diff --git a/workflow_avamb/README.md b/workflow_avamb/README.md
index ca2d5a28..ae7a3a36 100644
--- a/workflow_avamb/README.md
+++ b/workflow_avamb/README.md
@@ -6,12 +6,11 @@ In short it will:
 
 ```
 1. Filter contigs for 2000bp and rename them to conform with the multi-split workflow
-2. Index resulting contig-file with minimap2 and create a sequence dictionary
-3. Map reads with minimap2 to the combined contig set
-4. Sort bam-files
-5. Run Vamb and Aamb to bin the contigs, generating 3 sets of bins: vae_bins, aae_z_bins and aae_y_bins
-6. Determine completeness and contamination of the bins using CheckM2
-7. Dereplicate near complete (or whichever completeness and contamination thresholds were set), assuring contigs are present in one bin only.
+2. Map reads with strobealign to the combined contig set
+3. Sort bam-files
+4. Run Vamb and Aamb to bin the contigs, generating 3 sets of bins: vae_bins, aae_z_bins and aae_y_bins
+5. Determine completeness and contamination of the bins using CheckM2
+6. Dereplicate near complete (or whichever completeness and contamination thresholds were set), assuring contigs are present in one bin only.
 ```
 
 The nice thing about using snakemake for this is that it will keep track of which jobs have finished and it allows the workflow to be run on different hardware such as a laptop, a linux workstation and a HPC facility (currently with qsub). Keep in mind that there are three different paths, (named directed acyclic graphs in snakemake), that can be executed by snakemake depending on the outputs generated during the workflow and complicating a bit the interpretation of the snakemake file. That's why we added some comments for each rule briefily explaining their purpose. Feel free to reach us if you encounter any problems.  
diff --git a/workflow_avamb/avamb.snake.conda.py b/workflow_avamb/avamb.snake.conda.smk
similarity index 76%
rename from workflow_avamb/avamb.snake.conda.py
rename to workflow_avamb/avamb.snake.conda.smk
index 62a8b970..a7d088fb 100644
--- a/workflow_avamb/avamb.snake.conda.py
+++ b/workflow_avamb/avamb.snake.conda.smk
@@ -14,6 +14,7 @@ def get_config(name, default, regex):
         raise ValueError(
             f"Config option \"{name}\" is \"{res}\", but must conform to regex \"{regex}\"")
     return res
+    
 
 
 # set configurations
@@ -106,31 +107,29 @@ def get_config(name, default, regex):
         "avamb"
     shell: "python {params.path} {output} {input} -m {MIN_CONTIG_SIZE}"
 
-# Create abundance tables by aligning reads to the catalogue
-rule strobealign:
-    input:
-        contigs = os.path.join(OUTDIR,"contigs.flt.fna.gz"), 
-        fq = lambda wildcards: sample2path[wildcards.sample],
-    output: temp(os.path.join(OUTDIR, "mapped", "{sample}.aemb.tsv"))
-    params:
-        walltime="864000",
-        nodes="1",
-        ppn=SA_PPN
-    resources:
-        mem=SA_MEM
-    threads:
-        int(SA_PPN)
-    conda:
-        "envs/strobealign.yaml"
-    log:
-        out_sa = os.path.join(OUTDIR,"log/map/{sample}.strobealign.log"),
-        o = os.path.join(OUTDIR,"log/map/{sample}.strobealign.o"),
-        e = os.path.join(OUTDIR,"log/map/{sample}.strobealign.e")
-    conda:
-        "envs/strobealign.yaml"
-    shell:
-        "strobealign -t {threads} --aemb {input.contigs} {input.fq}"
-        " > {output} 2> {log.out_sa}"
+# # Create abundance tables by aligning reads to the catalogue
+# rule strobealign:
+#     input:
+#         contigs = os.path.join(OUTDIR,"contigs.flt.fna.gz"), 
+#         fq = lambda wildcards: sample2path[wildcards.sample],
+#     output: temp(os.path.join(OUTDIR, "mapped", "{sample}.aemb.tsv"))
+#     params:
+#         walltime="864000",
+#         nodes="1",
+#         ppn=SA_PPN
+#     resources:
+#         mem=SA_MEM
+#     threads:
+#         int(SA_PPN)
+#     conda:
+#         "envs/strobealign.yaml"
+#     log:
+#         out_sa = os.path.join(OUTDIR,"log/map/{sample}.strobealign.log"),
+#         o = os.path.join(OUTDIR,"log/map/{sample}.strobealign.o"),
+#         e = os.path.join(OUTDIR,"log/map/{sample}.strobealign.e")
+#     shell:
+#         "strobealign -t {threads} --aemb {input.contigs} {input.fq}"
+#         " > {output} 2> {log.out_sa}"
 
 rule create_abundance_tsv:
     input:
@@ -154,9 +153,26 @@ def get_config(name, default, regex):
         e = os.path.join(OUTDIR,"log/contigs/abundance.e")
     conda:
         "avamb"
-    shell: "cat <(echo -e 'contigname\tdepht') {input.files} > {output}"
+    shell: 
+        """
+        # TODO go back to the orginal
+
+        # Paste the abundances files together, such that the first column is the contigname 
+        # and the rest of the rows are the depht.
+        # The sed command gets every second row, 
+        # meaning it extracts the depht column from the abundance files
+        # Might want to refactor this as a python script.
+        paste {input.files} \
+        | cut -f1 \
+        | paste - {input.files} \
+        | sed -r 's/\\t[^\\t]*(\\t|$)/\\1/g' \
+        | cat <(echo "contigname {input.files}" | sed 's= =\\t=g') -  > {output}
+
+        # Getting every second column:
+        # https://www.unix.com/shell-programming-and-scripting/253617-printing-every-alternate-columns-text-file.html
+        """
 
-# Generate the 3 sets of clusters and bins
+# Generate the 2 sets of clusters and bins from running avamb
 rule run_avamb:
     input:
         contigs=os.path.join(OUTDIR,"contigs.flt.fna.gz"),
@@ -165,7 +181,7 @@ def get_config(name, default, regex):
         outdir_avamb=directory(os.path.join(OUTDIR,"avamb")),
         clusters_aae_z=os.path.join(OUTDIR,"avamb/aae_z_clusters_split.tsv"),
         clusters_aae_y=os.path.join(OUTDIR,"avamb/aae_y_clusters_split.tsv"),
-        clusters_vamb=os.path.join(OUTDIR,"avamb/vae_clusters_split.tsv"),
+        # clusters_vamb=os.path.join(OUTDIR,"avamb/vae_clusters_split.tsv"),
         composition=os.path.join(OUTDIR,"avamb/composition.npz"),
     params:
         walltime="86400",
@@ -197,10 +213,84 @@ def get_config(name, default, regex):
         touch {log.vamb_out}
         """
 
+# Generate the clusters from running vamb
+rule run_vamb:
+    input:
+        contigs=os.path.join(OUTDIR,"contigs.flt.fna.gz"),
+        abundance=os.path.join(OUTDIR,"abundance.tsv")
+    output:
+        outdir_vamb=directory(os.path.join(OUTDIR,"default_vamb")),
+        clusters_vamb=os.path.join(OUTDIR,"default_vamb/vae_clusters_split.tsv"),
+    params:
+        walltime="86400",
+        nodes="1",
+        ppn=AVAMB_PPN,
+        cuda="--cuda" if CUDA else ""
+    resources:
+        mem=AVAMB_MEM
+    threads:
+        int(avamb_threads)
+    conda:
+        "avamb" 
+    log:
+        vamb_out=os.path.join(OUTDIR,"tmp/vamb_finished.log"),
+        o=os.path.join(OUTDIR,'log','run_vamb.out'),
+        e=os.path.join(OUTDIR,'log','run_vamb.err')
+    shell:
+        """
+        rm -rf {output.outdir_vamb} # Snakemake creates an empty dir, this removes it before running vamb, as vamb will check whether the dir exist and dont run if it does.
+        vamb bin default --outdir {output.outdir_vamb} --fasta {input.contigs} -p {threads} \
+        --abundance_tsv {input.abundance} -m {MIN_CONTIG_SIZE} --minfasta {MIN_BIN_SIZE}  {params.cuda}  {AVAMB_PARAMS}
+        """
+
+rule format_vamb_output:
+    input:        
+        clusters_vamb=os.path.join(OUTDIR,"default_vamb/vae_clusters_split.tsv"),
+        clusters_aae_z=os.path.join(OUTDIR,"avamb/aae_z_clusters_split.tsv"),
+        clusters_aae_y=os.path.join(OUTDIR,"avamb/aae_y_clusters_split.tsv"),
+    output:
+        os.path.join(OUTDIR,"tmp/format_vamb_done.txt"),
+    params:
+        walltime="300",
+        nodes="1",
+        ppn="1"
+    resources:
+        mem="1GB"
+    log:
+        o=os.path.join(OUTDIR,'log','samples_with_bins.out'),
+        e=os.path.join(OUTDIR,'log','samples_with_bins.err')
+    threads:
+        1
+    shell:
+        """
+        # rename the default vamb clusternames to not overlap with the aae clusternames, adding X at the end of each
+        ls {OUTDIR}/default_vamb/bins | sed 's/.fna//' \
+            | xargs -I __ mv {OUTDIR}/default_vamb/bins/__.fna {OUTDIR}/default_vamb/bins/__X.fna
+        mv {OUTDIR}/default_vamb/bins/* {OUTDIR}/avamb/bins
+
+        # Also rename the clusters in vae_clusters_split so the cluster named are equivalient to above
+        cat {input.clusters_vamb} | awk '{{printf "%sX\\t%s\\n", $1, $2}}' \
+            |  tail -n +2 | cat <(echo -e "clustername\\tcontigname") - > {input.clusters_vamb}_x
+        mv {input.clusters_vamb}_x {input.clusters_vamb}
+
+        # Go through each sample and make a dir for each containing the bins
+        # then move the bins there. This is the format Checkm2 uses so we need to convert to it
+        dir={OUTDIR}/avamb/bins
+        for sample in $(ls $dir | cut -f1 -d 'C' | sort | uniq)
+            do
+            mkdir -p $dir/$sample
+            # TODO should not crash if allready have been run 
+            find $dir -type f -name $sample'*' | xargs -I X mv X $dir/$sample
+        done
+
+        touch {output}
+        """
+
 # Evaluate in which samples bins were reconstructed
 checkpoint samples_with_bins:
     input:        
-        os.path.join(OUTDIR,"tmp/avamb_finished.log")
+        # os.path.join(OUTDIR,"tmp/avamb_finished.log"),
+        os.path.join(OUTDIR,"tmp/format_vamb_done.txt"),
     output:
         os.path.join(OUTDIR,"tmp/samples_with_bins.txt")
     params:
@@ -216,7 +306,10 @@ def get_config(name, default, regex):
     threads:
         1
     shell:
-        "find {OUTDIR}/avamb/bins/*/ -type d ! -empty |sed 's=.*bins/==g'  |sed 's=/==g'  > {output}"
+        """
+        # Get the names of each sample
+        find {OUTDIR}/avamb/bins/* -type d ! -empty |sed 's=.*bins/==g'  |sed 's=/==g'  > {output}
+        """
 
 
 def samples_with_bins_f(wildcards):
@@ -242,8 +335,8 @@ def samples_with_bins_f(wildcards):
         o=os.path.join(OUTDIR,'log','checkm2_{sample}.out'),
         e=os.path.join(OUTDIR,'log','checkm2_{sample}.err')
 
-    conda: 
-        "checkm2" 
+    conda:
+        "envs/checkm2.yaml"
     shell:
         """
         checkm2 predict --threads {threads} --input {OUTDIR}/avamb/bins/{wildcards.sample}/*.fna --output-directory {OUTDIR}/tmp/checkm2_all/{wildcards.sample}
@@ -276,7 +369,7 @@ def samples_with_bins_f(wildcards):
 #   - {bin : bin_path}             
 rule create_cluster_scores_bin_path_dictionaries:
     input:
-        checkm2_finished_log_file = os.path.join(OUTDIR,"tmp/checkm2_finished.txt")
+        checkm2_finished_log_file = os.path.join(OUTDIR,"tmp/checkm2_finished.txt"),
     output:
         cluster_score_dict_path_avamb = os.path.join(OUTDIR,"tmp/cs_d_avamb.json"),
         bin_path_dict_path_avamb = os.path.join(OUTDIR,"tmp/bp_d_avamb.json"),
@@ -305,7 +398,7 @@ def samples_with_bins_f(wildcards):
         composition=os.path.join(OUTDIR,"avamb/composition.npz"),
         clusters_aae_z=os.path.join(OUTDIR,"avamb/aae_z_clusters_split.tsv"),
         clusters_aae_y=os.path.join(OUTDIR,"avamb/aae_y_clusters_split.tsv"),
-        clusters_vamb=os.path.join(OUTDIR,"avamb/vae_clusters_split.tsv")
+        clusters_vamb=os.path.join(OUTDIR,"default_vamb/vae_clusters_split.tsv")
 
     output:
         clusters_avamb_manual_drep=os.path.join(OUTDIR,"tmp/avamb_manual_drep_clusters.tsv")
@@ -437,6 +530,7 @@ def ripped_bins_avamb_check_output_f(wildcards):
          --output-directory {OUTDIR}/tmp/ripped_bins/checkm2_out 
         touch {log.log_fin}
         """
+
 # As explained in rule create_ripped_bins_avamb, contigs present in three bins were removed from the larger bin.
 # This rule updates the quality scores after removing such contig(s).
 rule update_cs_d_avamb:
@@ -551,23 +645,23 @@ def ripped_bins_avamb_check_output_f(wildcards):
         e=os.path.join(OUTDIR,'log','workflow_finished.err')
     shell:
         """
-        rm -r {OUTDIR}/tmp/checkm2_all/*/protein_files
-        
-        rm -r {OUTDIR}/avamb/bins
+        # TODO uncomment these again
+        # rm -r {OUTDIR}/tmp/checkm2_all/*/protein_files
         
-        mkdir {OUTDIR}/tmp/snakemake_tmp/
-        mv {OUTDIR}/tmp/*log  {OUTDIR}/tmp/snakemake_tmp/
-        mv {OUTDIR}/tmp/*json  {OUTDIR}/tmp/snakemake_tmp/
-        mv {OUTDIR}/tmp/*tsv  {OUTDIR}/tmp/snakemake_tmp/
-        mv {OUTDIR}/tmp/*txt  {OUTDIR}/tmp/snakemake_tmp/
-        mv {OUTDIR}/tmp/ripped_bins {OUTDIR}/tmp/snakemake_tmp/
+        # rm -r {OUTDIR}/avamb/bins
         
-        mv {OUTDIR}/tmp/checkm2_all  {OUTDIR}/tmp/snakemake_tmp/
-        mv {OUTDIR}/avamb/avamb_manual_drep_disjoint_clusters.tsv  {OUTDIR}/Final_clusters.tsv
-        mv {OUTDIR}/abundance.npz {OUTDIR}/tmp/
-        mv {OUTDIR}/mapped {OUTDIR}/tmp/
-        mv {OUTDIR}/contigs.flt.fna.gz {OUTDIR}/tmp/
-
+        # mkdir {OUTDIR}/tmp/snakemake_tmp/
+        # mv {OUTDIR}/tmp/*log  {OUTDIR}/tmp/snakemake_tmp/
+        # mv {OUTDIR}/tmp/*json  {OUTDIR}/tmp/snakemake_tmp/
+        # mv {OUTDIR}/tmp/*tsv  {OUTDIR}/tmp/snakemake_tmp/
+        # mv {OUTDIR}/tmp/*txt  {OUTDIR}/tmp/snakemake_tmp/
+        # mv {OUTDIR}/tmp/ripped_bins {OUTDIR}/tmp/snakemake_tmp/
+        #
+        # mv {OUTDIR}/tmp/checkm2_all  {OUTDIR}/tmp/snakemake_tmp/
+        # mv {OUTDIR}/avamb/avamb_manual_drep_disjoint_clusters.tsv  {OUTDIR}/Final_clusters.tsv
+        # mv {OUTDIR}/abundance.npz {OUTDIR}/tmp/
+        # mv {OUTDIR}/mapped {OUTDIR}/tmp/
+        # mv {OUTDIR}/contigs.flt.fna.gz {OUTDIR}/tmp/
         
 
         touch {output}
diff --git a/workflow_avamb/envs/checkm2.yaml b/workflow_avamb/envs/checkm2.yaml
new file mode 100644
index 00000000..c3980c24
--- /dev/null
+++ b/workflow_avamb/envs/checkm2.yaml
@@ -0,0 +1,6 @@
+channels:
+  - conda-forge
+  - bioconda
+  - defaults
+dependencies:
+  - checkm2
diff --git a/workflow_avamb/envs/checkm2.yml b/workflow_avamb/envs/checkm2.yml
deleted file mode 100644
index 95b0d61d..00000000
--- a/workflow_avamb/envs/checkm2.yml
+++ /dev/null
@@ -1,19 +0,0 @@
-channels:
-  - conda-forge
-  - bioconda
-  - defaults
-dependencies:
-  - python=3.8.15
-  - scikit-learn=0.23.2
-  - h5py=2.10.0
-  - numpy=1.23.2
-  - tensorflow=2.9.1
-  - lightgbm=3.3.2
-  - pandas=1.4.3
-  - scipy=1.9.0
-  - setuptools=65.3.0
-  - requests=2.28.1
-  - packaging=21.3
-  - tqdm=4.64.0
-  - diamond=2.0.15
-  - prodigal=2.6.3