.fa | Primer FASTA file (default: primers.fa). |
| HMMER | Primers Report | --report out.primer_info.csv | CSV file of primer info. Contains the same info found in the description lines of the output FASTA (default: out.primer_info.csv). |
| HMMER | CPUs | --cpus CPUS | Number of CPUs to run HMMER (default: 8). |
| Chimera-detection | Minimum Sequence Length | --min_seq_len MIN_SEQ_LEN | Minimum CCS length to be analyzed. Fragments shorter than minimum sequence length are excluded from analysis (default: 300). |
| Chimera-detection | Minimum PHMMER Score | --min_score MIN_SCORE | Minimum phmmer score for primer hit (default: 10). |
| Chimera-detection | Non-Full-Length Chimeras | --detect_chimera_nfl | Detect chimeric reads among non-full-length reads. Non-full-length non-chimeric/chimeric reads will saved to outDir/nflnc.fasta and outDir/nflc.fasta. |
| Read-Extraction | Ignore polyA | --ignore_polyA | Full-Length criteria does not require polyA tail. By default this is off, which means that polyA tails are required for a sequence to be considered full length. When it is turned on, sequences do not need polyA tails to be considered full length. |
In order to show Iso-Seq Cluster advanced options via command line: pbtranscript cluster.
| Type | Parameter | Example | Explanation |
|---|---|---|---|
| positional | Input Reads | isoseq_flnc.fasta,contigset.xml | Input full-length non-chimeric reads in FASTA or contigset XML format. Used for clustering consensus isoforms. |
| positional | Output Isoforms | out.fasta,congitset.xml | Output predicted (unpolished) consensus isoforms in FASTA file. |
| optional | Help | -h, --help | This prints the help message. |
| optional | Input Non-Full-Length | --nfl_fa isoseq_nfl.fasta | Input non-full-length reads in FASTA format, used for polishing consensus isoforms. |
| optional | CCS QVs FOFN | --ccs_fofn ccs.fofn | A ccs.fofn or ccs.bam or ccs.xml file. If not given, Cluster assumes there is no QV information available. |
| optional | Reads QVs FOFN | --bas_fofn my.subreadset.xml | A file which provides quality values of raw reads and subreads. Can be either a FOFN of BAM or BAX files, or a dataset XML. |
| optional | Output Directory | -d output/, --outDir output/ | Directory to store temporary and output cluster files (default: output/). |
| optional | Temp Directory | --tmp_dir tmp/ | Directory to store temporary files (default: tmp/). |
| optional | Summary | --summary my.cluster_summary.txt | TXT file to output cluster summary (default: my.cluster_summary.txt). |
| optional | Report | --report report.csv | A CSV file, each line containing a cluster, an associated read of the cluster, and the read type. |
| optional | Pickle | --pickle_fn PICKLE_FN | Developers' option from which all clusters can be reconstructed. |
| ICE | cDNA | --cDNA_size {under1k,between1k2k,between2k3k,above3k} | Estimated cDNA size. |
| ICE | Quiver | --quiver | Call Quiver or Arrow to polish consensus isoforms using non-full-length non-chimeric CCS reads. |
| ICE | Finer Quiver or Arrow | --use_finer_qv | Use finer classes of QV information from CCS input instead of a single QV from FASTQ. This option is slower and consumes more memory. |
| SGE | Run SGE | --use_sge | Instructs Cluster to use SGE. |
| SGE | Maximum SGE Jobs | --max_sge_jobs MAX_SGE_JOBS | The maximum number of jobs that will be submitted to SGE concurrently. |
| SGE | SGE Job ID | --unique_id UNIQUE_ID | Unique ID for submitting SGE jobs. |
| SGE | BLASR Cores | --blasr_nproc BLASR_NPROC | Number of cores for each BLASR job. |
| SGE | Quiver or Arrow CPUs | --quiver_nproc QUIVER_NPROC | Number of CPUs each quiver or Arrow job uses. |
| IceQuiver High QV/Low QV | Minimum Quiver or Arrow Accuracy | --hq_quiver_min_accuracy HQ_QUIVER_MIN_ACCURACY | Minimum allowed quiver or Arrow accuracy to classify an isoform as hiqh-quality. |
| IceQuiver High QV/Low QV | Trim QVs 5' | --qv_trim_5 QV_TRIM_5 | Ignore QV of n bases in the 5' end. |
| IceQuiver High QV/Low QV | Trim QVs 3' | --qv_trim_3 QV_TRIM_3 | Ignore QV of n bases in the 3' end. |
| IceQuiver High QV/Low QV | High-Quality Isoforms FASTA | --hq_isoforms_fa output/all_quivered_hq.fa | Quiver or Arrow polished, high-quality isoforms in FASTA (default: output/all_quivered_hq.fa). |
| IceQuiver High QV/Low QV | High-Quality Isoforms FASTQ | --hq_isoforms_fq output/all_quivered_hq.fq | Quiver or Arrow polished, high-quality isoforms in FASTQ (default: output/all_quivered_hq.fq). |
| IceQuiver High QV/Low QV | Low-Quality Isoforms FASTA | --lq_isoforms_fa output/all_quivered_lq.fa | Quiver or Arrow polished, low-quality isoforms in FASTA (default: output/all_quivered_lq.fa). |
| IceQuiver High QV/Low QV | Low-Quality Isoforms FASTQ | --lq_isoforms_fq output/all_quivered_lq.fq | Quiver or Arrow polished, low-quality isoforms in FASTQ (default: output/all_quivered_lq.fq). |
In order to show pbtranscript Subset options via command line: pbtranscript subset.
| Type | Parameter | Example | Explanation |
|---|---|---|---|
| positional | Input Sequences | isoseq_draft.fasta | Input FASTA file. |
| positional | Output Sequences | isoseq_subset.fasta | Output FASTA file. |
| optional | Help | -h, --help | This prints the help message. |
| optional | Output Full-length | --FL | Reads to output must be Full-Length, with 3' primer and 5' primer and polyA tail seen. |
| optional | Output Non-Full-length | --nonFL | Reads to output must be Non-Full-Length reads. |
| optional | Output Non-Chimeric | --nonChimeric | Reads to output must be non-chimeric reads. |
| optional | Output Read-Length | --printReadLengthOnly | Only print read lengths, no read names and sequences. |
| optional | Ignore polyA Tails | --ignore_polyA | Full-Length criteria does not require polyA tail. By default this is off, which means that polyA tails are required for a sequence to be considered full length. When it is turned on, sequences do not need polyA tails to be considered full length. |
Classify FASTA Output (isoseq*.fasta)_
isoseq_flnc.fasta contains all full-length, non-artificial-concatemer reads.
isoseq_nfl.fasta contains all non-full-length reads.
isoseq_draft.fasta is an intermediate file in order to get full-length reads, which you can ignore.
Reads in these FASTA files look like the following:
>m140121_100730_42141_c100626750070000001823119808061462_s1_p0/119/30_1067_CCS strand=+;fiveseen=1;polyAseen=1;threeseen=1;fiveend=30;polyAend=1067;threeend=1096;primer=1;chimera=0
ATAAGACGACGCTATATG
These lines have the format:
<movie_name>/<ZMW>/<start>_<end>_CCS INFO
The info fields are:
- strand: either + or -, whether a read is forward or reverse-complement cDNA,
- fiveseen: whether or not 5' prime is seen in this read, 1 yes, 0 no
- polyAseen: whether or not poly A tail is seen, 1 yes, 0 no
- threeseen: whether or not 3' prime is seen, 1 yes, 0 no
- fiveend: start position of 5'
- threeend: start position of 3' in read
- polyAend: start position of polyA in read
- primer: index of primer seen in this read (remember primer fasta file >F0 xxxxx >R0 xxxxx >F1 xxxxx >R1 xxxx)
- chimera: whether or not this read is classified as a chimeric cdna
Note: Reads in isoseq-flnc.fasta are always strand-specific. That is, the 5' and 3' primer (and sometimes the polyA tail) are used to tell whether the read is in the right strand. If needed, the scripts described here reverse-complement the original read and produce the sequence that is supposed to be the transcript. Non-full-length reads in isoseq_nfl.fasta on the other hand, could be in either orientation.
Summary (classify_summary.txt) This file contains the following statistics:
- Number of reads of insert
- Number of five prime reads
- Number of three prime reads
- Number of poly-A reads
- Number of filtered short reads
- Number of non-full-length reads
- Number of full-length reads
- Number of full-length non-chimeric reads
- Average full-length non-chimeric read length
Note: By seeing that the number of full-length, non-chimeric (flnc) reads is only a little less than the number of full-length reads, we can confirm that the number of artificial concatemers is very low. This indicates a successful SMRTbell library prep.
##Cluster Output Files
Summary (cluster_summary.txt) This file contains the following statistics:
- Number of consensus isoforms
- Average read length of consensus isoforms
Report (cluster_report.csv) This is a csv file each line of which contains the following fields:
- cluster_id: ID of a consensus isoforms from ICE.
- read_id : ID of a read which supports the consensus isoform.
- read_type : Type of the supportive read
CCS
pbccs is a tool to create circular consensus sequences (CCS) sequence
from raw subreads for PacBio sequences. See pbccs doc for usage.
Classify
Iso-Seq Classify classifies reads into full-length or non-full-length reads, artifical-concatemer chimeric or non-chimeric read.
In order to classify a read as full-length or non-full-length, we search for primers and polyA within reads. If and only if both primers and polyAs are seen in a read, we classify it as a full-length read. Otherwise, we classify the read as non-full-length. We also remove primers and polyAs from reads and identify read strandedness based on this information.
Note: The current version of the Iso-Seq application in SMRT Link 1.0 by default recognizes Clontech SMARTer primers.
Note: In SMRT Link 1.0, custom primers are NOT supported. In order to use custom primers, You must call pbtranscript from command line like
pbtranscript classify --primer your_primer_fasta ...
Where your_primer_fasta is a FASTA file with the following format:
>F0
5' sequence here
>R0
3' sequence here (but in reverse complement)
Next, we further look into full-length reads and classify them into artificial-concatemer chimeric reads or non-chimeric reads by locating primer hits within reads.
- HMMER: We use
phmmerin HMMER package to detect locations of primer hits within reads and classify reads which have primer hits in the middle of sequences as artificial-concatemer chimeric.
Cluster
Iso-Seq Cluster performs isoform-level clustering using the Iterative Clustering
and Error correction (ICE) algorithm, which iteratively classifies full-length
non-chimeric CCS reads into clusters and builds consensus sequences of
clusters using pbdagcon.
ICE is customized to work well on alternative isoforms and alternative polyadenlynation sites, but not on SNP analysis and SNP based highly complex gene families.
For a detailed explanation of ICE, please refer to the Iso-Seq webinar recording and slides.
- pbdagcon:
pdagconis a tool which builds consensus sequences using Directed Acyclic Graph Consensus.
Polish
Iso-Seq Polish further polishes consensus sequenecs of clusters (i.e., pbdagcon output)
taking into account all the QV information.
We assign not only full-length non-chimeric CCS reads but also non-full-length CCS
reads into clusters based on similarity. Then for each cluster, we align raw subreads
of its assigned ZMWs towards its consensus sequence. Finally, we load quality values
to these alignments and polish the consensus sequence using Quiver or Arrow.
- Quiver:
Quiver|Arrowis a consensus and variant-calling algorithm for PacBio reads.QuiverorArrowfinds the maximum likelihood template sequence given PacBio reads of the template. It is used by the Iso-Seq application to polish consensus isoforms.Quiver|Arrowuses quality values and creates higher-quality consensus sequence comapred withpbdagcon, but is more time-consuming.
The output of the Sequel™ instruments is BAM format, while the output of the PacBio RS and PacBio RS II instruments is bax.h5. Major differences between Iso-Seq software in SMRT Analysis v3.0 and Iso-Seq software in SMRT Analysis v2.3 are listed in the table below.
Note: Functions of Iso-Seq Analysis have NOT been changed since v2.3, and Iso-Seq Tofu has NOT been integrated.
| Iso-Seq Application in SMRT Analysis v3.0 | Iso-Seq Application in SMRT Analysis v2.3 |
|---|---|
| SMRT Analysis Web Server: SMRT Link | SMRT Analysis Web Server: SMRT Portal |
| Works on data from Sequel instrument | Works on data from PacBio RS and RS II |
| Input PacBio reads are stored in BAM | Input PacBio reads are stored in bax.h5 format |
| Supports PacBio DataSet | Does NOT support PacBio Dataset |
| Uses new algorithm pbccs to create CCS reads | Uses ConsensusTools.sh to create CCS reads |
| Does NOT support using customer primers from SMRT Link | Supports using customer primers from SMRT Portal |
Does NOT support using GMAP to align consensus isoforms to reference from SMRT Link |
Supports using GMAP to align consensus isoforms to reference from SMRT Portal |
SMRT Link has two protocols: IsoSeq Classify Only and IsoSeq. The IsoSeq Classify Only protocol only classifies reads, while the IsoSeq protocol not only classifies reads but also generates consensus isoforms using ICE and polish them using Quiver or Arrow. |
SMRT Portal has one protocol: RS_IsoSeq, which provides options such that users can calssify reads, or run ICE and generate unpolished consensus isoforms or polish consensus isoforms using Quiver or Arrow. |
##Handling PacBio RS and PacBio RS II data
If you want to run the Iso-Seq application on existing PacBio RS or PacBio RS II data, you will need to convert reads in bax.h5 files to BAM files.
Converting PacBio RS and PacBio RS II data to BAM with SMRT Link
TODO: points to SMRT Link Doc.
Converting PacBio RS and PacBio RS II data to BAM from command line
bax2bam -o mynewbam mydata.1.bax.h5 mydata.2.bax.h5 mydata.3.bax.h5
-
Chimera
- Iso-Seq Classify classifies reads as artificial-concatemer chimeric or non-chimeric based on whether or not primers are found in the middle of the sequence.
-
High QV | Low QV
- Iso-Seq Cluster generates polished consensus isoforms are classified into either high-quality or low-quality isoforms. We classify an isoform as high quality if its consensus accuracy is no less than a cut-off, otherwise low quality. The default cut-off is 0.99. You may change this value from command line, or via SMRT Link Advanced Analysis Parameters when creating an Iso-Seq job.
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