diff --git a/mgnify_pipelines_toolkit/analysis/amplicon/primer_agrep.sh b/mgnify_pipelines_toolkit/analysis/amplicon/primer_agrep.sh
deleted file mode 100644
index f953c14..0000000
--- a/mgnify_pipelines_toolkit/analysis/amplicon/primer_agrep.sh
+++ /dev/null
@@ -1,26 +0,0 @@
-
-# Use agrep to find primer matches with allowed mismatches in given input fasta
-
-mismatch=1
-
-while getopts i:p:n:s: option
-do 
-    case "${option}"
-        in
-        i)input_file=${OPTARG};;
-        p)primer=${OPTARG};;
-        n)mismatch=${OPTARG};;
-        s)strand=${OPTARG};;
-    esac
-done
-
-if [ $strand == 'F' ]; then
-    zcat $input_file | sed -n '2~4p' | awk '{print substr($0,1,50)}' > ./substrings.txt
-elif [ $strand == 'R' ]; then
-    zcat $input_file | sed -n '2~4p' | awk '{print substr($0,length($0)-49,50)}' > ./substrings.txt
-fi
-
-/hps/nobackup/rdf/metagenomics/service-team/users/chrisata/agrep/agrep -V0 -c -$mismatch $primer ./substrings.txt
-
-
-# zcat $input_file | sed -n '2~2p' | awk '{print substr($0,1,50)substr($0,length($0)-49,50)}' > ./substrings.txt
diff --git a/mgnify_pipelines_toolkit/analysis/amplicon/standard_primer_agrep.py b/mgnify_pipelines_toolkit/analysis/amplicon/standard_primer_agrep.py
deleted file mode 100644
index 9d045eb..0000000
--- a/mgnify_pipelines_toolkit/analysis/amplicon/standard_primer_agrep.py
+++ /dev/null
@@ -1,284 +0,0 @@
-
-import argparse
-from collections import defaultdict
-import os
-import subprocess
-
-from Bio.Seq import Seq
-
-from mgnify_pipelines_toolkit.analysis.amplicon.amplicon_utils import primer_regex_query_builder, get_read_count
-
-def parse_args():
-
-    parser = argparse.ArgumentParser()
-
-    parser.add_argument("-i", "--input", required=True, type=str, help="Path to merged FASTQ to look for primers")
-    parser.add_argument("-p", "--primers", required=True, type=str, help="Path to directory containing standard primers fasta files")
-    parser.add_argument("-s", "--sample", required=True, type=str, help="Sample ID")
-    parser.add_argument("-o", "--output", required=True, type=str, help="Output path")
-    args = parser.parse_args()
-  
-    _INPUT = args.input
-    _PRIMERS = args.primers
-    _SAMPLE = args.sample
-    _OUTPUT = args.output
-
-    return _INPUT, _PRIMERS, _SAMPLE, _OUTPUT
-
-def parse_std_primers(_PRIMERS):
-    """
-    Parse the library of standard primers.
-
-    Reads the fasta files in the given directory
-    Primer names (which are the fasta headers) are labeled with F or R for 5'-3' and 3'-5' primers respectively
-
-    Returns two dictionaries:
-        std_primer_dict_regex
-            key: region+primer name
-            val: primer sequence from 5' to 3'
-        std_primer_dict
-            key: region+primer name
-            val: primer sequence from 5' to 3' for forward primers, 3' to 5' for reverse
-    """
-
-    std_primer_dict_regex = defaultdict(defaultdict)
-    std_primer_dict = defaultdict(defaultdict)
-
-    dir = os.listdir(_PRIMERS)
-    dir = [ f'{_PRIMERS}/{path}' for path in dir ]
-    
-    rev_flag = False
-
-    for path in dir:
-        region = path.split('/')[-1].split('.')[0]
-        with open(path, 'r') as fr:
-            key = ''
-            for line in fr:
-                line = line.strip()
-                if line[0] == '>':
-                    if 'R' in line: # If a primer is a reverse primer
-                        rev_flag = True
-                    key = line[1:]
-                else:
-                    if rev_flag:
-                        rev_conv = str(Seq(line).reverse_complement())
-                        line = rev_conv
-                        rev_flag = False
-
-                    primer = primer_regex_query_builder(line)
-                    std_primer_dict_regex[region][key] = primer
-                    std_primer_dict[region][key] = line
-
-    return std_primer_dict_regex, std_primer_dict
-
-def run_primer_agrep_once(input_path, input_primer, strand, mismatches=1):
-    """
-    Run the primer_agrep script.
-
-    Takes one primer, strand, and fastq input
-    Returns number of agrep matches
-    """
-
-    cmd = [
-        'bash',
-        './mgnify_pipelines_toolkit/analysis/amplicon/primer_agrep.sh',
-        '-i',
-        input_path,
-        '-p',
-        input_primer,
-        '-n',
-        str(mismatches),
-        '-s',
-        strand
-    ]
-
-    proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
-    stdout, stderr = proc.communicate()
-    output = stdout.decode('ascii')
-    if output == '':
-        output = 0
-    else:
-        output = float(output.strip())
-
-    return output
-
-def get_primer_props(std_primer_dict_regex, input_path):
-    """
-    Look for the standard primers in the input fastq file.
-
-    Will loop through the dictionary of primers, using approximate grep (agrep) to find matching primers.
-    If a std primer is present above a set threshold proportion, it is collected. Both strands are searched for.
-    If there is an std primer for both the F and R strands, the maximum prop for each strand is chosen and the pair
-    is output as a combination.
-
-    Returns a list containing two elements:
-        max_region: the amplified region the chosen primers belong to
-        max_primers: dictionary containing the F and/or R primers that were chosen
-    """
-
-    threshold = 0.60 # Arbitrary threshold for collecting a matched primer
-    read_count = get_read_count(input_path, 'fastq') # Get read count of fastq file to calculate proportion with
-    res_dict = defaultdict(defaultdict)
-
-    # Loop through every primer region
-    for region, primer in std_primer_dict_regex.items():
-        res_dict[region]['F'] = {}
-        res_dict[region]['R'] = {}
-
-        # Loop through every primer of a certain region
-        for primer_name, primer_seq in primer.items():
-            
-            region_name_str = f'{region};{primer_name}'
-            primer_count = 0.0
-
-            if 'F' in primer_name:
-                primer_count = run_primer_agrep_once(input_path, primer_seq, 'F', 1) # Get proportion of a F primer with agrep
-            elif 'R' in primer_name:
-                primer_count = run_primer_agrep_once(input_path, primer_seq, 'R', 1) # Get proportion of a R primer with agrep
-
-            try:
-                primer_prop = primer_count / read_count
-            except ZeroDivisionError:
-                primer_prop = 0
-
-            if 'F' in primer_name:
-                if primer_prop > threshold: # Only collect primer if it's above threshold
-                    res_dict[region]['F'][primer_name] = primer_prop
-            elif 'R' in primer_name:
-                if primer_prop > threshold: # Only collect primer if it's above threshold
-                    res_dict[region]['R'][primer_name] = primer_prop
-
-            print(f'{region_name_str}: {primer_prop}')
-        
-        # If an F or/and R primer wasn't found then just remove it from the dictionary
-        if res_dict[region]['F'] == {}:
-            res_dict[region].pop('F')
-        if res_dict[region]['R'] == {}:
-            res_dict[region].pop('R')
-        
-
-    singles = defaultdict(str)
-    doubles = defaultdict(list)
-
-    double_status = False # Flag for whether primers were found on both strands
-
-    #  Loop through every collected primer and put primers in singles or doubles
-    for region in res_dict.keys():
-        strands = res_dict[region]
-                
-        for strand in strands.keys():
-            primers = strands[strand]
-            max_prop = 0
-            max_name = ''
-            for primer_name, prop in primers.items():
-                if prop > max_prop:
-                    max_prop = prop
-                    max_name = primer_name
-                
-            if len(strands.keys()) == 2:
-                double_status = True
-                doubles[region].append({max_name: max_prop})
-            elif len(strands.keys()) == 1:
-                singles[region] = {max_name: max_prop}
-
-    max_region = ''
-    max_primers = {}
-    max_mean_prop = 0
-    
-    # if at least one pair of primers was collected
-    if double_status:
-        for region in doubles: # Loop through all pairs of primers and choose the best one
-            primers = doubles[region]
-
-            f_primer_name = list(primers[0].keys())[0]
-            r_primer_name = list(primers[1].keys())[0]
-            f_primer_prop = primers[0][f_primer_name]
-            r_primer_prop = primers[1][r_primer_name]
-            
-            mean_prop = (f_primer_prop + r_primer_prop) / 2.0
-            if mean_prop > max_mean_prop:
-                max_mean_prop = mean_prop
-                max_region = region
-                max_primers = [{f_primer_name: f_primer_prop}, {r_primer_name: r_primer_prop}]
-
-    else:
-        for region in singles: # Choose the best single primer
-            primer = singles[region]
-            primer_name = list(primer.keys())[0]
-            prop = primer[primer_name]
-            if prop > max_mean_prop:
-                max_mean_prop = prop
-                max_region = region
-                max_primers = {primer_name: prop}
-
-    if max_region == '':
-        print('No standard library primers!')
-        return([])
-    elif double_status:
-        print('Standard library primers found!')
-        print(f'Region: {max_region}')
-        print(f'Forward Primer: {max_primers[0]}')
-        print(f'Reverse Primer: {max_primers[1]}')
-
-        return([max_region, max_primers[0], max_primers[1]])
-    else:
-        print('Standard library primer found on one strand!')
-        print(f'Region: {max_region}')
-        print(f'Primer: {max_primers}')
-        
-        return([max_region, max_primers])
-
-
-
-def save_out(results, sample_id, output, std_primer_dict):
-    """
-    Save found std primers into a fasta file.
-    """
-
-    with open(f'{output}/{sample_id}_std_primer_out.txt', 'w') as fw_out, open(f'{output}/{sample_id}_std_primers.fasta', 'w') as fw_seq:
-        if results == []:
-            fw_out.write(f'')
-            fw_seq.write(f'')
-        
-        elif len(results) == 2:
-            region = results[0]
-            primer_name = list(results[1].keys())[0]
-            primer_prop = results[1][list(results[1].keys())[0]]
-            seq = std_primer_dict[region][primer_name]
-            if 'R' in primer_name:
-                seq = str(Seq(seq).reverse_complement())
-            fw_out.write(f'{region}\n')
-            fw_out.write(f'{primer_name}: {primer_prop}')
-
-            fw_seq.write(f'>{primer_name}\n{seq}')
-            
-        
-        elif len(results) == 3:
-            region = results[0]
-            f_primer_name = list(results[1].keys())[0]
-            f_primer_prop = results[1][list(results[1].keys())[0]]
-            f_seq = std_primer_dict[region][f_primer_name]
-            r_primer_name = list(results[2].keys())[0]
-            r_primer_prop = results[2][list(results[2].keys())[0]]
-            r_seq = std_primer_dict[region][r_primer_name]
-            r_seq = str(Seq(r_seq).reverse_complement())
-            
-
-            fw_out.write(f'{region}\n')
-            fw_out.write(f'{f_primer_name}: {f_primer_prop}\n')
-            fw_out.write(f'{r_primer_name}: {r_primer_prop}')
-
-            fw_seq.write(f'>{f_primer_name}\n{f_seq}\n')
-            fw_seq.write(f'>{r_primer_name}\n{r_seq}\n')
-
-    
-def main():
-    
-    _INPUT, _PRIMERS, _SAMPLE, _OUTPUT = parse_args()
-    std_primer_dict_regex, std_primer_dict = parse_std_primers(_PRIMERS) # Parse std primer library into dictionaries
-    results = get_primer_props(std_primer_dict_regex, _INPUT) # Find all the std primers in the input and select most common
-    save_out(results, _SAMPLE, _OUTPUT, std_primer_dict)
-    
-
-if __name__ == "__main__":
-    main()
\ No newline at end of file
diff --git a/pyproject.toml b/pyproject.toml
index 69a9bd1..ae26cfe 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -49,5 +49,4 @@ classify_var_regions = "mgnify_pipelines_toolkit.analysis.amplicon.classify_var_
 find_mcp_inflection_points = "mgnify_pipelines_toolkit.analysis.amplicon.find_mcp_inflection_points:main"
 make_asv_count_table = "mgnify_pipelines_toolkit.analysis.amplicon.make_asv_count_table:main"
 remove_ambiguous_reads = "mgnify_pipelines_toolkit.analysis.amplicon.remove_ambiguous_reads:main"
-rev_comp_se_primers = "mgnify_pipelines_toolkit.analysis.amplicon.rev_comp_se_primers:main"
-standard_primer_agrep = "mgnify_pipelines_toolkit.analysis.amplicon.standard_primer_agrep:main"
+rev_comp_se_primers = "mgnify_pipelines_toolkit.analysis.amplicon.rev_comp_se_primers:main"
\ No newline at end of file
diff --git a/tests/unit/analysis/amplicon/standard_primer_agrep/test_standard_primer_agrep.yml b/tests/unit/analysis/amplicon/standard_primer_agrep/test_standard_primer_agrep.yml
deleted file mode 100644
index 31a7095..0000000
--- a/tests/unit/analysis/amplicon/standard_primer_agrep/test_standard_primer_agrep.yml
+++ /dev/null
@@ -1,15 +0,0 @@
-- name: standard_primer_agrep test_wrong_args
-  tags:
-    - standard_primer_agrep
-  exit_code: 2 
-  command: python -m mgnify_pipelines_toolkit.analysis.amplicon.standard_primer_agrep --chromosome X
-  stderr:
-    contains:
-      - "standard_primer_agrep.py: error: the following arguments are required: -i/--input, -p/--primers, -s/--sample, -o/--output"
-- name: standard_primer_agrep test_correct_args
-  tags:
-    - standard_primer_agrep
-  command: python -m mgnify_pipelines_toolkit.analysis.amplicon.standard_primer_agrep -i tests/fixtures/sequences/test.fastq.gz -p tests/fixtures/sequences/standard_primers -s sample -o ./
-  files:
-    - path: "sample_std_primers.fasta"
-      md5sum: f26cdc22a5231d2dbd0831f1f1983dc6