diff --git a/.deprecated/align-minimap.smk b/.deprecated/align-minimap.smk
deleted file mode 100644
index 54e9752f7..000000000
--- a/.deprecated/align-minimap.smk
+++ /dev/null
@@ -1,345 +0,0 @@
-containerized: "docker://pdimens/harpy:latest"
-
-import os
-import re
-import sys
-from rich.panel import Panel
-from rich import print as rprint
-
-outdir      = config["output_directory"]
-envdir      = os.path.join(os.getcwd(), ".harpy_envs")
-genomefile 	= config["inputs"]["genome"]
-fqlist      = config["inputs"]["fastq"]
-extra 		= config.get("extra", "") 
-bn 			= os.path.basename(genomefile)
-genome_zip  = True if bn.lower().endswith(".gz") else False
-bn_idx      = f"{bn}.gzi" if genome_zip else f"{bn}.fai"
-envdir      = os.getcwd() + "/.harpy_envs"
-windowsize  = config["depth_windowsize"]
-skipreports = config["skipreports"]
-windowsize  = config["depth_windowsize"]
-molecule_distance = config["molecule_distance"]
-
-wildcard_constraints:
-    sample = "[a-zA-Z0-9._-]+"
-
-onerror:
-    print("")
-    rprint(
-        Panel(
-            f"The workflow has terminated due to an error. See the log file below for more details.",
-            title = "[bold]harpy align minimap",
-            title_align = "left",
-            border_style = "red"
-            ),
-        file = sys.stderr
-    )
-
-onsuccess:
-    print("")
-    rprint(
-        Panel(
-            f"The workflow has finished successfully! Find the results in [bold]{outdir}[/bold]",
-            title = "[bold]harpy align minimap",
-            title_align = "left",
-            border_style = "green"
-            ),
-        file = sys.stderr
-    )
-
-bn_r = r"([_\.][12]|[_\.][FR]|[_\.]R[12](?:\_00[0-9])*)?\.((fastq|fq)(\.gz)?)$"
-samplenames = {re.sub(bn_r, "", os.path.basename(i), flags = re.IGNORECASE) for i in fqlist}
-d = dict(zip(samplenames, samplenames))
-
-def get_fq(wildcards):
-    # returns a list of fastq files for read 1 based on *wildcards.sample* e.g.
-    r = re.compile(fr".*/({re.escape(wildcards.sample)}){bn_r}", flags = re.IGNORECASE)
-    return sorted(list(filter(r.match, fqlist))[:2])
-
-rule process_genome:
-    input:
-        genomefile
-    output: 
-        f"Genome/{bn}"
-    container:
-        None
-    message: 
-        "Copying {input} to Genome/"
-    shell: 
-        """
-        if (file {input} | grep -q compressed ) ;then
-            # is regular gzipped, needs to be BGzipped
-            zcat {input} | bgzip -c > {output}
-        else
-            cp -f {input} {output}
-        fi
-        """
-
-rule index_genome:
-    input: 
-        f"Genome/{bn}"
-    output: 
-        fai = f"Genome/{bn}.fai",
-        gzi = f"Genome/{bn}.gzi" if genome_zip else []
-    log:
-        f"Genome/{bn}.faidx.log"
-    params:
-        genome_zip
-    container:
-        None
-    message:
-        "Indexing {input}"
-    shell: 
-        """
-        if [ "{params}" = "True" ]; then
-            samtools faidx --gzi-idx {output.gzi} --fai-idx {output.fai} {input} 2> {log}
-        else
-            samtools faidx --fai-idx {output.fai} {input} 2> {log}
-        fi
-        """
-
-rule genome_index:
-    input: 
-        f"Genome/{bn}"
-    output: 
-        temp(f"Genome/{bn}.mmi")
-    log:
-        f"Genome/{bn}.mmi.log"
-    conda:
-        f"{envdir}/align.yaml"
-    message:
-        "Indexing {input}"
-    shell: 
-        "minimap2 -x sr -d {output} {input} 2> {log}"
-
-rule align:
-    input:
-        fastq = get_fq,
-        genome   = f"Genome/{bn}.mmi"
-    output:  
-        pipe(outdir + "/samples/{sample}/{sample}.raw.sam")
-    log:
-        outdir + "/logs/{sample}.minimap.log"
-    params: 
-        samps = lambda wc: d[wc.get("sample")],
-        extra = extra
-    benchmark:
-        ".Benchmark/Mapping/minimap/align.{sample}.txt"
-    threads:
-        min(10, workflow.cores) - 2
-    conda:
-        f"{envdir}/align.yaml"
-    message:
-        "Aligning sequences: {wildcards.sample}"
-    shell:
-        """
-        minimap2 -ax sr -t {threads} -y --sam-hit-only -R \"@RG\\tID:{wildcards.sample}\\tSM:{wildcards.sample}\" {input.genome} {input.fastq} > {output} 2> {log}
-        """
- 
-rule quality_filter:
-    input:
-        outdir + "/samples/{sample}/{sample}.raw.sam"
-    output:
-        temp(outdir + "/samples/{sample}/{sample}.mm2.sam")
-    params: 
-        quality = config["quality"]
-    container:
-        None
-    message:
-        "Quality filtering alignments: {wildcards.sample}"
-    shell:
-        "samtools view -h -F 4 -q {params.quality} {input} > {output}"
-
-rule collate:
-    input:
-        outdir + "/samples/{sample}/{sample}.mm2.sam"
-    output:
-        temp(outdir + "/samples/{sample}/{sample}.collate.bam")
-    container:
-        None
-    message:
-        "Collating alignments: {wildcards.sample}"
-    shell:
-        "samtools collate -o {output} {input} 2> /dev/null"
-
-rule fix_mates:
-    input:
-        outdir + "/samples/{sample}/{sample}.collate.bam"
-    output:
-        temp(outdir + "/samples/{sample}/{sample}.fixmate.bam")
-    container:
-        None
-    message:
-        "Fixing mates in alignments: {wildcards.sample}"
-    shell:
-        "samtools fixmate -m {input} {output} 2> /dev/null"
-
-rule sort_alignments:
-    input:
-        sam           = outdir + "/samples/{sample}/{sample}.fixmate.bam",
-        genome 		  = f"Genome/{bn}",
-        genome_samidx = f"Genome/{bn_idx}"
-    output:
-        bam = temp(outdir + "/samples/{sample}/{sample}.sort.bam"),
-        bai = temp(outdir + "/samples/{sample}/{sample}.sort.bam.bai")
-    log:
-        outdir + "/logs/{sample}.minimap.sort.log"
-    params: 
-        quality = config["quality"],
-        tmpdir = lambda wc: outdir + "/." + d[wc.sample]
-    container:
-        None
-    message:
-        "Sorting alignments: {wildcards.sample}"
-    shell:
-        """
-        samtools sort -T {params.tmpdir} --reference {input.genome} -O bam -l 0 -m {resources.mem_mb}M --write-index -o {output.bam}##idx##{output.bai} {input.sam} 2> {log}
-        rm -rf {params.tmpdir}
-        """
-
-rule mark_duplicates:
-    input:
-        outdir + "/samples/{sample}/{sample}.sort.bam"
-    output:
-        temp(outdir + "/samples/{sample}/{sample}.markdup.bam")
-    log:
-        outdir + "/logs/{sample}.markdup.log"
-    threads:
-        2
-    container:
-        None
-    message:
-        "Marking duplicates in alignments alignment: {wildcards.sample}"
-    shell:
-        "samtools markdup -@ {threads} -S --barcode-tag BX -f {log} {input} {output}  2> /dev/null"
-
-rule index_markdups:
-    input:
-        outdir + "/samples/{sample}/{sample}.markdup.bam"
-    output:
-        temp(outdir + "/samples/{sample}/{sample}.markdup.bam.bai")
-    container:
-        None
-    message:
-        "Indexing duplicate-marked alignments: {wildcards.sample}"
-    shell:
-        "samtools index {input}"
-
-rule assign_molecules:
-    input:
-        bam = outdir + "/samples/{sample}/{sample}.markdup.bam",
-        bai = outdir + "/samples/{sample}/{sample}.markdup.bam.bai"
-    output:
-        bam = outdir + "/{sample}.bam",
-        bai = outdir + "/{sample}.bam.bai"
-    params:
-        molecule_distance
-    conda:
-        f"{envdir}/qc.yaml"
-    message:
-        "Assigning barcodes to molecules: {wildcards.sample}"
-    shell:
-        "assign_mi.py -o {output.bam} -c {params} {input.bam}"
-
-rule alignment_bxstats:
-    input:
-        bam = outdir + "/{sample}.bam",
-        bai = outdir + "/{sample}.bam.bai"
-    output: 
-        outdir + "/reports/data/bxstats/{sample}.bxstats.gz"
-    params:
-        sample = lambda wc: d[wc.sample]
-    conda:
-        f"{envdir}/qc.yaml"
-    message:
-        "Calculating barcode alignment statistics: {wildcards.sample}"
-    shell:
-        "bx_stats.py -o {output} {input.bam}"
-
-rule alignment_coverage:
-    input: 
-        bam = outdir + "/{sample}.bam",
-        bai = outdir + "/{sample}.bam.bai"
-    output: 
-        outdir + "/reports/data/coverage/{sample}.cov.gz"
-    params:
-        windowsize
-    container:
-        None
-    message:
-        "Calculating genomic coverage: {wildcards.sample}"
-    shell:
-        "samtools depth -a {input.bam} | depth_windows.py {params} | gzip > {output}"
-
-rule alignment_report:
-    input:
-        outdir + "/reports/data/bxstats/{sample}.bxstats.gz",
-        outdir + "/reports/data/coverage/{sample}.cov.gz"
-    output:	
-        outdir + "/reports/{sample}.html"
-    params:
-        molecule_distance
-    conda:
-        f"{envdir}/r.yaml"
-    message: 
-        "Summarizing barcoded alignments: {wildcards.sample}"
-    script:
-        "report/align_stats.Rmd"
-
-rule general_alignment_stats:
-    input:
-        bam      = outdir + "/{sample}.bam",
-        bai      = outdir + "/{sample}.bam.bai"
-    output: 
-        stats    = temp(outdir + "/reports/data/samtools_stats/{sample}.stats"),
-        flagstat = temp(outdir + "/reports/data/samtools_flagstat/{sample}.flagstat")
-    container:
-        None
-    message:
-        "Calculating alignment stats: {wildcards.sample}"
-    shell:
-        """
-        samtools stats -d {input.bam} > {output.stats}
-        samtools flagstat {input.bam} > {output.flagstat}
-        """
-
-rule samtools_reports:
-    input: 
-        collect(outdir + "/reports/data/samtools_{ext}/{sample}.{ext}", sample = samplenames, ext = ["stats", "flagstat"])
-    output: 
-        outdir + "/reports/minimap.stats.html"
-    params:
-        outdir
-    conda:
-        f"{envdir}/qc.yaml"
-    message:
-        "Summarizing samtools stats and flagstat"
-    shell:
-        """
-        multiqc {params}/reports/data/samtools_stats {params}/reports/data/samtools_flagstat --force --quiet --title "Basic Alignment Statistics" --comment "This report aggregates samtools stats and samtools flagstats results for all alignments." --no-data-dir --filename {output} 2> /dev/null
-        """
-
-rule workflow_summary:
-    default_target: True
-    input: 
-        bams = collect(outdir + "/{sample}.{ext}", sample = samplenames, ext = ["bam","bam.bai"]),
-        samtools =  outdir + "/reports/minimap.stats.html" if not skip_reports else [] ,
-        bx_reports = collect(outdir + "/reports/{sample}.html", sample = samplenames) if not skip_reports else []
-    params:
-        quality = config["quality"],
-        extra   = extra
-
-    run:
-        with open(outdir + "/workflow/align.minimap.summary", "w") as f:
-            _ = f.write("The harpy align module ran using these parameters:\n\n")
-            _ = f.write(f"The provided genome: {bn}\n")
-            _ = f.write("Sequencing were aligned with Minimap2 using:\n")
-            _ = f.write(f"    minimap2 -y {params.extra} --sam-hit-only -R \"@RG\\tID:SAMPLE\\tSM:SAMPLE\" genome.mmi forward_reads reverse_reads |\n")
-            _ = f.write(f"    samtools view -h -F 4 -q {params.quality} |\n")
-            _ = f.write("Duplicates in the alignments were marked following:\n")
-            _ = f.write("    samtools collate \n")
-            _ = f.write("    samtools fixmate\n")
-            _ = f.write("    samtools sort -m 2000M\n")
-            _ = f.write("    samtools markdup -S --barcode-tag BX\n")
-            _ = f.write("\nThe Snakemake workflow was called via command line:\n")
-            _ = f.write("    " + str(config["workflow_call"]) + "\n")
\ No newline at end of file
diff --git a/.deprecated/hpc.py b/.deprecated/hpc.py
deleted file mode 100644
index c8deb1965..000000000
--- a/.deprecated/hpc.py
+++ /dev/null
@@ -1,248 +0,0 @@
-"""Harpy module to create HPC profiles for running snakemake on a cluster"""
-
-import os
-import rich_click as click
-from rich.markdown import Markdown
-from ._printing import print_notice
-
-@click.group(options_metavar='', context_settings={"help_option_names" : ["-h", "--help"]})
-def hpc():
-    """
-    Profile templates for cluster job submissions
-
-    If running Harpy on an HPC system, you can leverage Snakemake
-    to handle all the job submissions on your behalf. This command creates templates
-    for common HPC schedulers so you can run Harpy on a cluster with minimal friction.
-    The subcommands create a `config.yaml` in an `hpc/` directory. You will also need
-    to install the associated Snakemake executor plugin for HPC job submission to work.
-    """
-
-docstring = {
-    "harpy hpc": [
-        {
-            "name": "Submission Systems",
-            "commands": ["generic", "googlebatch", "htcondor", "lsf", "slurm"],
-        },
-    ]
-}
-
-@click.command()
-def generic():
-    """Configuration for a generic scheduler"""
-    outfile = "hpc/generic/config.yaml"
-    os.makedirs("hpc/generic", exist_ok=True)
-    if os.path.exists(outfile):
-        click.echo(f"{outfile} exists, overwriting.")
-    print_notice(Markdown("""
-Using a scheduler requires installing an additional Snakemake plugin. If you haven't already, install the `generic-cluster` plugin with:
-    
-```bash
-mamba install bioconda::snakemake-executor-plugin-cluster-generic
-```
-                """))
-    with open(outfile, "w", encoding = "utf-8") as yml:
-        yml.write("__use_yte__: true\n")
-        yml.write("executor: cluster-generic\n")
-        yml.write("default-resources:\n")
-        yml.write("  mem_mb: attempt * 2000\n")
-        yml.write("jobs: 50\n")
-        yml.write("latency-wait: 60\n")
-        yml.write("retries: 1\n")
-        yml.write("# command for submitting jobs\n")
-        yml.write("cluster-generic-submit-cmd VALUE\n")
-        yml.write("# [optional] command for retrieving job status\n")
-        yml.write("cluster-generic-status-cmd VALUE\n")
-        yml.write("# [optional] command for cancelling jobs-- expected to take one or more jobids as arguments\n")
-        yml.write("cluster-generic-cancel-cmd VALUE\n")
-        yml.write("# [optional] number of jobids to pass to cancel_cmd and if more are given, cancel_cmd will be called multiple times\n")
-        yml.write("cluster-generic-cancel-nargs 20\n")
-        yml.write("# [optional] command for sidecar process\n")
-        yml.write("cluster-generic-sidecar-cmd VALUE\n")
-        yml.write("\n# This section is for advanced copying into a scratch directory #\n")
-        yml.write("## requires snakemake-storage-plugin-fs, which can be installed via conda\n")
-        yml.write("#default-storage-provider: fs\n")
-        yml.write("#local-storage-prefix: /home2/$USER\n")
-        yml.write("#shared-fs-usage:\n")
-        yml.write("#  - persistence\n")
-        yml.write("#  - software-deployment\n")
-        yml.write("#  - sources\n")
-        yml.write("#  - source-cache\n")
-
-@click.command()
-def lsf():
-    """Configuration for LSF"""
-    outfile = "hpc/lsf/config.yaml"
-    os.makedirs("hpc/lsf", exist_ok=True)
-    if os.path.exists(outfile):
-        click.echo(f"{outfile} exists, overwriting.")
-    print_notice(Markdown("""
-Using a scheduler requires installing an additional Snakemake plugin. If you haven't already, install the `lsf` plugin with:
-    
-```bash
-mamba install bioconda::snakemake-executor-plugin-lsf
-```
-                """))
-    with open(outfile, "w", encoding = "utf-8") as yml:
-        yml.write("__use_yte__: true\n")
-        yml.write("executor: lsf\n")
-        yml.write("default-resources:\n")
-        yml.write("  lsf_queue: \n")
-        yml.write("  walltime: 60 # minutes per job\n")
-        yml.write("  mem_mb: attempt * 2000\n")
-        yml.write("  # other args to pass to bsub\n")
-        yml.write("  lsf_extra: \n")
-        yml.write("jobs: 50\n")
-        yml.write("latency-wait: 60\n")
-        yml.write("retries: 1\n")
-        yml.write("\n# This section is for advanced copying into a scratch directory #\n")
-        yml.write("## requires snakemake-storage-plugin-fs, which can be installed via conda\n")
-        yml.write("#default-storage-provider: fs\n")
-        yml.write("#local-storage-prefix: /home2/$USER\n")
-        yml.write("#shared-fs-usage:\n")
-        yml.write("#  - persistence\n")
-        yml.write("#  - software-deployment\n")
-        yml.write("#  - sources\n")
-        yml.write("#  - source-cache\n")
-
-@click.command()
-def htcondor():
-    """Configuration for HTCondor"""
-    os.makedirs("hpc/htcondor", exist_ok=True)
-    outfile = "hpc/htcondor/config.yaml"
-    if os.path.exists(outfile):
-        click.echo(f"{outfile} exists, overwriting.")
-    print_notice(Markdown("""
-Using a scheduler requires installing an additional Snakemake plugin. If you haven't already, install the `htcondor` plugin with:
-    
-```bash
-mamba install bioconda::snakemake-executor-plugin-htcondor
-```
-                """))
-    with open(outfile, "w", encoding = "utf-8") as yml:
-        yml.write("__use_yte__: true\n")
-        yml.write("executor: htcondor\n")
-        yml.write("default-resources:\n")
-        yml.write("  getenv: True\n")
-        yml.write("  rank: \n")
-        yml.write("  max-retries: 1\n")
-        yml.write("  request_memory: attempt * 2000\n")
-        yml.write("jobs: 50\n")
-        yml.write("latency-wait: 60\n")
-        yml.write("retries: 1\n")
-        yml.write("\n# This section is for advanced copying into a scratch directory #\n")
-        yml.write("## requires snakemake-storage-plugin-fs, which can be installed via conda\n")
-        yml.write("#default-storage-provider: fs\n")
-        yml.write("#local-storage-prefix: /home2/$USER\n")
-        yml.write("#shared-fs-usage:\n")
-        yml.write("#  - persistence\n")
-        yml.write("#  - software-deployment\n")
-        yml.write("#  - sources\n")
-        yml.write("#  - source-cache\n")
-
-@click.command()
-def slurm():
-    """Configuration for SLURM"""
-    os.makedirs("hpc/slurm", exist_ok=True)
-    outfile = "hpc/slurm/config.yaml"
-    if os.path.exists(outfile):
-        click.echo(f"{outfile} exists, overwriting.")
-    print_notice(Markdown("""
-Using a scheduler requires installing an additional Snakemake plugin. If you haven't already, install the `slurm` plugin with:
-    
-```bash
-mamba install bioconda::snakemake-executor-plugin-slurm
-```
-                """))
-    with open(outfile, "w", encoding = "utf-8") as yml:
-        yml.write("__use_yte__: true\n")
-        yml.write("executor: slurm\n")
-        yml.write("default-resources:\n")
-        yml.write("  slurm_account: $USER\n")
-        yml.write("  slurm_partition: regular\n")
-        yml.write("  mem_mb: attempt * 2000\n")
-        yml.write("  runtime: 10\n")
-        yml.write("jobs: 50\n")
-        yml.write("latency-wait: 60\n")
-        yml.write("retries: 1\n")
-        yml.write("\n# This section is for advanced copying into a scratch directory #\n")
-        yml.write("## requires snakemake-storage-plugin-fs, which can be installed via conda\n")
-        yml.write("#default-storage-provider: fs\n")
-        yml.write("#local-storage-prefix: /home2/$USER\n")
-        yml.write("#shared-fs-usage:\n")
-        yml.write("#  - persistence\n")
-        yml.write("#  - software-deployment\n")
-        yml.write("#  - sources\n")
-        yml.write("#  - source-cache\n")
-
-@click.command()
-def googlebatch():
-    """Configuration for Google Batch"""
-    os.makedirs("hpc/googlebatch", exist_ok=True)
-    outfile = "hpc/googlebatch/config.yaml"
-    if os.path.exists(outfile):
-        click.echo(f"{outfile} exists, overwriting.")
-    print_notice(Markdown("""
-Using a scheduler requires installing an additional Snakemake plugin. If you haven't already, install the `googlebatch` plugin with:
-    
-```bash
-mamba install bioconda::snakemake-executor-plugin-googlebatch
-```
-                """))
-    with open(outfile, "w", encoding = "utf-8") as yml:
-        yml.write("__use_yte__: true\n")
-        yml.write("executor: googlebatch\n")
-        yml.write("jobs: 50\n")
-        yml.write("latency-wait: 45\n")
-        yml.write("retries: 1\n")
-        yml.write("default-resources:\n")
-        yml.write("## YOU MAY NOT NEED ALL OF THESE! ##\n")
-        yml.write("# The name of the Google Project\n")
-        yml.write("  googlebatch_project: Harpy\n")
-        yml.write("# The name of the Google Project region (e.g., 'us-central1')\n")
-        yml.write("  googlebatch_region: 'us-central1'\n")
-        yml.write("# Retry count\n")
-        yml.write("  googlebatch_retry_count: 1\n")
-        yml.write("# Maximum run duration, string (e.g., '3600s')\n")
-        yml.write("  googlebatch_max_run_duration: '3600s'\n")
-        yml.write("# Memory in MiB\n")
-        yml.write("  googlebatch_memory: attempt * 2000\n")
-        yml.write("# The default number of work tasks (these are NOT MPI ranks)\n")
-        yml.write("  googlebatch_work_tasks: 50\n")
-        yml.write("# The default number of work tasks per node (NOT MPI ranks)\n")
-        yml.write("  googlebatch_work_tasks_per_node: 10\n")
-        yml.write("# Milliseconds per cpu-second\n")
-        yml.write("  googlebatch_cpu_milli: 1000\n")
-        yml.write("# A custom container for use with Google Batch COS\n")
-        yml.write("  googlebatch_container: VALUE\n")
-        yml.write("# A docker registry password for COS if credentials are required\n")
-        yml.write("  googlebatch_docker_password: VALUE\n")
-        yml.write("# A docker registry username for COS if credentials are required\n")
-        yml.write("  googlebatch_docker_username: VALUE\n")
-        yml.write("# Google Cloud machine type or VM (mpitune on c2 and c2d family)\n")
-        yml.write("  googlebatch_machine_type: 'c2-standard-4'\n")
-        yml.write("# Comma separated key value pairs to label job (e.g., model=a3,stage=test)\n")
-        yml.write("  googlebatch_labels: VALUE\n")
-        yml.write("# Google Cloud image family (defaults to hpc-centos-7)\n")
-        yml.write("  googlebatch_image_family: 'hpc-centos-7'\n")
-        yml.write("# Selected image project\n")
-        yml.write("  googlebatch_image_project: 'cloud-hpc-image-public'\n")
-        yml.write("# Boot disk size (GB)\n")
-        yml.write("  googlebatch_boot_disk_gb: VALUE\n")
-        yml.write("# The URL of an existing network resource\n")
-        yml.write("  googlebatch_network: VALUE\n")
-        yml.write("# The URL of an existing subnetwork resource\n")
-        yml.write("  googlebatch_subnetwork: VALUE\n")
-        yml.write("# Boot disk type. (e.g., gcloud compute disk-types list)\n")
-        yml.write("  googlebatch_boot_disk_type: VALUE\n")
-        yml.write("# Boot disk image (e.g., batch-debian, bath-centos)\n")
-        yml.write("  googlebatch_boot_disk_image: VALUE\n")
-        yml.write("# Mount path for Google bucket (if defined)\n")
-        yml.write("  googlebatch_mount_path: '/mnt/share'\n")
-        yml.write("# One or more snippets to add to the Google Batch task setup\n")
-        yml.write("  googlebatch_snippets: VALUE\n")
-
-hpc.add_command(slurm)
-hpc.add_command(htcondor)
-hpc.add_command(lsf)
-hpc.add_command(generic)
-hpc.add_command(googlebatch)
diff --git a/.deprecated/phase.bak.smk b/.deprecated/phase.bak.smk
deleted file mode 100644
index cace77c90..000000000
--- a/.deprecated/phase.bak.smk
+++ /dev/null
@@ -1,323 +0,0 @@
-containerized: "docker://pdimens/harpy:latest"
-
-from rich import print as rprint
-from rich.panel import Panel
-import sys
-
-##TODO MANUAL PRUNING OF SWITCH ERRORS
-# https://github.com/vibansal/HapCUT2/blob/master/outputformat.md
-
-bam_dir           = config["seq_directory"]
-samplenames       = config["samplenames"]
-variantfile       = config["variantfile"]
-pruning           = config["prune"]
-molecule_distance = config["molecule_distance"]
-extra             = config.get("extra", "") 
-outdir 			  = config["output_directory"]
-envdir      = os.path.join(os.getcwd(), ".harpy_envs")
-
-if config["noBX"]:
-    fragfile = outdir + "/extractHairs/{sample}.unlinked.frags"
-else:
-    fragfile =  outdir + "/linkFragments/{sample}.linked.frags"
-
-linkarg     = "--10x 0" if config["noBX"] else "--10x 1"
-skipreports = config["skip_reports"]
-
-try:
-    indelarg = "--indels 1 --ref " + config["indels"]
-except:
-    indelarg = ""
-
-wildcard_constraints:
-    sample = "[a-zA-Z0-9._-]+"
-
-onerror:
-    print("")
-    rprint(
-        Panel(
-            f"The workflow has terminated due to an error. See the log file below for more details.",
-            title = "[bold]harpy phase",
-            title_align = "left",
-            border_style = "red"
-            ),
-        file = sys.stderr
-    )
-
-onsuccess:
-    print("")
-    rprint(
-        Panel(
-            f"The workflow has finished successfully! Find the results in [bold]{outdir}/[/bold]",
-            title = "[bold]harpy phase",
-            title_align = "left",
-            border_style = "green"
-            ),
-        file = sys.stderr
-    )
-
-rule split_by_samplehet:
-    input: 
-        vcf = variantfile,
-        bam = bam_dir + "/{sample}.bam"
-    output:
-        outdir + "/workflow/input/vcf/{sample}.het.vcf"
-    benchmark:
-        ".Benchmark/Phase/splithet.{sample}.txt"
-    container:
-        None
-    message:
-        "Extracting heterozygous variants: {wildcards.sample}"
-    shell:
-        """
-        bcftools view -s {wildcards.sample} {input.vcf} |
-        awk '/^#/;/CHROM/ {{OFS="\\t"}}; !/^#/ && $10~/^0\\/1/' > {output}
-        """
-
-rule split_by_sample:
-    input: 
-        vcf = variantfile,
-        bam = bam_dir + "/{sample}.bam"
-    output:
-        outdir + "/workflow/input/vcf/{sample}.vcf"
-    benchmark:
-        ".Benchmark/Phase/split.{sample}.txt"
-    container:
-        None
-    message:
-        "Extracting variants: {wildcards.sample}"
-    shell:
-        """
-        bcftools view -s {wildcards.sample} {input.vcf} |
-        awk '/^#/;/CHROM/ {{OFS="\\t"}}; !/^#/ &&  $10~/^0\\/0/ {{$10="0|0:"substr($10,5);print $0}}; !/^#/ && $10~/^0\\/1/; !/^#/ &&  $10~/^1\\/1/ {{$10="1|1:"substr($10,5);print $0}}; !/^#/ {{print $0}}' > {output}
-        """
-
-rule index_alignment:
-    input:
-        bam_dir + "/{sample}.bam"
-    output:
-        bam_dir + "/{sample}.bam.bai"
-    container:
-        None
-    message:
-        "Indexing alignment: {wildcards.sample}"
-    shell:
-        "samtools index {input} {output} 2> /dev/null"
-
-rule extract_hairs:
-    input:
-        vcf = outdir + "/workflow/input/vcf/{sample}.het.vcf",
-        bam = bam_dir + "/{sample}.bam",
-        bai = bam_dir + "/{sample}.bam.bai"
-    output:
-        outdir + "/extractHairs/{sample}.unlinked.frags"
-    log:
-        outdir + "/extractHairs/logs/{sample}.unlinked.log"
-    params:
-        indels = indelarg,
-        bx = linkarg
-    conda:
-        f"{envdir}/phase.yaml"
-    benchmark:
-        ".Benchmark/Phase/extracthairs.{sample}.txt"
-    message:
-        "Converting to compact fragment format: {wildcards.sample}"
-    shell:
-        "extractHAIRS {params} --nf 1 --bam {input.bam} --VCF {input.vcf} --out {output} 2> {log}"
-
-rule link_fragments:
-    input: 
-        bam       = bam_dir + "/{sample}.bam",
-        vcf       = outdir + "/workflow/input/vcf/{sample}.het.vcf",
-        fragments = outdir + "/extractHairs/{sample}.unlinked.frags"
-    output:
-        outdir + "/linkFragments/{sample}.linked.frags"
-    log:
-        outdir + "/linkFragments/logs/{sample}.linked.log"
-    params:
-        d = molecule_distance
-    conda:
-        f"{envdir}/phase.yaml"
-    benchmark:
-        ".Benchmark/Phase/linkfrag.{sample}.txt"
-    message:
-        "Linking fragments: {wildcards.sample}"
-    shell:
-        "LinkFragments.py --bam {input.bam} --VCF {input.vcf} --fragments {input.fragments} --out {output} -d {params} > {log} 2>&1"
-
-rule phase_blocks:
-    input:
-        vcf       = outdir + "/workflow/input/vcf/{sample}.het.vcf",
-        fragments = fragfile
-    output: 
-        blocks    = outdir + "/phaseBlocks/{sample}.blocks",
-        vcf       = outdir + "/phaseBlocks/{sample}.blocks.phased.VCF"
-    log:
-        outdir + "/phaseBlocks/logs/{sample}.blocks.phased.log"
-    params: 
-        prune = f"--threshold {pruning}" if pruning > 0 else "--no_prune 1",
-        extra = extra
-    conda:
-        f"{envdir}/phase.yaml"
-    benchmark:
-        ".Benchmark/Phase/phase.{sample}.txt"
-    message:
-        "Creating phased haplotype blocks: {wildcards.sample}"
-    shell:
-        "HAPCUT2 --fragments {input.fragments} --vcf {input.vcf} {params} --out {output.blocks} --nf 1 --error_analysis_mode 1 --call_homozygous 1 --outvcf 1 > {log} 2>&1"
-
-rule create_annotations:
-    input:
-        outdir + "/phaseBlocks/{sample}.blocks.phased.VCF"
-    output:
-        outdir + "/annotations/{sample}.annot.gz"
-    container:
-        None
-    message:
-        "Creating annotation files: {wildcards.sample}"
-    shell:
-        "bcftools query -f \"%CHROM\\t%POS[\\t%GT\\t%PS\\t%PQ\\t%PD]\\n\" {input} | bgzip -c > {output}"
-
-rule index_annotations:
-    input:
-        outdir + "/annotations/{sample}.annot.gz"
-    output:
-        outdir + "/annotations/{sample}.annot.gz.tbi"
-    container:
-        None
-    message:
-        "Indexing {wildcards.sample}.annot.gz"
-    shell: 
-        "tabix -b 2 -e 2 {input}"
-
-rule headerfile:
-    output:
-        outdir + "/workflow/input/header.names"
-    message:
-        "Creating additional header file"
-    run:
-        with open(output[0], "w") as fout:
-            _ = fout.write('##INFO=<ID=HAPCUT,Number=0,Type=Flag,Description="The haplotype was created with Hapcut2">\n')
-            _ = fout.write('##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype/Haplotype">\n')
-            _ = fout.write('##FORMAT=<ID=PS,Number=1,Type=Integer,Description="ID of Phase Set for Variant">\n')
-            _ = fout.write('##FORMAT=<ID=PQ,Number=1,Type=Integer,Description="Phred QV indicating probability that this variant is incorrectly phased relative to the haplotype">\n')
-            _ = fout.write('##FORMAT=<ID=PD,Number=1,Type=Integer,Description="phased Read Depth">')
-
-rule merge_annotations:
-    input:
-        annot   = outdir + "/annotations/{sample}.annot.gz",
-        idx     = outdir + "/annotations/{sample}.annot.gz.tbi",
-        orig    = outdir + "/workflow/input/vcf/{sample}.vcf",
-        headers = outdir + "/workflow/input/header.names"
-    output:
-        bcf = outdir + "/annotations_merge/{sample}.phased.annot.bcf",
-        idx = outdir + "/annotations_merge/{sample}.phased.annot.bcf.csi"
-    threads:
-        2
-    benchmark:
-        ".Benchmark/Phase/mergeAnno.{sample}.txt"
-    container:
-        None
-    message:
-        "Merging annotations: {wildcards.sample}"
-    shell:
-        """
-        bcftools annotate -h {input.headers} -a {input.annot} {input.orig} -c CHROM,POS,FMT/GT,FMT/PS,FMT/PQ,FMT/PD -m +HAPCUT |
-            awk '!/<ID=GX/' |
-            sed 's/:GX:/:GT:/' |
-            bcftools view -Ob --write-index -o {output.bcf} -
-        """
-
-rule merge_samples:
-    input: 
-        bcf = collect(outdir + "/annotations_merge/{sample}.phased.annot.bcf", sample = samplenames),
-        idx = collect(outdir + "/annotations_merge/{sample}.phased.annot.bcf.csi", sample = samplenames)
-    output:
-        bcf = outdir + "/variants.phased.bcf",
-        idx = outdir + "/variants.phased.bcf.csi"
-    params:
-        "true" if len(samplenames) > 1 else "false"
-    threads:
-        workflow.cores
-    container:
-        None
-    message:
-        "Combining results into {output.bcf}" if len(samplenames) > 1 else "Copying results to {output.bcf}"
-    shell:
-        """
-        if [ "{params}" = true ]; then
-            bcftools merge --threads {threads} -Ob -o {output.bcf} --write-index {input.bcf}
-        else
-           cp {input.bcf} {output.bcf}
-           cp {input.idx} {output.idx}
-        fi
-        """
-
-rule summarize_blocks:
-    input:
-        collect(outdir + "/phaseBlocks/{sample}.blocks", sample = samplenames)
-    output:
-        outdir + "/reports/blocks.summary.gz"
-    params:
-        outdir + "/reports/blocks.summary"
-    container:
-        None
-    message:
-        "Summarizing phasing results"
-    shell:
-        """
-        echo -e "sample\\tcontig\\tn_snp\\tpos_start\\tblock_length" > {params}
-        for i in {input}; do
-            parse_phaseblocks.py -i $i >> {params}
-        done
-        gzip {params}
-        """
-
-rule phase_report:
-    input:
-        outdir + "/reports/blocks.summary.gz"
-    output:
-        outdir + "/reports/phase.html"
-    conda:
-        f"{envdir}/r.yaml"
-    message:
-        "Summarizing phasing results"
-    script:
-        "report/hapcut.Rmd"
-
-rule workflow_summary:
-    default_target: True
-    input:
-        vcf = outdir + "/variants.phased.bcf",
-        reports = outdir + "/reports/phase.html" if not skip_reports else []
-    params:
-        prune = f"--threshold {pruning}" if pruning > 0 else "--no_prune 1",
-        extra = extra
-    message:
-        "Creating record of relevant runtime parameters"
-    run:
-        with open(outdir + "/workflow/phase.summary", "w") as f:
-            _ = f.write("The harpy phase module ran using these parameters:\n\n")
-            _ = f.write(f"The provided variant file: {variantfile}\n")
-            _ = f.write(f"The directory with alignments: {bam_dir}\n")
-            _ = f.write("The variant file was split by sample and preprocessed using:\n")
-            _ = f.write("""    bcftools view -s SAMPLE | awk '/^#/;/CHROM/ OFS="\\t"; !/^#/ && $10~/^0\\/1/'\n\n""")
-            _ = f.write("Phasing was performed using the components of HapCut2:\n")
-            _ = f.write("    extractHAIRS " + linkarg + " --nf 1 --bam sample.bam --VCF sample.vcf --out sample.unlinked.frags\n")
-            _ = f.write("    LinkFragments.py --bam sample.bam --VCF sample.vcf --fragments sample.unlinked.frags --out sample.linked.frags -d " + f"{molecule_distance}" + "\n")
-            _ = f.write("    HAPCUT2 --fragments sample.linked.frags --vcf sample.vcf --out sample.blocks --nf 1 --error_analysis_mode 1 --call_homozygous 1 --outvcf 1" + f" {params[0]} {params[1]}" + "\n\n")
-            _ = f.write("Variant annotation was performed using:\n")
-            _ = f.write("    bcftools query -f \"%CHROM\\t%POS[\\t%GT\\t%PS\\t%PQ\\t%PD]\\n\" sample.vcf | bgzip -c\n")
-            _ = f.write("    bcftools annotate -h header.file -a sample.annot sample.bcf -c CHROM,POS,FMT/GX,FMT/PS,FMT/PQ,FMT/PD -m +HAPCUT |\n")
-            _ = f.write("        awk '!/<ID=GX/' |\n")
-            _ = f.write("        sed 's/:GX:/:GT:/' |\n")
-            _ = f.write("        bcftools view -Ob -o sample.annot.bcf -\n")
-            _ = f.write("    bcftools merge --output-type b samples.annot.bcf\n\n")
-            _ = f.write("The header.file of extra vcf tags:\n")
-            _ = f.write('    ##INFO=<ID=HAPCUT,Number=0,Type=Flag,Description="The haplotype was created with Hapcut2">\n')
-            _ = f.write('    ##FORMAT=<ID=GX,Number=1,Type=String,Description="Haplotype">\n')
-            _ = f.write('    ##FORMAT=<ID=PS,Number=1,Type=Integer,Description="ID of Phase Set for Variant">\n')
-            _ = f.write('    ##FORMAT=<ID=PQ,Number=1,Type=Integer,Description="Phred QV indicating probability that this variant is incorrectly phased relative to the haplotype">\n')
-            _ = f.write('    ##FORMAT=<ID=PD,Number=1,Type=Integer,Description="phased Read Depth">\n')
-            _ = f.write("\nThe Snakemake workflow was called via command line:\n")
-            _ = f.write("    " + str(config["workflow_call"]) + "\n")
\ No newline at end of file
diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
index 00953809b..ab7432fc9 100644
--- a/.github/workflows/tests.yml
+++ b/.github/workflows/tests.yml
@@ -833,7 +833,7 @@ jobs:
         run: harpy downsample -d 1 --random-seed 699 --quiet test/bam/sample1.bam
       - name: harpy downsample fastq
         shell: micromamba-shell {0}
-        run: harpy downsample -d 1 --quiet test/fastq/sample1.*
+        run: harpy downsample -d 1 --quiet test/fastq/sample1.*gz
       - name: harpy hpc
         shell: micromamba-shell {0}
         run: |
diff --git a/harpy/bin/extract_bxtags.py b/harpy/bin/extract_bxtags.py
new file mode 100755
index 000000000..fd3e2c586
--- /dev/null
+++ b/harpy/bin/extract_bxtags.py
@@ -0,0 +1,53 @@
+#! /usr/bin/env python
+
+import re
+import sys
+import pysam
+import random
+import argparse
+
+parser = argparse.ArgumentParser(
+    prog = 'extract_bxtags.py',
+    description = 'Extracts all the barcodes present in a SAM/BAM file. Can optionally subsample the barcodes. Use --invalid to specify a proportion of invalid haplotagging to output.',
+    usage = "extract_bxtags.py [-i] -b BC -d 15000 input.bam > output.txt",
+    )
+parser.add_argument('-i','--invalid', type= float, default=1, help = "Proportion of invalid barcodes to include in subsampling/output (default: %(default)s)")
+parser.add_argument('-d','--downsample', type= int, help = "Number of barcodes to downsample to")
+parser.add_argument('-r','--random-seed', type= int, help = "Random seed for sampling")
+parser.add_argument('-b','--bx-tag', type= str, default="BX", help = "2-character tag with the barcodes (alphanumeric, default: %(default)s)")
+parser.add_argument('input', type= str, help = "Input BAM file")
+if len(sys.argv) == 1:
+    parser.print_help(sys.stderr)
+    sys.exit(1)
+
+args = parser.parse_args()
+if args.invalid < 0 or args.invalid > 1:
+    parser.error("--invalid must be between 0 and 1")
+
+bx_tag = args.bx_tag.upper()
+inv_prop = args.invalid
+rng  = random.Random(args.random_seed) if args.random_seed else random.Random()
+invalid_pattern = re.compile(r'[AaBbCcDd]00')
+barcodes = set()
+mode = "r" if args.input.lower().endswith("sam") else "rb"
+with pysam.AlignmentFile(args.input, mode, check_sq=False) as infile:
+    for record in infile:
+        try:
+            barcode = record.get_tag(bx_tag)
+            if invalid_pattern.search(barcode):
+                # invalid barcode retention
+                if rng.random() > inv_prop:
+                    continue
+        except KeyError:
+            continue
+        barcodes.add(barcode)
+    if args.downsample:
+        n_bc = len(barcodes)
+        if n_bc < args.downsample:
+            raise ValueError(f"The input has fewer barcodes ({n_bc}) than the requested downsampling amount ({args.downsample})")
+        else:
+            for i in rng.sample(sorted(barcodes), args.downsample):
+                sys.stdout.write(f"{i}\n")
+    else:
+        for i in barcodes:
+            sys.stdout.write(f"{i}\n")
\ No newline at end of file
diff --git a/harpy/downsample.py b/harpy/downsample.py
index 62beccb40..a0c4bd5c3 100644
--- a/harpy/downsample.py
+++ b/harpy/downsample.py
@@ -3,52 +3,53 @@
 import os
 import re
 import sys
-import pysam
-import random
-import subprocess
+import yaml
+from rich import box
 from pathlib import Path
+from rich.table import Table
 import rich_click as click
-from ._misc import harpy_pulsebar
-
+from ._cli_types_generic import SnakemakeParams
+from ._launch import launch_snakemake
+from ._misc import fetch_rule, snakemake_log
 
 docstring = {
     "harpy downsample": [
         {
             "name": "Parameters",
-            "options": sorted(["--downsample", "--invalid", "--bx-tag", "--random-seed", "--prefix"]),
+            "options": sorted(["--downsample", "--invalid", "--random-seed", "--prefix"]),
         },
         {
             "name": "Workflow Controls",
-            "options": ["--quiet", "--snakemake", "--threads", "--help"],
+            "options": ["--output-dir", "--quiet", "--snakemake", "--threads", "--help"],
         },
     ]
 }
-
 @click.command(no_args_is_help = True, context_settings=dict(allow_interspersed_args=False), epilog = "Documentation: https://pdimens.github.io/harpy/workflows/downsample")
 @click.option('-d', '--downsample', type = click.IntRange(min = 1), help = 'Downsampling amount')
-@click.option('-i', '--invalid', default = "keep", show_default = True, type=click.Choice( ["keep","drop"]), help = "Strategy to handle invalid/missing barcodes")
-@click.option('-b', '--bx-tag', type = str, default = "BX", show_default=True, help = "The header tag with the barcode")
+@click.option('-i', '--invalid', default = 1, show_default = True, type=click.FloatRange(min=0,max=1), help = "Proportion of invalid barcodes to sample")
 @click.option('-p', '--prefix', type = click.Path(exists = False), default = "downsampled", show_default = True, help = 'Prefix for output file(s)')
 @click.option('--random-seed', type = click.IntRange(min = 1), help = "Random seed for sampling")
+@click.option('-o', '--output-dir', type = click.Path(exists = False), default = "Downsample", show_default=True,  help = 'Output directory name')
 @click.option('-t', '--threads', default = 4, show_default = True, type = click.IntRange(min = 1, max_open = True), help = 'Number of threads to use')
 @click.option('--quiet',  is_flag = True, show_default = True, default = False, help = 'Don\'t show output text while running')
+@click.option('--setup-only',  is_flag = True, hidden = True, show_default = True, default = False, help = 'Setup the workflow and exit')
+@click.option('--snakemake', type = SnakemakeParams(), help = 'Additional Snakemake parameters, in quotes')
 @click.argument('input', required=True, type=click.Path(exists=True, readable=True, dir_okay=False), nargs=-1)
-def downsample(input, prefix, downsample, invalid, bx_tag, random_seed, threads, quiet):
+def downsample(input, invalid, output_dir, prefix, downsample, random_seed, setup_only, snakemake, threads, quiet):
     """
     Downsample data by barcode
 
-    Downsamples FASTQ or BAM file(s) by barcode to keep all reads
-    from `-d` barcodes.
+    Downsamples FASTQ or BAM file(s) by barcode in the `BX` tag to keep all reads
+    from `-d` barcodes. Input can be:
     - one BAM file
     - two FASTQ files (R1 and R2 of a paired-end read set)
     
-    Use `--invalid` to specify how to handle invalid barcodes:
-    - `keep`: output all invalid/missing barcodes
-    - `drop`: don't output any invalid/missing barcodes
+    Use `--invalid` to specify the proportion of invalid barcodes to consider for sampling:
+    - `0` removes all invalid barcodes from the barcode pool
+    - `1` adds all invalid barcodes to the barcode pool
+    - 0<`i`<1 (e.g. `0.25`) keeps that proprotion of invalid barcodes in the barcode pool
     """
     # validate input files as either 1 bam or 2 fastq
-    if len(bx_tag) != 2 or not bx_tag.isalnum():
-        raise click.BadParameter(f'\'{bx_tag}\' is not a valid SAM tag. Tags for --bx-tag must be alphanumeric and exactly 2 characters, e.g. "BX"')
     if len(input) > 2:
         raise click.BadParameter('inputs must be 1 BAM file or 2 FASTQ files.')
     if len(input) == 1:
@@ -58,134 +59,44 @@ def downsample(input, prefix, downsample, invalid, bx_tag, random_seed, threads,
         if input[0] == input[1]:
             raise click.BadParameter('the two input files cannot be identical')
         re_ext = re.compile(r"\.(fq|fastq)(?:\.gz)?$", re.IGNORECASE)
-        badfastq = []
         for i in input:
             if not re.search(re_ext, i):
-                badfastq.append(i)
-        if badfastq:
-            raise click.BadParameter('inputs must be 1 BAM (.bam) file or 2 FASTQ (.fastq|.fq) files. The FASTQ files can be gzipped.')
-
-    output_bam = f"{prefix}.bam"
-    bx_tag = bx_tag.upper()
-    rng = random.Random(random_seed).sample if random_seed else random.Random().sample
-    logfile = open(f"{prefix}.log", "w")
-    sys.stderr.write = logfile.write
-
-    with harpy_pulsebar(quiet, f"sorting by {bx_tag} tags") as progress:
-        progress.add_task(f"sorting by {bx_tag} tags", total = None)
-        if len(input) == 2:
-            samtools_import = subprocess.Popen(f"samtools import -@ {threads} -T * {input[0]} {input[1]}".split(), stdout=subprocess.PIPE, stderr=logfile) 
-            subprocess.run(f"samtools sort -@ {threads} -o bx_sorted.bam -t {bx_tag}".split(), stdin = samtools_import.stdout, stderr=logfile)
-        else:
-            subprocess.run(f"samtools sort -@ {threads} -o bx_sorted.bam -t {bx_tag} {input[0]}".split(), stderr=logfile)
-    sorted_bam = Path("bx_sorted.bam").resolve().as_posix()
-    invalid_pattern = re.compile(r'[AaBbCcDd]00')
-
-    # read input file, get list of valid barcodes, subsample valid barcodes, read input again, output only sampled barcodes
-    with (
-        pysam.AlignmentFile(sorted_bam, "rb", check_sq=False) as infile,
-        harpy_pulsebar(quiet, f"parsing {bx_tag} tags") as progress
-    ):
-        progress.add_task(f"parsing {bx_tag} tags", total = None)
-        barcodes = set()
-        for record in infile:
-            try:
-                barcode = record.get_tag(bx_tag)
-                if isinstance(barcode, int):
-                    pass # an int from an MI-tharype tag
-                elif invalid_pattern.search(barcode):
-                    continue
-            except KeyError:
-                continue
-            barcodes.add(barcode)
-        n_bc = len(barcodes)
-        if downsample > n_bc:
-            sys.stderr.write(f"The number of intended barcodes to downsample to ({downsample}) is greater than the number of barcodes in the input file ({n_bc}). Please choose a smaller number to downsample to.\n")
-            sys.exit(1)
-        barcodes = rng(sorted(barcodes), downsample)
-    with (
-        pysam.AlignmentFile(sorted_bam, "rb", check_sq=False) as infile,
-        pysam.AlignmentFile(output_bam, "wb", template=infile) as outfile,
-        harpy_pulsebar(quiet, f"downsampling {bx_tag} tags") as progress
-    ):
-        progress.add_task(f"downsampling {bx_tag} tags", total = None)
-        for record in infile:
-            try:
-                barcode = record.get_tag(bx_tag)
-                if isinstance(barcode, int):
-                    pass # an int from an MI-type tag
-                elif invalid_pattern.search(barcode):
-                    if invalid == "keep":
-                        outfile.write(record)
-                    continue
-            except KeyError:
-                if invalid == "keep":
-                    outfile.write(record)
-                continue
-            if barcode in barcodes:
-                outfile.write(record)
-
-    # convert back
-    os.remove(sorted_bam)
-    if len(input) == 2:
-        subprocess.run(f'samtools fastq -T * -c 6 -1 {prefix}.R1.fq.gz -2 {prefix}.R2.fq.gz {output_bam}'.split(), stderr=logfile)
-        os.remove(output_bam)
-    logfile.close()
+                raise click.BadParameter('inputs must be 1 BAM (.bam) file or 2 FASTQ (.fastq|.fq) files. The FASTQ files can be gzipped.')            
+    workflow = "downsample"
+    output_dir = output_dir.rstrip("/")
+    workflowdir = os.path.join(output_dir, 'workflow')
+    command = f'snakemake --rerun-incomplete --show-failed-logs --rerun-triggers input mtime params --nolock --cores {threads} --directory . '
+    command += f"--snakefile {workflowdir}/{workflow}.smk "
+    command += f"--configfile {workflowdir}/config.yaml "
+    if snakemake:
+        command += snakemake
 
+    os.makedirs(workflowdir, exist_ok=True)
+    os.makedirs(f"{output_dir}/logs/snakemake", exist_ok = True)
+    fetch_rule(workflowdir, f"{workflow}.smk")
+    sm_log = snakemake_log(output_dir, workflow)
+    configs = {
+        "workflow": workflow,
+        "snakemake_log" : sm_log,
+        "output_directory" : output_dir,
+        "prefix" :  prefix,
+        "downsample" :  downsample,
+        "invalid_proportion" : invalid,       
+        **({"random_seed" : random_seed} if random_seed else {}),
+        "workflow_call" : command.rstrip(),
+        "inputs": [Path(i).resolve().as_posix() for i in input]
+        }
+    with open(os.path.join(workflowdir, 'config.yaml'), "w", encoding="utf-8") as config:
+        yaml.dump(configs, config, default_flow_style= False, sort_keys=False, width=float('inf'))
 
+    if setup_only:
+        sys.exit(0)
 
-# store records with the same barcode in an array
-# then subsample according to the downsample fraction and write to output
-# "within":
-#        with (
-#            pysam.AlignmentFile(sorted_bam, "rb", check_sq=False) as infile,
-#            pysam.AlignmentFile(output_bam, "wb", template=infile) as outfile,
-#            harpy_pulsebar(quiet, f"downsampling within {bx_tag} tags") as progress
-#        ):
-#            progress.add_task(f"downsampling within {bx_tag} tags", total = None)
-#            record_store_F = []
-#            record_store_R = []
-#            last_barcode = None
-#            for record in infile:
-#                try:
-#                    barcode = record.get_tag(bx_tag)
-#                    if isinstance(barcode, int):
-#                        pass
-#                    elif invalid_pattern.search(barcode):
-#                        if invalid == "keep":
-#                            outfile.write(record)
-#                        elif invalid == "downsample":
-#                            if rng.uniform(0, 1) <= downsample:
-#                                outfile.write(record)    
-#                        continue
-#                except KeyError:
-#                    if invalid == "keep":
-#                        outfile.write(record)
-#                    elif invalid == "downsample":
-#                        if rng.uniform(0, 1) <= downsample:
-#                            outfile.write(record)    
-#                    continue
-#                    
-#                if last_barcode and barcode != last_barcode:
-#                    # subsample records to file and reset record stores
-#                    for i,j in zip(record_store_F, record_store_R):
-#                        if rng.uniform(0, 1) <= downsample:
-#                            if i:
-#                                outfile.write(i)
-#                            if j:
-#                                outfile.write(j)
-#                    record_store_F = []
-#                    record_store_R = []
-#                # otherwise proceed to append record to stores
-#                if record.is_forward and record.is_paired:
-#                    record_store_F.append(record)
-#                elif record.is_reverse and record.is_paired:
-#                    record_store_R.append(record)    
-#                elif record.is_forward and not record.is_paired:
-#                    record_store_F.append(record)
-#                    record_store_R.append(None)
-#                elif record.is_reverse and not record.is_paired:
-#                    record_store_F.append(None)
-#                    record_store_R.append(record)
-#                # update what the last barcode is
-#                last_barcode = barcode
+    start_text = Table(show_header=False,pad_edge=False, show_edge=False, padding = (0,0), box=box.SIMPLE)
+    start_text.add_column("detail", justify="left", style="light_steel_blue", no_wrap=True)
+    start_text.add_column("value", justify="left")
+    start_text.add_row("Output Folder:", output_dir + "/")
+    start_text.add_row("Downsample to:", f"{downsample} barcodes")
+    start_text.add_row("Invalid Proportion:", f"{invalid}")
+    start_text.add_row("Workflow Log:", sm_log.replace(f"{output_dir}/", "") + "[dim].gz")
+    launch_snakemake(command, workflow, start_text, output_dir, sm_log, quiet, f"workflow/{workflow}.summary")
diff --git a/harpy/reports/hapcut.Rmd b/harpy/reports/hapcut.Rmd
index 15a4129a7..5015b6624 100644
--- a/harpy/reports/hapcut.Rmd
+++ b/harpy/reports/hapcut.Rmd
@@ -51,6 +51,14 @@ df <- df[df$block_length > 0, c(1,2,3,4,6,5)]
 levels(df$sample) <- basename(levels(df$sample))
 ```
 
+```{r nxx, results = F}
+NX <- function(lengths, X=50){
+  lengths <- as.numeric(sort(lengths, decreasing=TRUE))
+  index <- which(cumsum(lengths) / sum(lengths) >= X/100)[1]
+  return(lengths[index])
+}
+```
+
 # General Stats
 ## fileheader 
 ### details desc {.no-title}
@@ -60,11 +68,9 @@ The data presented here are the results of phasing genotypes into haplotypes usi
 which summarized information across all samples using the `.blocks` files HapCut2
 generates. The VCF files HapCut2 also generates were not used as they lack
 some of the information in the `.blocks` files that were collated in this report.
-This page shows general and per-contig information. You may click the plots to
-expand them in your browser. Clicking them again will exit from the zoomed pop-up
-window. The `Per-Sample Stats` tab in the navigation bar above will show you
-statistics relating to haplotypes on the per-sample level. Haplotype blocks with a size
-of `0` were removed from the data.
+This page shows general and per-contig information. The `Per-Sample Stats` tab in
+the navigation bar above will show you statistics relating to haplotypes on the
+per-sample level. Haplotype blocks with a size of `0` were removed from the data.
 
 ## Haplotyping details {data-height=100}
 ```{r process_stats}
@@ -72,9 +78,10 @@ overall <- df %>% summarise(
     total_snps = sum(n_snp),
     mean_snps = round(mean(n_snp), digits = 0),
     median_snps = median(n_snp),
-    mean_blocksize = round(mean(block_length), digits = 0),
-    median_blocksize = median(block_length),
-    max_blocksize = max(block_length)
+    max_blocksize = max(block_length),
+    N50 = NX(block_length, 50),
+    N75 = NX(block_length, 75),
+    N90 = NX(block_length, 90)
 )
 ```
 
@@ -92,14 +99,19 @@ valueBox(scales::comma(overall$mean_snps[1]), caption = "Avg SNPs/Haplotype", co
 ```{r}
 valueBox(scales::comma(overall$median_snps[1]), caption = "Median SNPs/Haplotype", color = "info")
 ```
-### avg blocksize
+### N50
+```{r}
+valueBox(scales::comma(overall$N50[1]), caption = "N50", color = "info")
+```
+
+### N75
 ```{r}
-valueBox(scales::comma(overall$mean_blocksize[1]), caption = "Avg Haplotype Length", color = "info")
+valueBox(scales::comma(overall$N75[1]), caption = "N75", color = "info")
 ```
 
-### median blocksize
+### N90
 ```{r}
-valueBox(scales::comma(overall$median_blocksize[1]), caption = "Median Haplotype Length", color = "info")
+valueBox(scales::comma(overall$N90[1]), caption = "N90", color = "info")
 ```
 
 ### longest haplotype
@@ -152,7 +164,7 @@ percontig <- df %>% group_by(contig) %>% summarise(
     mean_snps = round(mean(n_snp), digits = 0),
     median_snps = median(n_snp),
     mean_blocksize = round(mean(block_length), digits = 0),
-    median_blocksize = median(block_length),
+    N50 = NX(block_length, 50),
     max_blocksize = max(block_length)
   )
 
@@ -165,7 +177,7 @@ DT::datatable(
     buttons = list(list(extend = "csv",filename = "phasing_per_contig")), 
     scrollX = TRUE
   ),
-  colnames = c("Contig", "Total Haplotypes", "Mean SNPs", "Median SNPs", "Mean Haplotype Length", "Median Haplotype Length", "Largest Haplotype"),
+  colnames = c("Contig", "Total Haplotypes", "Mean SNPs", "Median SNPs", "Mean Haplotype Length", "Haplotype N50", "Largest Haplotype"),
   fillContainer = T
 )
 ```
@@ -248,7 +260,7 @@ persample <- df %>% group_by(sample) %>% summarise(
     mean_snps = round(mean(n_snp), digits = 0),
     median_snps = median(n_snp),
     mean_blocksize = round(mean(block_length), digits = 0),
-    median_blocksize = median(block_length),
+    N50 = NX(block_length, 50),
     max_blocksize = max(block_length)
 )
 
@@ -261,7 +273,7 @@ DT::datatable(
     buttons = list(list(extend = "csv",filename = "phasing_per_sample")), 
     scrollX = TRUE
   ),
-  colnames = c("Sample", "Haplotypes", "Mean SNPs", "Median SNPs", "Mean Haplotype Length", "Median Haplotype Length", "Largest Haplotype"),
+  colnames = c("Sample", "Haplotypes", "Mean SNPs", "Median SNPs", "Mean Haplotype Length", "Haplotype N50", "Largest Haplotype"),
   fillContainer = T
 )
 ```
diff --git a/harpy/snakefiles/downsample.smk b/harpy/snakefiles/downsample.smk
new file mode 100644
index 000000000..1cbe7563d
--- /dev/null
+++ b/harpy/snakefiles/downsample.smk
@@ -0,0 +1,151 @@
+import os
+import re
+import gzip
+import pysam
+import logging
+
+onstart:
+    logger.logger.addHandler(logging.FileHandler(config["snakemake_log"]))
+onsuccess:
+    os.remove(logger.logfile)
+onerror:
+    os.remove(logger.logfile)
+
+outdir      = config["output_directory"]
+inputs      = config["inputs"]
+invalids    = config["invalid_proportion"]
+random_seed = config.get("random_seed", None)
+downsample  = config["downsample"]
+prefix      = config["prefix"]
+infiles     = dict(zip(inputs, inputs))
+is_fastq    = True if len(inputs) == 2 else False
+
+if is_fastq:
+    try:
+        with gzip.open(inputs[0], 'rt') as f:
+            f.read(10)
+        is_gzip = True
+    except gzip.BadGzipFile:
+        is_gzip = False
+else:
+    is_gzip = False
+
+rule bam_convert:
+    input:
+        inputs
+    output:
+        temp(f"{outdir}/input.bam")
+    threads:
+        workflow.cores
+    shell:
+        """
+        samtools import -@ {threads} -T "*" {input} -O BAM > {output}
+        """
+
+rule sample_barcodes:
+    input:
+        f"{outdir}/input.bam" if is_fastq else inputs[0]
+    output:
+        f"{outdir}/{prefix}.barcodes"
+    log:
+        f"{outdir}/logs/sampled_barcodes.log"
+    threads:
+        workflow.cores
+    params:
+        inv_prop = f"-i {invalids}",
+        downsample_amt = f"-d {downsample}",
+        bx_tag = "-b BX",
+        random_seed = f"-r {random_seed}" if random_seed else ""
+    shell:
+        "extract_bxtags.py {params} {input} > {output} 2> {log}"
+
+rule index_barcodes:
+    input:
+        lambda wc: infiles[wc.inputfile]
+    output:
+        bci = temp("{inputfile}.bci"),
+        bai = temp("{inputfile}.bai") if not is_fastq else [],
+        gzi = temp("{inputfile}i") if is_fastq and is_gzip else []
+    threads:
+        workflow.cores
+    run:
+        if is_fastq:
+            gz_arg = "--gzip" if is_gzip else ""
+            shell(f"LRez index fastq -t {threads} -f {input} -o {output.bci} {gz_arg}")
+        else:
+            shell(f"samtools index {input}")
+            shell(f"LRez index bam --offsets -t {threads} -b {input} -o {output.bci}")
+
+rule downsample:
+    input:
+        bam = inputs[0],
+        bai = inputs[0] + ".bai",
+        bc_index = inputs[0] + ".bci",
+        bc_list = f"{outdir}/{prefix}.barcodes"
+    output:
+        sam = temp(f"{outdir}/{prefix}.sam"),
+        bam = f"{outdir}/{prefix}.bam"
+    threads:
+        workflow.cores
+    shell:
+        """
+        samtools view -H {input.bam} > {output.sam}
+        LRez query bam -t {threads} -b {input.bam} -i {input.bc_index} -l {input.bc_list} >> {output.sam}
+        samtools view -O BAM {output.sam} > {output.bam}
+        """
+
+rule downsample_read_1:
+    input:
+        fastq = inputs[0],
+        bc_index = inputs[0] + ".bci",
+        fq_index = inputs[0] + "i",
+        bc_list = f"{outdir}/{prefix}.barcodes"
+    output:
+        f"{outdir}/{prefix}.R1.fq.gz"
+    params:
+        "--gzip" if is_gzip else ""
+    threads:
+        workflow.cores
+    shell:
+        "LRez query fastq -t {threads} -f {input.fastq} -i {input.bc_index} -l {input.bc_list} {params} | bgzip > {output}"
+
+rule downsample_read_2:
+    input:
+        file = inputs[-1],
+        bc_index = inputs[-1] + ".bci",
+        fq_index = inputs[-1] + "i",
+        bc_list = f"{outdir}/{prefix}.barcodes"
+    output:
+        f"{outdir}/{prefix}.R2.fq.gz"
+    params:
+        "--gzip" if is_gzip else ""
+    threads:
+        workflow.cores
+    shell:
+        "LRez query fastq -t {threads} -f {input.file} -i {input.bc_index} -l {input.bc_list} {params} | bgzip > {output}"
+
+rule workflow_summary:
+    default_target: True
+    input:
+        f"{outdir}/{prefix}.bam" if not is_fastq else [],
+        collect(f"{outdir}/{prefix}.R" + "{FR}.fq.gz", FR = [1,2]) if is_fastq else []
+    params:
+        random_seed = f"-r {random_seed}" if random_seed else ""
+    run:
+        summary = ["The harpy downsample workflow ran using these parameters:"]
+        summary.append(f"The provided input file(s):\n\t" + "\n\t".join(inputs))
+        convs = "The FASTQ files were converted into a BAM file with:\n"
+        convs += "\tsamtools import -T * fastq1 fastq2"
+        if is_fastq:
+            summary.append(convs)
+        extraction = "Barcodes were extracted and sampled using:\n"
+        extraction += f"\textract_bxtags.py -i {invalids} -b BX -d {downsample} {params.random_seed} input.bam"
+        summary.append(extraction)
+        lrez = "The inputs were indexed and downsampled using LRez:\n"
+        if is_fastq:
+            lrez += "\tLRez query fastq -f fastq -i index.bci -l barcodes.txt"
+        else:
+            lrez += "\tLRez query bam -b bam -i index.bci -l barcodes.txt"
+        summary.append(lrez)
+        with open(outdir + "/workflow/downsample.summary", "w") as f:
+            f.write("\n\n".join(summary))
diff --git a/harpy/snakefiles/sv_leviathan.smk b/harpy/snakefiles/sv_leviathan.smk
index 4aa54074e..929b0e5a4 100644
--- a/harpy/snakefiles/sv_leviathan.smk
+++ b/harpy/snakefiles/sv_leviathan.smk
@@ -61,8 +61,8 @@ rule index_barcode:
         temp(outdir + "/lrezIndexed/{sample}.bci")
     threads:
         max(10, workflow.cores)
-    conda:
-        f"{envdir}/variants.yaml"
+    container:
+        None
     shell:
         "LRez index bam --threads {threads} -p -b {input.bam} -o {output}"
 
diff --git a/harpy/snakefiles/sv_leviathan_pop.smk b/harpy/snakefiles/sv_leviathan_pop.smk
index 8680fa3fd..60adf24a2 100644
--- a/harpy/snakefiles/sv_leviathan_pop.smk
+++ b/harpy/snakefiles/sv_leviathan_pop.smk
@@ -108,8 +108,8 @@ rule index_barcode:
         temp(outdir + "/lrez_index/{population}.bci")
     threads:
         max(10, workflow.cores)
-    conda:
-        f"{envdir}/variants.yaml"
+    container:
+        None
     shell:
         "LRez index bam -p -b {input.bam} -o {output} --threads {threads}"
 
diff --git a/resources/harpy.yaml b/resources/harpy.yaml
index 14652b913..fd7a6db3a 100644
--- a/resources/harpy.yaml
+++ b/resources/harpy.yaml
@@ -6,6 +6,7 @@ dependencies:
   - apptainer
   - bcftools =1.20
   - conda >24.7
+  - lrez
   - pysam
   - python
   - rich-click
diff --git a/resources/meta.yaml b/resources/meta.yaml
index f7b81569d..3c33871fd 100644
--- a/resources/meta.yaml
+++ b/resources/meta.yaml
@@ -36,6 +36,7 @@ requirements:
     - apptainer
     - bcftools =1.20
     - conda >24.7
+    - lrez
     - pysam
     - python
     - rich-click