rule make_scaled_bigwig:
    input:
        CHROM_SIZES,
        bam = lambda wildcards: replicate_label_to_bams[wildcards.replicate_label],
    output:
        bg_plus = temp("output/bedgraphs/scaled/plus/{replicate_label}.scaled.plus.bg"),
        bg_minus = temp("output/bedgraphs/scaled/minus/{replicate_label}.scaled.minus.bg"),
        bw_plus = "output/bigwigs/scaled/plus/{replicate_label}.scaled.plus.bw",
        bw_minus = "output/bigwigs/scaled/minus/{replicate_label}.scaled.minus.bw",
    params:
        error_file = "stderr/{replicate_label}.make_bigwig.err",
        out_file = "stdout/{replicate_label}.make_bigwig.out",
        run_time = "40:00",
        memory = "1000",
        job_name = "make_bigwig"
    benchmark: "benchmarks/bigwigs/unassigned_experiment.{replicate_label}.make_bigwig.txt"
    container:
        "docker://howardxu520/skipper:bedtools_2.31.0"
    shell:
        "factor=$(samtools idxstats {input.bam} | awk '{{sum += $3}} END {{print 10**6 / sum}}');"
        "bedtools genomecov -scale $factor -split -strand + -bg -ibam {input.bam} | sort -k1,1 -k2,2n | grep -v EBV > {output.bg_plus};"
        "bedtools genomecov -scale $factor -split -strand - -bg -ibam {input.bam} | sort -k1,1 -k2,2n | grep -v EBV > {output.bg_minus};"
        "{TOOL_DIR}/bedGraphToBigWig {output.bg_plus} {CHROM_SIZES} {output.bw_plus};" 
        "{TOOL_DIR}/bedGraphToBigWig {output.bg_minus} {CHROM_SIZES} {output.bw_minus};"

FROM jupyter/datascience-notebook:hub-2.0.2

(base) shuhaoxu@Shuhaos-MBP 1.39.3 % docker build -t deseq2/1.39.3 .
[+] Building 617.1s (10/12)                                                                          
 => [internal] load .dockerignore                                                               0.0s
 => => transferring context: 2B                                                                 0.0s
 => [internal] load build definition from Dockerfile                                            0.0s
 => => transferring dockerfile: 1.62kB                                                          0.0s
 => [internal] load metadata for docker.io/jupyter/datascience-notebook:hub-2.2.2               1.1s
 => [auth] jupyter/datascience-notebook:pull token for registry-1.docker.io                     0.0s
 => [1/7] FROM docker.io/jupyter/datascience-notebook:hub-2.2.2@sha256:f5984966ed1024e70369860  0.0s
 => [internal] load build context                                                               0.0s
 => => transferring context: 825B                                                               0.0s
 => CACHED [2/7] COPY apt-packages.txt /tmp/apt-packages.txt                                    0.0s
 => [3/7] COPY conda-packages.txt /tmp/conda-packages.txt                                       0.0s
 => [4/7] RUN apt-get update && xargs apt-get install -y < /tmp/apt-packages.txt              231.7s
 => ERROR [5/7] RUN mamba install -y -c bioconda -c conda-forge --file /tmp/conda-packages.t  384.7s 
------                                                                                               
 > [5/7] RUN mamba install -y -c bioconda -c conda-forge --file /tmp/conda-packages.txt:             
------                                                                                               
Dockerfile:26                                                                                        
--------------------                                                                                 
  24 |     
  25 |     # Install additional R packages from conda-forge using mamba
  26 | >>> RUN mamba install -y -c bioconda -c conda-forge --file /tmp/conda-packages.txt
  27 |     
  28 |     RUN Rscript -e 'install.packages("devtools", repos = "https://cran.us.r-project.org")'
--------------------
ERROR: failed to solve: process "/bin/bash -o pipefail -c mamba install -y -c bioconda -c conda-forge --file /tmp/conda-packages.txt" did not complete successfully: exit code: 137