gene_x 0 like s 16 view s
Tags: pipeline
Input data:
ln -s ../raw_data_2024/hCoV229E_Rluc_R1.fastq.gz hCoV229E_Rluc_R1.fastq.gz
ln -s ../raw_data_2024/hCoV229E_Rluc_R2.fastq.gz hCoV229E_Rluc_R2.fastq.gz
ln -s ../raw_data_2024/p10_DMSO_R1.fastq.gz p10_DMSO_R1.fastq.gz
ln -s ../raw_data_2024/p10_DMSO_R2.fastq.gz p10_DMSO_R2.fastq.gz
ln -s ../raw_data_2024/p10_K22_R1.fastq.gz p10_K22_R1.fastq.gz
ln -s ../raw_data_2024/p10_K22_R2.fastq.gz p10_K22_R2.fastq.gz
ln -s ../raw_data_2024/p10_K7523_R1.fastq.gz p10_K7523_R1.fastq.gz
ln -s ../raw_data_2024/p10_K7523_R2.fastq.gz p10_K7523_R2.fastq.gz
ln -s ../raw_data_2025/250506_VH00358_136_AAG3YJ5M5/p20606/p16_DMSO_S29_R1_001.fastq.gz p16_DMSO_R1.fastq.gz
ln -s ../raw_data_2025/250506_VH00358_136_AAG3YJ5M5/p20606/p16_DMSO_S29_R2_001.fastq.gz p16_DMSO_R2.fastq.gz
ln -s ../raw_data_2025/250506_VH00358_136_AAG3YJ5M5/p20607/p16_K22_S30_R1_001.fastq.gz p16_K22_R1.fastq.gz
ln -s ../raw_data_2025/250506_VH00358_136_AAG3YJ5M5/p20607/p16_K22_S30_R2_001.fastq.gz p16_K22_R2.fastq.gz
ln -s ../raw_data_2025/250506_VH00358_136_AAG3YJ5M5/p20608/p16_X7523_S31_R1_001.fastq.gz p16_X7523_R1.fastq.gz
ln -s ../raw_data_2025/250506_VH00358_136_AAG3YJ5M5/p20608/p16_X7523_S31_R2_001.fastq.gz p16_X7523_R2.fastq.gz
Call variant calling using snippy
ln -s ~/Tools/bacto/db/ .;
ln -s ~/Tools/bacto/envs/ .;
ln -s ~/Tools/bacto/local/ .;
cp ~/Tools/bacto/Snakefile .;
cp ~/Tools/bacto/bacto-0.1.json .;
cp ~/Tools/bacto/cluster.json .;
#download CU459141.gb from GenBank
mv ~/Downloads/sequence\(2\).gb db/PP810610.gb
#setting the following in bacto-0.1.json
"fastqc": false,
"taxonomic_classifier": false,
"assembly": true,
"typing_ariba": false,
"typing_mlst": true,
"pangenome": true,
"variants_calling": true,
"phylogeny_fasttree": true,
"phylogeny_raxml": true,
"recombination": false, (due to gubbins-error set false)
"genus": "Alphacoronavirus",
"kingdom": "Viruses",
"species": "Human coronavirus 229E",
"mykrobe": {
"species": "corona"
},
"reference": "db/PP810610.gb"
mamba activate /home/jhuang/miniconda3/envs/bengal3_ac3
(bengal3_ac3) /home/jhuang/miniconda3/envs/snakemake_4_3_1/bin/snakemake --printshellcmds
Summarize all SNPs and Indels from the snippy result directory.
#Output: snippy/summary_snps_indels.csv
# IMPORTANT_ADAPT the array isolates = ["AYE-S", "AYE-Q", "AYE-WT on Tig4", "AYE-craA on Tig4", "AYE-craA-1 on Cm200", "AYE-craA-2 on Cm200"]
python3 ~/Scripts/summarize_snippy_res.py snippy
cd snippy
#grep -v "None,,,,,,None,None" summary_snps_indels.csv > summary_snps_indels_.csv
Using spandx calling variants (almost the same results to the one from viral-ngs!)
mamba activate /home/jhuang/miniconda3/envs/spandx
mkdir ~/miniconda3/envs/spandx/share/snpeff-5.1-2/data/PP810610
cp PP810610.gb ~/miniconda3/envs/spandx/share/snpeff-5.1-2/data/PP810610/genes.gbk
vim ~/miniconda3/envs/spandx/share/snpeff-5.1-2/snpEff.config
/home/jhuang/miniconda3/envs/spandx/bin/snpEff build PP810610 #-d
~/Scripts/genbank2fasta.py PP810610.gb
mv PP810610.gb_converted.fna PP810610.fasta #rename "NC_001348.1 xxxxx" to "NC_001348" in the fasta-file
ln -s /home/jhuang/Tools/spandx/ spandx
(spandx) nextflow run spandx/main.nf --fastq "trimmed/*_P_{1,2}.fastq" --ref PP810610.fasta --annotation --database PP810610 -resume
# Rerun SNP_matrix.sh due to the error ERROR_CHROMOSOME_NOT_FOUND in the variants annotation
cd Outputs/Master_vcf
(spandx) cp -r ../../snippy/hCoV229E_Rluc/reference .
(spandx) cp ../../spandx/bin/SNP_matrix.sh ./
#Note that ${variant_genome_path}=NC_001348 in the following command, but it was not used after command replacement.
#Adapt "snpEff eff -no-downstream -no-intergenic -ud 100 -formatEff -v ${variant_genome_path} out.vcf > out.annotated.vcf" to
"/home/jhuang/miniconda3/envs/bengal3_ac3/bin/snpEff eff -no-downstream -no-intergenic -ud 100 -formatEff -c reference/snpeff.config -dataDir . ref out.vcf > out.annotated.vcf" in SNP_matrix.sh
(spandx) bash SNP_matrix.sh PP810610 .
Calling inter-host variants by merging the results from snippy+spandx (Manually!)
# Inter-host variants（宿主间变异）:一种病毒在两个人之间有不同的基因变异，这些变异可能与宿主的免疫反应、疾病表现或病毒传播的方式相关。
cp All_SNPs_indels_annotated.txt All_SNPs_indels_annotated_backup.txt
vim All_SNPs_indels_annotated.txt
#in the file ids: grep "$(echo -e '\t')353$(echo -e '\t')" All_SNPs_indels_annotated.txt >> All_SNPs_indels_annotated_.txt
#Replace \n with " All_SNPs_indels_annotated.txt >> All_SNPs_indels_annotated_.txt\ngrep "
#Replace grep " --> grep "$(echo -e '\t')
#Replace " All_ --> $(echo -e '\t')" All_
# Potential intra-host variants: 10871, 19289, 23435.
CHROM POS REF ALT TYPE hCoV229E_Rluc_trimmed p10_DMSO_trimmed p10_K22_trimmed p10_K7523_trimmed p16_DMSO_trimmed p16_K22_trimmed p16_X7523_trimmed Effect Impact Functional_Class Codon_change Protein_and_nucleotide_change Amino_Acid_Length Gene_name Biotype
PP810610 1464 T C SNP C C C C C C C missense_variant MODERATE MISSENSE gTt/gCt p.Val416Ala/c.1247T>C 6757 CDS_1 protein_coding
PP810610 1699 C T SNP T T T T T T T synonymous_variant LOW SILENT gtC/gtT p.Val494Val/c.1482C>T 6757 CDS_1 protein_coding
PP810610 6691 C T SNP T T T T T T T synonymous_variant LOW SILENT tgC/tgT p.Cys2158Cys/c.6474C>T 6757 CDS_1 protein_coding
PP810610 6919 C G SNP G G G G G G G synonymous_variant LOW SILENT ggC/ggG p.Gly2234Gly/c.6702C>G 6757 CDS_1 protein_coding
PP810610 7294 T A SNP A A A A A A A missense_variant MODERATE MISSENSE agT/agA p.Ser2359Arg/c.7077T>A 6757 CDS_1 protein_coding
* PP810610 10871 C T SNP C C/T T C/T C/T T C/T missense_variant MODERATE MISSENSE Ctt/Ttt p.Leu3552Phe/c.10654C>T 6757 CDS_1 protein_coding
PP810610 14472 T C SNP C C C C C C C missense_variant MODERATE MISSENSE aTg/aCg p.Met4752Thr/c.14255T>C 6757 CDS_1 protein_coding
PP810610 15458 T C SNP C C C C C C C synonymous_variant LOW SILENT Ttg/Ctg p.Leu5081Leu/c.15241T>C 6757 CDS_1 protein_coding
PP810610 16035 C A SNP A A A A A A A stop_gained HIGH NONSENSE tCa/tAa p.Ser5273*/c.15818C>A 6757 CDS_1 protein_coding
PP810610 17430 T C SNP C C C C C C C missense_variant MODERATE MISSENSE tTa/tCa p.Leu5738Ser/c.17213T>C 6757 CDS_1 protein_coding
* PP810610 19289 G T SNP G G T G G G/T G missense_variant MODERATE MISSENSE Gtt/Ttt p.Val6358Phe/c.19072G>T 6757 CDS_1 protein_coding
PP810610 21183 T G SNP G G G G G G G missense_variant MODERATE MISSENSE tTt/tGt p.Phe230Cys/c.689T>G 1173 CDS_2 protein_coding
PP810610 22636 T G SNP G G G G G G G missense_variant MODERATE MISSENSE aaT/aaG p.Asn714Lys/c.2142T>G 1173 CDS_2 protein_coding
PP810610 23022 T C SNP C C C C C C C missense_variant MODERATE MISSENSE tTa/tCa p.Leu843Ser/c.2528T>C 1173 CDS_2 protein_coding
* PP810610 23435 C T SNP C C T C/T C C/T C/T missense_variant MODERATE MISSENSE Ctt/Ttt p.Leu981Phe/c.2941C>T 1173 CDS_2 protein_coding
PP810610 24512 C T SNP T T T T T T T missense_variant MODERATE MISSENSE Ctc/Ttc p.Leu36Phe/c.106C>T 88 CDS_4 protein_coding
PP810610 24781 C T SNP T T T T T T T missense_variant MODERATE MISSENSE aCt/aTt p.Thr36Ile/c.107C>T 77 CDS_5 protein_coding
PP810610 25163 C T SNP T T T T T T T missense_variant MODERATE MISSENSE Ctt/Ttt p.Leu82Phe/c.244C>T 225 CDS_6 protein_coding
PP810610 25264 C T SNP T T T T T T T synonymous_variant LOW SILENT gtC/gtT p.Val115Val/c.345C>T 225 CDS_6 protein_coding
PP810610 26838 G T SNP T T T T T T T
Calling intra-host variants using viral-ngs
# Intra-host variants（宿主内变异）：同一个人感染了某种病毒，但在其体内的不同细胞或器官中可能存在多个不同的病毒变异株。
#How to run and debug the viral-ngs docker?
# ---- DEBUG_2025_1: using docker instead ----
mkdir viralngs; cd viralngs
ln -s ~/Tools/viral-ngs_docker/Snakefile Snakefile
ln -s ~/Tools/viral-ngs_docker/bin bin
cp ~/DATA_D/Data_Pietschmann_229ECoronavirus_Mutations_2024/refsel.acids refsel.acids
cp ~/DATA_D/Data_Pietschmann_229ECoronavirus_Mutations_2024/lastal.acids lastal.acids
cp ~/DATA_D/Data_Pietschmann_229ECoronavirus_Mutations_2024/config.yaml config.yaml
cp ~/DATA_D/Data_Pietschmann_229ECoronavirus_Mutations_2024/samples-runs.txt samples-runs.txt
cp ~/DATA_D/Data_Pietschmann_229ECoronavirus_Mutations_2024/samples-depletion.txt samples-depletion.txt
cp ~/DATA_D/Data_Pietschmann_229ECoronavirus_Mutations_2024/samples-metagenomics.txt samples-metagenomics.txt
cp ~/DATA_D/Data_Pietschmann_229ECoronavirus_Mutations_2024/samples-assembly.txt samples-assembly.txt
cp ~/DATA_D/Data_Pietschmann_229ECoronavirus_Mutations_2024/samples-assembly-failures.txt samples-assembly-failures.txt
# Adapt the sample-*.txt
mkdir viralngs/data
mkdir viralngs/data/00_raw
mkdir bams
ref_fa="PP810610.fasta";
#for sample in hCoV229E_Rluc p10_DMSO p10_K22; do
for sample in p10_K7523 p16_DMSO p16_K22 p16_X7523; do
bwa index ${ref_fa}; \
bwa mem -M -t 16 ${ref_fa} trimmed/${sample}_trimmed_P_1.fastq trimmed/${sample}_trimmed_P_2.fastq | samtools view -bS - > bams/${sample}_genome_alignment.bam; \
done
conda activate viral-ngs4
#for sample in hCoV229E_Rluc p10_DMSO p10_K22; do
#for sample in p10_K7523 p16_DMSO p16_K22 p16_X7523; do
for sample in p16_K22; do
picard AddOrReplaceReadGroups I=bams/${sample}_genome_alignment.bam O=~/DATA_D/Data_Pietschmann_229ECoronavirus_Mutations_2025/viralngs/data/00_raw/${sample}.bam SORT_ORDER=coordinate CREATE_INDEX=true RGPL=illumina RGID=$sample RGSM=$sample RGLB=standard RGPU=$sample VALIDATION_STRINGENCY=LENIENT; \
done
conda deactivate
# -- ! Firstly set the samples-assembly.txt empty, so that only focus on running depletion!
docker run -it -v /mnt/md1/DATA_D/Data_Pietschmann_229ECoronavirus_Mutations_2025/viralngs:/work -v /home/jhuang/Tools/viral-ngs_docker:/home/jhuang/Tools/viral-ngs_docker -v /home/jhuang/REFs:/home/jhuang/REFs -v /home/jhuang/Tools/GenomeAnalysisTK-3.6:/home/jhuang/Tools/GenomeAnalysisTK-3.6 -v /home/jhuang/Tools/novocraft_v3:/home/jhuang/Tools/novocraft_v3 -v /usr/local/bin/gatk:/usr/local/bin/gatk own_viral_ngs bash
cd /work
snakemake --directory /work --printshellcmds --cores 40
# -- ! Secondly manully run assembly steps
# --> By itereative add the unfinished assembly in the list, each time replace one, and run "snakemake --directory /work --printshellcmds --cores 40"
# # ---- NOTE that the following steps need rerun --> DOES NOT WORK, USE STRATEGY ABOVE ----
# #for sample in p10_K22 p10_K7523; do
# for sample in hCoV229E_Rluc p10_DMSO p10_K22 p10_K7523 p16_DMSO p16_K22 p16_X7523; do
# bin/read_utils.py merge_bams data/01_cleaned/${sample}.cleaned.bam tmp/01_cleaned/${sample}.cleaned.bam --picardOptions SORT_ORDER=queryname
# bin/read_utils.py rmdup_mvicuna_bam tmp/01_cleaned/${sample}.cleaned.bam data/01_per_sample/${sample}.cleaned.bam --JVMmemory 30g
# done
#
# #Note that the error generated by nextflow is from the step gapfill_gap2seq!
# for sample in hCoV229E_Rluc p10_DMSO p10_K22 p10_K7523 p16_DMSO p16_K22 p16_X7523; do
# bin/assembly.py assemble_spades data/01_per_sample/${sample}.taxfilt.bam /home/jhuang/REFs/viral_ngs_dbs/trim_clip/contaminants.fasta tmp/02_assembly/${sample}.assembly1-spades.fasta --nReads 10000000 --threads 15 --memLimitGb 12
# done
# for sample in hCoV229E_Rluc p10_DMSO p10_K22 p10_K7523 p16_DMSO p16_K22 p16_X7523; do
# for sample in p10_K22 p10_K7523; do
# bin/assembly.py order_and_orient tmp/02_assembly/${sample}.assembly1-spades.fasta refsel_db/refsel.fasta tmp/02_assembly/${sample}.assembly2-scaffolded.fasta --min_pct_contig_aligned 0.05 --outAlternateContigs tmp/02_assembly/${sample}.assembly2-alternate_sequences.fasta --nGenomeSegments 1 --outReference tmp/02_assembly/${sample}.assembly2-scaffold_ref.fasta --threads 15
# done
#
# for sample in hCoV229E_Rluc p10_DMSO p10_K22 p10_K7523 p16_DMSO p16_K22 p16_X7523; do
# bin/assembly.py gapfill_gap2seq tmp/02_assembly/${sample}.assembly2-scaffolded.fasta data/01_per_sample/${sample}.cleaned.bam tmp/02_assembly/${sample}.assembly2-gapfilled.fasta --memLimitGb 12 --maskErrors --randomSeed 0 --loglevel DEBUG
# done
#IMPORTANT: Reun the following commands!
for sample in hCoV229E_Rluc p10_DMSO p10_K22 p10_K7523 p16_DMSO p16_K22 p16_X7523; do
bin/assembly.py impute_from_reference tmp/02_assembly/${sample}.assembly2-gapfilled.fasta tmp/02_assembly/${sample}.assembly2-scaffold_ref.fasta tmp/02_assembly/${sample}.assembly3-modify.fasta --newName ${sample} --replaceLength 55 --minLengthFraction 0.05 --minUnambig 0.05 --index --loglevel DEBUG
done
# for sample in hCoV229E_Rluc p10_DMSO p10_K22 p10_K7523 p16_DMSO p16_K22 p16_X7523; do
# bin/assembly.py refine_assembly tmp/02_assembly/${sample}.assembly3-modify.fasta data/01_per_sample/${sample}.cleaned.bam tmp/02_assembly/${sample}.assembly4-refined.fasta --outVcf tmp/02_assembly/${sample}.assembly3.vcf.gz --min_coverage 2 --novo_params '-r Random -l 20 -g 40 -x 20 -t 502' --threads 15 --loglevel DEBUG
# bin/assembly.py refine_assembly tmp/02_assembly/${sample}.assembly4-refined.fasta data/01_per_sample/${sample}.cleaned.bam data/02_assembly/${sample}.fasta --outVcf tmp/02_assembly/${sample}.assembly4.vcf.gz --min_coverage 3 --novo_params '-r Random -l 20 -g 40 -x 20 -t 100' --threads 15 --loglevel DEBUG
# done
# -- ! Thirdly set the samples-assembly.txt completely and run "snakemake --directory /work --printshellcmds --cores 40"
Merge intra- and inter-host variants, comparing the variants to the alignments of the assemblies to confirm its correctness.
cat NC_001348.fasta viralngs/data/02_assembly/VZV_20S.fasta viralngs/data/02_assembly/VZV_60S.fasta > aligned_1.fasta
mafft --clustalout aligned_1.fasta > aligned_1.aln
#~/Scripts/convert_fasta_to_clustal.py aligned_1.fasta_orig aligned_1.aln
~/Scripts/convert_clustal_to_clustal.py aligned_1.aln aligned_1_.aln
#manully delete the postion with all or '-' in aligned_1_.aln
~/Scripts/check_sequence_differences.py aligned_1_.aln
~/Scripts/check_sequence_differences.py aligned_1_.aln > aligned_1.res
grep -v " = n" aligned_1.res > aligned_1_.res
cat NC_001348.fasta viralngs/tmp/02_assembly/VZV_20S.assembly4-refined.fasta viralngs/tmp/02_assembly/VZV_60S.assembly4-refined.fasta > aligned_1.fasta
mafft --clustalout aligned_1.fasta > aligned_1.aln
~/Scripts/convert_clustal_to_clustal.py aligned_1.aln aligned_1_.aln
~/Scripts/check_sequence_differences.py aligned_1_.aln > aligned_1.res
grep -v " = n" aligned_1.res > aligned_1_.res
#Differences found at the following positions (150):
Position 8956: OP297860.1 = A, HSV1_S1-1 = A, HSV-Klinik_S2-1 = G
Position 8991: OP297860.1 = A, HSV1_S1-1 = A, HSV-Klinik_S2-1 = C
Position 8992: OP297860.1 = T, HSV1_S1-1 = C, HSV-Klinik_S2-1 = C
Position 8995: OP297860.1 = T, HSV1_S1-1 = T, HSV-Klinik_S2-1 = C
Position 9190: OP297860.1 = T, HSV1_S1-1 = A, HSV-Klinik_S2-1 = T
* Position 13659: OP297860.1 = G, HSV1_S1-1 = T, HSV-Klinik_S2-1 = G
* Position 47969: OP297860.1 = C, HSV1_S1-1 = T, HSV-Klinik_S2-1 = C
* Position 53691: OP297860.1 = G, HSV1_S1-1 = T, HSV-Klinik_S2-1 = G
* Position 55501: OP297860.1 = T, HSV1_S1-1 = C, HSV-Klinik_S2-1 = C
* Position 63248: OP297860.1 = G, HSV1_S1-1 = T, HSV-Klinik_S2-1 = G
Position 63799: OP297860.1 = T, HSV1_S1-1 = C, HSV-Klinik_S2-1 = T
* Position 64328: OP297860.1 = C, HSV1_S1-1 = A, HSV-Klinik_S2-1 = C
Position 65179: OP297860.1 = T, HSV1_S1-1 = T, HSV-Klinik_S2-1 = C
* Position 65225: OP297860.1 = G, HSV1_S1-1 = G, HSV-Klinik_S2-1 = A
* Position 95302: OP297860.1 = C, HSV1_S1-1 = A, HSV-Klinik_S2-1 = C
gunzip isnvs.annot.txt.gz
~/Scripts/filter_isnv.py isnvs.annot.txt 0.05
cut -d$'\t' filtered_isnvs.annot.txt -f1-7
chr pos sample patient time alleles iSNV_freq
OP297860 13203 HSV1_S1 HSV1_S1 T,C,A 1.0
OP297860 13203 HSV-Klinik_S2 HSV-Klinik_S2 T,C,A 1.0
OP297860 13522 HSV1_S1 HSV1_S1 G,T 1.0
OP297860 13522 HSV-Klinik_S2 HSV-Klinik_S2 G,T 0.008905554253573941
OP297860 13659 HSV1_S1 HSV1_S1 G,T 1.0
OP297860 13659 HSV-Klinik_S2 HSV-Klinik_S2 G,T 0.008383233532934131
~/Scripts/convert_clustal_to_fasta.py aligned_1_.aln aligned_1.fasta
samtools faidx aligned_1.fasta
samtools faidx aligned_1.fasta OP297860.1 > OP297860.1.fasta
samtools faidx aligned_1.fasta HSV1_S1-1 > HSV1_S1-1.fasta
samtools faidx aligned_1.fasta HSV-Klinik_S2-1 > HSV-Klinik_S2-1.fasta
seqkit seq OP297860.1.fasta -w 70 > OP297860.1_w70.fasta
diff OP297860.1_w70.fasta ../../refsel_db/refsel.fasta
Consensus sequences of each and of all isolates
cp data/02_assembly/*.fasta ./
for sample in 838_S1 840_S2 820_S3 828_S4 815_S5 834_S6 808_S7 811_S8 837_S9 768_S10 773_S11 767_S12 810_S13 814_S14 10121-16_S15 7510-15_S16 828-17_S17 8806-15_S18 9881-16_S19 8981-14_S20; do
for sample in p953-84660-tsek p938-16972-nra p942-88507-nra p943-98523-nra p944-103323-nra p947-105565-nra p948-112830-nra; do \
mv ${sample}.fasta ${sample}.fa
cat all.fa ${sample}.fa >> all.fa
done
cat RSV_dedup.fa all.fa > RSV_all.fa
mafft --adjustdirection RSV_all.fa > RSV_all.aln
snp-sites RSV_all.aln -o RSV_all_.aln
Download all Human alphaherpesvirus 3 (Varicella-zoster virus) genomes
Human alphaherpesvirus 3
acronym: HHV-3 VZV
equivalent: Human herpes virus 3
Human alphaherpesvirus 3 (Varicella-zoster virus)
* Human herpesvirus 3 strain Dumas
* Human herpesvirus 3 strain Oka vaccine
* Human herpesvirus 3 VZV-32
#Taxonomy ID: 10335
esearch -db nucleotide -query "txid10335[Organism:exp]" | efetch -format fasta -email j.huang@uke.de > genome_10335_ncbi.fasta
python ~/Scripts/filter_fasta.py genome_10335_ncbi.fasta complete_genome_10335_ncbi.fasta #2041-->165
# ---- Download related genomes from ENA ----
https://www.ebi.ac.uk/ena/browser/view/10335
#Click "Sequence" and download "Counts" (2003) and "Taxon descendants count" (2005) if there is enough time! Downloading time points is 11.03.2025.
python ~/Scripts/filter_fasta.py ena_10335_sequence.fasta complete_genome_10335_ena_taxon_descendants_count.fasta #2005-->153
#python ~/Scripts/filter_fasta.py ena_10335_sequence_Counts.fasta complete_genome_10335_ena_Counts.fasta #xxx, 5.8G
https://www.ebi.ac.uk/ena/browser/view/10239
https://www.ebi.ac.uk/ena/browser/view/2497569
https://www.ebi.ac.uk/ena/browser/view/Taxon:2497569
ena_10239_sequence.fasta
esearch -db nucleotide -query "txid10239[Organism:exp]" | efetch -format fasta -email j.huang@uke.de > genome_10239_ncbi.fasta
Using Multi-CAR for scaffolding the contigs (If not useful, choose another scaffolding tool, e.g. https://github.com/malonge/RagTag)
All contigs over 500 bp were successfully scaffolded to the graft genome using Multi-CAR (13), resulting in a chromosomal assembly of 4,506,689 bp.
https://genome.cs.nthu.edu.tw/Multi-CAR/
https://github.com/ablab-nthu/Multi-CSAR
Using the bowtie of vrap to map the reads on ref_genome/reference.fasta (The reference refers to the closest related genome found from the list generated by vrap)
(vrap) vrap/vrap.py -1 trimmed/VZV_20S_trimmed_P_1.fastq -2 trimmed/VZV_20S_trimmed_P_2.fastq -o VZV_20S_on_X04370 --host /home/jhuang/DATA/Data_Huang_Human_herpesvirus_3/X04370.fasta -t 100 -l 200 -g
cd bowtie
mv mapped mapped.sam
samtools view -S -b mapped.sam > mapped.bam
samtools sort mapped.bam -o mapped_sorted.bam
samtools index mapped_sorted.bam
samtools view -H mapped_sorted.bam
samtools flagstat mapped_sorted.bam
Show the bw on IGV
Reports
diff data/02_assembly/2040_04.fasta tmp/02_assembly/2040_04.assembly4-refined.fasta
diff data/02_assembly/2040_04.fasta tmp/02_assembly/2040_04.assembly1-spades.fasta
diff data/02_assembly/2040_04.fasta tmp/02_assembly/2040_04.assembly2-scaffolded.fasta
diff data/02_assembly/2040_04.fasta tmp/02_assembly/2040_04.assembly2-gapfilled.fasta
diff data/02_assembly/2040_04.fasta tmp/02_assembly/2040_04.assembly3-modify.fasta
diff data/02_assembly/2040_04.fasta tmp/02_assembly/2040_04.assembly4-refined.fasta
./2040_04.assembly2-alternate_sequences.fasta
./2040_04.assembly2-scaffold_ref.fasta
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