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Script for daily routine

The scripts are used to deal with data in my daily work

Merging metaphlan

# python merge_metaphlan.py \
#   -f dataset/metaphlan/metaphlan_test_filepath.tsv \
#   -p merge_metaphlan \
#   -t s__|t__ \
#   -o result
  
python merge_metaphlan.py \
  -f dataset/metaphlan/metaphlan_test_filepath.tsv \
  -p merge_metaphlan \
  -t species \
  -o result

Merging humann

python merge_humann.py \
  -f dataset/humann/Humann2_pathabundance_test_filepath.tsv \
  -p merge_humann \
  -d humann2 \
  -o result

Calculating md5sum of csv file

Rscript calculate_file_md5sum.R \
  -f dataset/phenotype \
  -p csv \
  -o result

Generating phyloseq object in BJ GI cancer

Rscript generate_phyloseq_for_BJ.R \
  -m dataset/phenotype/bjch_sample_sequence_metadata_20220923.csv \
  -p dataset/metaphlan/metaphlan2_BJ_RoundB_merge.csv \
  -r RoundB \
  -t metaphlan \
  -n metaphlan2 \
  -o result

Summarizing accounts of patients and samples in BJ GI cancer

Rscript Summarize_Patients_Samples.R \
  -a dataset/phyloseq/metaphlan2_BJ_all_ps.RDS \
  -p dataset/phyloseq/metaphlan2_BJ_all_ps_baseline_R6.RDS \
  -o result

Plotting swimming plot in in BJ GI cancer

Rscript BJ_GI_Swimming_plot.R \
  -p dataset/phenotype/bjch_sample_sequence_metadata_20220923.csv \
  -c colon_cancer \
  -n Swimming_Plot \
  -w 10 \
  -g 20 \
  -o result

Obtaining Reads' status from metaphlan pipeline

# fastp & kneaddata
python obtain_metaphlan_ReadsQC.py \
  -f dataset/pipeline_result/BJ_RoundG \
  -p BJ_RoundG_ReadsQC \
  -o result

# only kneaddata
python obtain_metaphlan_ReadsQC.py \
  -f dataset/pipeline_result/BJ_RoundB \
  -p BJ_RoundB_ReadsQC \
  -o result

phyloseq for BJ GI for three types' dataset

Rscript generate_phyloseq_for_BJ_v2.R \
  -m dataset/phenotype/bjch_sample_sequence_metadata_20221008.csv \
  -p dataset/profile/metaphlan2_BJ_RoundB-G_merge.csv \
  -r all \
  -t metaphlan \
  -n metaphlan2 \
  -o result

Integrating phyloseq object per taxa levels into list object

Rscript integrate_taxa_phyloseq_for_BJ.R \
  -p ./dataset/phyloseq/metaphlan2_phylum_BJ_all_ps_total.RDS \
  -c ./dataset/phyloseq/metaphlan2_class_BJ_all_ps_total.RDS \
  -o ./dataset/phyloseq/metaphlan2_order_BJ_all_ps_total.RDS \
  -f ./dataset/phyloseq/metaphlan2_family_BJ_all_ps_total.RDS \
  -g ./dataset/phyloseq/metaphlan2_genus_BJ_all_ps_total.RDS \
  -s ./dataset/phyloseq/metaphlan2_species_BJ_all_ps_total.RDS \
  -n total \
  -d ./result/

Summarizing accounts of patients and samples in BJ GI cancer (version 2)

Rscript Summarize_Patients_Samples_v2.R \
  -a dataset/phyloseq/metaphlan2_BJ_all_metadata_total.csv \
  -b dataset/phyloseq/metaphlan2_phylum_BJ_all_ps_filter.RDS \
  -c dataset/phyloseq/metaphlan2_phylum_BJ_all_ps_baseR6.RDS \
  -d dataset/phyloseq/16s_BJ_all_metadata_total.csv \
  -e dataset/phyloseq/16s_BJ_all_metadata_filter.csv \
  -f dataset/phyloseq/16s_BJ_all_metadata_baseR6.csv \
  -n Summarize_Patients_Samples \
  -o result

checking whether the sra files were successfully downloaded

perl get_update_sra_NCBI.pl \
  -f SRR_Acc_List.txt \
  -d /share/projects/Analytics/IO/zouhua/pipeline/GSE164150/SRA/sra \
  -o SRR_Acc_List_redownload.txt
prefetch --option-file SRR_Acc_List_redownload.txt

converting sra into fastq

find /share/projects/Analytics/IO/zouhua/pipeline/GSE164150/SRA/sra/ -name "*.sra" | \
  perl -e 'print"SampleID\tMode\tPath\n"; while(<>){chomp; $name=(split("\/", $_))[-1]; $name=~s/.sra//g; $type = "PAIRED"; print "$name\t$type\t$_\n";}' \
  > samples.path.tsv
perl sra2fq.pl \
  -f samples.path.tsv \
  -d fastq \
  -p sra_into_fastq
sh sra_into_fastq.sh

scp file between local and remote

perl get_each_scp.pl \
  -f filepath.tsv \
  -s xbiome_102 \
  -d /share/projects/Analytics/IO/zouhua/database/ \
  -o scp_file

rsync files between source and destination directory

python rsync.py \
  -s /share/projects/Analytics/IO/zouhua/pipeline/GSE164150/SRA/sra/ \
  -d /share/projects/Analytics/IO/zouhua/database \
  -p sra \
  -l sra_log.tsv

batch run for scripts

python run_batch_shell.py \
  -m sra_into_fastq.sh \
  -o sra_into_fastq_batch.sh

APAlyzer Expression

Rscript APAlyzer_Expression.R \
  -b bam_file.tsv \
  -r RData \
  -g mm9_REF.RData \
  -c chr19 \
  -e 3UTR \
  -o result