> ## Documentation Index
> Fetch the complete documentation index at: https://opensre.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Start monitoring your first pipelines in minutes

export const CodePreview = ({filename, language, code, totalLines, githubUrl}) => {
  const [copied, setCopied] = React.useState(false);
  const handleCopy = () => {
    navigator.clipboard.writeText(code);
    setCopied(true);
    setTimeout(() => setCopied(false), 2000);
  };
  return <div style={{
    backgroundColor: '#1a1a1a',
    border: '1px solid #333',
    borderRadius: '0.125rem',
    overflow: 'hidden',
    marginTop: '1rem',
    marginBottom: '1rem'
  }}>
      <div style={{
    display: 'flex',
    alignItems: 'center',
    justifyContent: 'space-between',
    padding: '12px 16px',
    backgroundColor: '#1a1a1a',
    borderBottom: '1px solid #333'
  }}>
        <span style={{
    fontFamily: 'Monaco, Menlo, Ubuntu Mono, Consolas, source-code-pro, monospace',
    fontSize: '13px',
    color: '#c9d1d9',
    fontWeight: '400'
  }}>
          {filename}
        </span>
        <button onClick={handleCopy} style={{
    background: 'transparent',
    border: 'none',
    cursor: 'pointer',
    padding: '6px',
    display: 'flex',
    alignItems: 'center',
    justifyContent: 'center'
  }} aria-label="Copy code">
          <svg width="18" height="18" viewBox="0 0 18 18" fill="none" xmlns="http://www.w3.org/2000/svg" style={{
    color: copied ? '#22c55e' : 'rgba(255, 255, 255, 0.4)',
    stroke: copied ? '#22c55e' : 'currentColor',
    fill: 'none',
    transition: 'color 0.2s ease'
  }}>
            {copied ? <path d="M15 5L7 13L3 9" stroke="currentColor" strokeWidth="1.5" strokeLinecap="round" strokeLinejoin="round" /> : <>
                <path d="M14.25 5.25H7.25C6.14543 5.25 5.25 6.14543 5.25 7.25V14.25C5.25 15.3546 6.14543 16.25 7.25 16.25H14.25C15.3546 16.25 16.25 15.3546 16.25 14.25V7.25C16.25 6.14543 15.3546 5.25 14.25 5.25Z" stroke="currentColor" strokeWidth="1.5" strokeLinecap="round" strokeLinejoin="round" />
                <path d="M2.80103 11.998L1.77203 5.07397C1.61003 3.98097 2.36403 2.96397 3.45603 2.80197L10.38 1.77297C11.313 1.63397 12.19 2.16297 12.528 3.00097" stroke="currentColor" strokeWidth="1.5" strokeLinecap="round" strokeLinejoin="round" />
              </>}
          </svg>
        </button>
      </div>
    <div style={{
    position: 'relative',
    maxHeight: '200px',
    overflow: 'hidden',
    backgroundColor: '#1a1a1a'
  }}>
      <div style={{
    padding: '16px',
    fontFamily: 'Monaco, Menlo, Ubuntu Mono, Consolas, source-code-pro, monospace',
    fontSize: '14px',
    lineHeight: '1.6',
    color: '#c9d1d9',
    backgroundColor: '#1a1a1a'
  }}>
        <pre style={{
    margin: 0,
    padding: 0,
    background: 'transparent',
    border: 'none',
    whiteSpace: 'pre',
    overflow: 'visible'
  }}>
          <code className={`language-${language}`} style={{
    background: 'transparent',
    padding: 0,
    fontSize: '14px'
  }}>
{code}
          </code>
        </pre>
      </div>
      <div style={{
    position: 'absolute',
    bottom: 0,
    left: 0,
    right: 0,
    height: '80px',
    background: 'linear-gradient(to bottom, transparent, #1a1a1a)',
    pointerEvents: 'none'
  }}></div>
    </div>
    <a href={githubUrl} target="_blank" rel="noopener noreferrer" style={{
    display: 'flex',
    alignItems: 'center',
    gap: '6px',
    padding: '10px 16px',
    backgroundColor: '#1a1a1a',
    borderTop: '1px solid #333',
    color: '#8b949e',
    fontSize: '13px',
    textDecoration: 'none',
    transition: 'background-color 0.2s ease',
    boxSizing: 'border-box',
    height: '41px'
  }} onMouseEnter={e => {
    e.currentTarget.style.backgroundColor = '#161b22';
    e.currentTarget.style.textDecoration = 'none';
  }} onMouseLeave={e => {
    e.currentTarget.style.backgroundColor = '#1a1a1a';
    e.currentTarget.style.textDecoration = 'none';
  }}>
      <span style={{
    textDecoration: 'none'
  }}>...</span>
      <span style={{
    textDecoration: 'none'
  }}>See all {totalLines} lines</span>
    </a>
  </div>;
};

## 2 minutes walkthrough

Tracer runs anywhere from the OS, just follow the steps below:

<Note>Use the Tracer CLI and dashboard below to start tracking your pipelines in minutes.</Note>

<Steps>
  <Step icon="https://mintcdn.com/tracer/qjOJrE6rm6eykCOz/images/logo/tracer/Tracer-Head-Black.png?fit=max&auto=format&n=qjOJrE6rm6eykCOz&q=85&s=b86a4e1eb150f63a684f4652b7c7e2ab" title="Step 1: Install Tracer - Only One Line of Code" width="200" height="200" data-path="images/logo/tracer/Tracer-Head-Black.png">
    ```bash theme={null}
    curl -sSL https://install.tracer.cloud | sh -s
    ```
  </Step>

  <Step icon="key" title="Step 2: Authenticate with Tracer">
    ```bash theme={null}
    sudo tracer login
    ```

    <Info>This will open up a browser window to log in to your Tracer account.</Info>
  </Step>

  <Step icon="rocket" title="Step 3: Initialize Pipeline Tracking">
    ```bash theme={null}
    sudo tracer init
    ```

    You will be prompted to configure the pipeline name. Filling this out ensures that each pipeline is uniquely identifiable, customizable, and easy to search later on.

    <div
      style={{
backgroundColor: 'rgba(96, 165, 250, 0.15)',
border: '1px solid rgba(96, 165, 250, 0.4)',
borderRadius: '8px',
padding: '18px 20px',
marginTop: '16px'
}}
    >
      <div style={{ display: 'flex', alignItems: 'flex-start', gap: '14px' }}>
        <div
          style={{
  flexShrink: 0,
  paddingTop: '2px'
}}
        >
          <svg xmlns="http://www.w3.org/2000/svg" width="22" height="22" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2" strokeLinecap="round" strokeLinejoin="round">
            <path d="M15 14c.2-1 .7-1.7 1.5-2.5 1-.9 1.5-2.2 1.5-3.5A6 6 0 0 0 6 8c0 1 .2 2.2 1.5 3.5.7.7 1.3 1.5 1.5 2.5" />

            <path d="M9 18h6" />

            <path d="M10 22h4" />
          </svg>
        </div>

        <div style={{ flex: 1 }}>
          <div
            style={{
    fontWeight: '700',
    fontSize: '1.15em',
    marginBottom: '10px'
  }}
            className="dark:text-white text-black"
          >
            Tracer is now tracking your pipeline.
          </div>

          <div style={{ marginBottom: '10px' }}>
            Every run you launch for this pipeline will be automatically monitored.
          </div>

          <div>
            <strong>Note:</strong> You will only need to run <code className="dark:!text-blue-300 !text-blue-600" style={{
                              backgroundColor: 'rgba(96, 165, 250, 0.2)',
                              padding: '2px 6px',
                              borderRadius: '4px',
                              fontSize: '0.9em'
                            }}>tracer init</code> again for a new pipeline, not per pipeline run.
          </div>
        </div>
      </div>
    </div>
  </Step>

  <Step icon="radar" title="Step 4: Launch (y)our pipeline">
    ```bash theme={null}
    sudo tracer demo
    ```

    Alternatively: Run your usual command (Nextflow, Snakemake, WDL, etc.)<br />Tracer works automatically once the agent is active.

    Watch your pipeline run in the [Tracer dashboard](https://app.tracer.cloud/).

    <CodePreview
      filename="fastquorum.nf"
      language="groovy"
      totalLines={240}
      githubUrl="https://github.com/nf-core/fastquorum/blob/master/workflows/fastquorum.nf"
      code={`/*
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
IMPORT MODULES / SUBWORKFLOWS / FUNCTIONS
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
*/

include { paramsSummaryMap } from 'plugin/nf-schema'
include { paramsSummaryMultiqc } from '../subworkflows/nf-core/utils_nfcore_pipeline'
include { softwareVersionsToYAML } from '../subworkflows/nf-core/utils_nfcore_pipeline'
include { methodsDescriptionText } from '../subworkflows/local/utils_nfcore_fastquorum_pipeline'

include { ALIGN_BAM as ALIGN_RAW_BAM } from '../modules/local/align_bam/main'
include { ALIGN_BAM as ALIGN_CONSENSUS_BAM } from '../modules/local/align_bam/main'
include { FASTQC } from '../modules/nf-core/fastqc/main'
include { FGBIO_FASTQTOBAM as FASTQTOBAM } from '../modules/local/fgbio/fastqtobam/main'
include { FGBIO_GROUPREADSBYUMI as GROUPREADSBYUMI } from '../modules/local/fgbio/groupreadsbyumi/main'
include { FGBIO_CALLMOLECULARCONSENSUSREADS as CALLMOLECULARCONSENSUSREADS } from '../modules/local/fgbio/callmolecularconsensusreads/main'
include { FGBIO_CALLDDUPLEXCONSENSUSREADS as CALLDDUPLEXCONSENSUSREADS } from '../modules/local/fgbio/callduplexconsensusreads/main'
include { FGBIO_FILTERCONSENSUSREADS as FILTERCONSENSUSREADS } from '../modules/local/fgbio/filterconsensusreads/main'
include { FGBIO_COLLECTDUPLEXSEQMETRICS as COLLECTDUPLEXSEQMETRICS } from '../modules/local/fgbio/collectduplexseqmetrics/main'
include { FGBIO_CALLANDFILTERMOLECULARCONSENSUSREADS as CALLANDFILTERMOLECULARCONSENSUSREADS } from '../modules/local/fgbio/callandfiltermolecularconsensusreads/main'
include { FGBIO_CALLANDFILTERDUPLEXCONSENSUSREADS as CALLANDFILTERDUPLEXCONSENSUSREADS } from '../modules/local/fgbio/callandfilterduplexconsensusreads/main'
include { SAMTOOLS_MERGE as MERGE_BAM } from '../modules/nf-core/samtools/merge/main'

include { MULTIQC } from '../modules/nf-core/multiqc/main'

/*
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
RUN MAIN WORKFLOW
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
*/

workflow FASTQUORUM {
take:
params // NB: must pass params; see https://github.com/nextflow-io/nextflow/issues/4982
ch_samplesheet
ch_bwa
ch_dict
ch_fasta
ch_fasta_fai

main:

// To gather all QC reports for MultiQC
ch_versions = Channel.empty()
ch_multiqc_files = Channel.empty()
//
// MODULE: Run FastQC
//
FASTQC(
    ch_samplesheet
)
ch_versions = ch_versions.mix(FASTQC.out.versions.first())
ch_multiqc_files = ch_multiqc_files.mix(FASTQC.out.zip.collect { it[1] })

//
// MODULE: Run fgbio FastqToBam
//
FASTQTOBAM(ch_samplesheet)
ch_versions = ch_versions.mix(FASTQTOBAM.out.versions.first())

//
// MODULE: Align with bwa mem
//
ALIGN_RAW_BAM(FASTQTOBAM.out.bam, ch_fasta, ch_fasta_fai, ch_dict, ch_bwa, "template-coordinate")
ch_versions = ch_versions.mix(ALIGN_RAW_BAM.out.versions.first())

//
// Create a channel that:
// 1. Groups the aligned BAMs by sample identifier.  We use \`groupKey\` here since we know how many BAMs each
//    sample expects to have.  Typically a sample has more than one BAM if it had multiple runs or lanes.
// 2. Splits the samples into those that have more than one BAM, and those that have exactly one BAM.  The former
//    samples will have their BAMs merged.
//
// The \`n_samples\` is added by \`validateInputSamplesheet\` method in \`PIPELINE_INITIALISATION\` workflow
// NB: bam is a list (of one BAM) so return just the one BAM
bam_to_merge = ALIGN_RAW_BAM.out.bam
    .map { meta, bam ->
        [groupKey(meta, meta.n_samples), bam]
    }
    .groupTuple()
    .branch { meta, bam ->
        single: meta.n_samples <= 1
        return [meta, bam[0]]
        multiple: meta.n_samples > 1
    }

//
// MODULE: Run samtools merge to merge across runs/lanes for the same sample
//
MERGE_BAM(bam_to_merge.multiple, [[], []], [[], []])
ch_versions = ch_versions.mix(MERGE_BAM.out.versions.first())

//
// Create a channel that contains the merged BAMs and those that did not need to be merged.
//
bam_all = MERGE_BAM.out.bam.mix(bam_to_merge.single)

//
// MODULE: Run fgbio GroupReadsByUmi
//
GROUPREADSBYUMI(bam_all, params.groupreadsbyumi_strategy, params.groupreadsbyumi_edits)
ch_multiqc_files = ch_multiqc_files.mix(GROUPREADSBYUMI.out.histogram.map { it[1] }.collect())
ch_versions = ch_versions.mix(GROUPREADSBYUMI.out.versions.first())

if (params.duplex_seq) {
    //
    // MODULE: Run fgbio CollectDuplexSeqMetrics
    //
    COLLECTDUPLEXSEQMETRICS(GROUPREADSBYUMI.out.bam)
    ch_versions = ch_versions.mix(COLLECTDUPLEXSEQMETRICS.out.versions.first())
}

// TODO: duplex_seq can be inferred from the read structure, but that's out of scope for now
if (params.mode == 'rd') {
    if (params.duplex_seq) {
        //
        // MODULE: Run fgbio CallDuplexConsensusReads
        //
        CALLDDUPLEXCONSENSUSREADS(GROUPREADSBYUMI.out.bam, params.call_min_reads, params.call_min_baseq)
        ch_versions = ch_versions.mix(CALLDDUPLEXCONSENSUSREADS.out.versions.first())

        // Add the consensus BAM to the channel for downstream processing
        CALLDDUPLEXCONSENSUSREADS.out.bam.set { ch_consensus_bam }
    }
    else {
        //
        // MODULE: Run fgbio CallMolecularConsensusReads
        //
        CALLMOLECULARCONSENSUSREADS(GROUPREADSBYUMI.out.bam, params.call_min_reads, params.call_min_baseq)
        ch_versions = ch_versions.mix(CALLMOLECULARCONSENSUSREADS.out.versions.first())

        // Add the consensus BAM to the channel for downstream processing
        CALLMOLECULARCONSENSUSREADS.out.bam.set { ch_consensus_bam }
    }

    //
    // MODULE: Align with bwa mem
    //
    ALIGN_CONSENSUS_BAM(ch_consensus_bam, ch_fasta, ch_fasta_fai, ch_dict, ch_bwa, "none")
    ch_versions = ch_versions.mix(ALIGN_CONSENSUS_BAM.out.versions.first())

    //
    // MODULE: Run fgbio FilterConsensusReads
    //
    FILTERCONSENSUSREADS(ALIGN_CONSENSUS_BAM.out.bam, ch_fasta, params.filter_min_reads, params.filter_min_baseq, params.filter_max_base_error_rate)
    ch_versions = ch_versions.mix(FILTERCONSENSUSREADS.out.versions.first())
}
else {
    if (params.duplex_seq) {
        //
        // MODULE: Run fgbio CallDuplexConsensusReads and fgbio FilterConsensusReads
        //
        CALLANDFILTERDUPLEXCONSENSUSREADS(GROUPREADSBYUMI.out.bam, ch_fasta, ch_fasta_fai, params.call_min_reads, params.call_min_baseq, params.filter_max_base_error_rate)
        ch_versions = ch_versions.mix(CALLANDFILTERDUPLEXCONSENSUSREADS.out.versions.first())

        // Add the consensus BAM to the channel for downstream processing
        CALLANDFILTERDUPLEXCONSENSUSREADS.out.bam.set { ch_consensus_bam }
    }
    else {
        //
        // MODULE: Run fgbio CallMolecularConsensusReads and fgbio FilterConsensusReads
        //
        CALLANDFILTERMOLECULARCONSENSUSREADS(GROUPREADSBYUMI.out.bam, ch_fasta, ch_fasta_fai, params.call_min_reads, params.call_min_baseq, params.filter_max_base_error_rate)
        ch_versions = ch_versions.mix(CALLANDFILTERMOLECULARCONSENSUSREADS.out.versions.first())

        // Add the consensus BAM to the channel for downstream processing
        CALLANDFILTERMOLECULARCONSENSUSREADS.out.bam.set { ch_consensus_bam }
    }

    //
    // MODULE: Align with bwa mem
    //
    ALIGN_CONSENSUS_BAM(ch_consensus_bam, ch_fasta, ch_fasta_fai, ch_dict, ch_bwa, "coordinate")
    ch_versions = ch_versions.mix(ALIGN_CONSENSUS_BAM.out.versions.first())
}

//
// Collate and save software versions
//
softwareVersionsToYAML(ch_versions)
    .collectFile(
        storeDir: "\${params.outdir}/pipeline_info",
        name: 'nf_core_' + 'fastquorum_software_' + 'mqc_' + 'versions.yml',
        sort: true,
        newLine: true,
    )
    .set { ch_collated_versions }


//
// MODULE: MultiQC
//
ch_multiqc_config = Channel.fromPath(
    "\${projectDir}/assets/multiqc_config.yml",
    checkIfExists: true
)
ch_multiqc_custom_config = params.multiqc_config
    ? Channel.fromPath(params.multiqc_config, checkIfExists: true)
    : Channel.empty()
ch_multiqc_logo = params.multiqc_logo
    ? Channel.fromPath(params.multiqc_logo, checkIfExists: true)
    : Channel.empty()

summary_params = paramsSummaryMap(
    workflow,
    parameters_schema: "nextflow_schema.json"
)
ch_workflow_summary = Channel.value(paramsSummaryMultiqc(summary_params))
ch_multiqc_files = ch_multiqc_files.mix(
    ch_workflow_summary.collectFile(name: 'workflow_summary_mqc.yaml')
)
ch_multiqc_custom_methods_description = params.multiqc_methods_description
    ? file(params.multiqc_methods_description, checkIfExists: true)
    : file("\${projectDir}/assets/methods_description_template.yml", checkIfExists: true)
ch_methods_description = Channel.value(
    methodsDescriptionText(ch_multiqc_custom_methods_description)
)

ch_multiqc_files = ch_multiqc_files.mix(ch_collated_versions)
ch_multiqc_files = ch_multiqc_files.mix(
    ch_methods_description.collectFile(
        name: 'methods_description_mqc.yaml',
        sort: true,
    )
)

MULTIQC(
    ch_multiqc_files.collect(),
    ch_multiqc_config.toList(),
    ch_multiqc_custom_config.toList(),
    ch_multiqc_logo.toList(),
    [],
    [],
)

emit:
multiqc_report = MULTIQC.out.report.toList() // channel: /path/to/multiqc_report.html
versions = ch_versions // channel: [ path(versions.yml) ]
}`}
    />
  </Step>
</Steps>

See all our environment specific guides below:

| [Linux (Cloud)](/environments/linux-cloud) | [macOS](/environments/macos) | [AWS Batch](/environments/aws-batch) | [Linux (Local)](/environments/linux-local) | [Docker](/environments/docker) | [Windows](/environments/windows-local) |
| :----------------------------------------: | :--------------------------: | :----------------------------------: | :----------------------------------------: | :----------------------------: | :------------------------------------: |

Let's start monitoring!