File description:

• kallisto_pipeline.nf - the main quantification pipeline
• kallisto_pipeline_SRR.nf - quantification pipeline for files downloaded from SRA
• kallisto_velocity_pipeline.nf - the quantification pipeline for RNA velocity

Notes on pipeline:

• while kallisto_pipeline.nf detects read1 and read2 as all files in a folder that have "R1."/"R2.", kallisto_pipeline_SRR.nf detects the same reads as files with "_2."/"_3.". This is the only different between these pipelines
• reads are passed as a list of all fastq files in a directory (e.g. "*.fastq.gz"), so ideally all reads to be used in the quantification of a given sample should be in the same directory
• currently, the %MT detection assumes a gene format like "geneID-genename", and tries to detect MT genes based on predefined gene names
• the transcriptome index is created in the same folder where the fasta file is located. if it has been created in advance, you still need to pass a fasta file path, as well as the index file name
• running the pipeline for Visium data also requires installing spaceranger. this is necessary to do a mock run, where the image outputs are retrieved from
• at the moment, the mock spaceranger run relies on a quantification against a human transcriptome index THAT IS HARDCODED IN THE CODE AND NEEDS TO BE ADAPTED

Example commands:

• 10xv3:

nextflow run kallisto_pipeline.nf --transcriptome /links/groups/treutlein/USERS/tomasgomes/gene_refs/axolotl/Amex_T_v47/full_transcript/Amex_Tv47_Gv6.full_transcript_artificial.fa --transindex Amex_Tv47_Gv6.full_transcript_artificial.kalid --t2g /links/groups/treutlein/USERS/tomasgomes/gene_refs/axolotl/Amex_T_v47/full_transcript/AmexT_v47_artificial_genenames_t2g.txt --white /links/groups/treutlein/USERS/tomasgomes/gene_refs/other/737K-arc-v1.txt --samplename "a1_1_GEX" --outdir /links/groups/treutlein/USERS/tomasgomes/data/axolotl/ --protocol 10xv3 --reads "/local1/DATA/sequencing/20210518_P1567_ASHLEY_10X_axolotl_whole_pallium_multiome/raw/a1_1_GEX/*.fastq.gz"

• Smart-seq2 data (requires preparing data table):

nextflow run kallisto_pipeline.nf --transcriptome /links/groups/treutlein/USERS/tomasgomes/gene_refs/axolotl/Amex_T_v47/cDNA_transcripts/AmexT_v47_artificial.fa --transindex AmexT_v47_artificial.kalid --t2g /links/groups/treutlein/USERS/tomasgomes/gene_refs/axolotl/Amex_T_v47/cDNA_transcripts/AmexT_v47_artificial_genenames_t2g.txt --samplename "Gerber_plate" --outdir /links/groups/treutlein/USERS/tomasgomes/data/axolotl/ --protocol plate --reads /links/groups/treutlein/USERS/tomasgomes/projects/axolotl/data/raw/Gerber_allcells/kallisto_batch.txt

• Visium:

nextflow run kallisto_pipeline.nf --transcriptome /links/groups/treutlein/USERS/tomasgomes/gene_refs/axolotl/Amex_T_v47/cDNA_transcripts/AmexT_v47_artificial.fa --transindex AmexT_v47_artificial.kalid --t2g /links/groups/treutlein/USERS/tomasgomes/gene_refs/axolotl/Amex_T_v47/cDNA_transcripts/AmexT_v47_artificial_genenames_t2g.txt --white /links/groups/treutlein/USERS/tomasgomes/gene_refs/other/visium-v1_whitelist_kallisto.txt --samplename "A1_limb" --outdir /links/groups/treutlein/USERS/tomasgomes/data/axolotl/ --protocol visiumv1 --reads "/links/groups/treutlein/DATA/sequencing/20200821_P1288_ASHLEY_VISIUM_axolotl_visium_control_11dpa/raw/A1_Animal1_Control/*.fastq.gz" --images "V19S23-109" --imagear "A1" --imagef "/links/groups/treutlein/DATA/sequencing/20200821_P1288_ASHLEY_VISIUM_axolotl_visium_control_11dpa/image/A1_large_image1.jpg" --imageal "/links/groups/treutlein/DATA/sequencing/20200821_P1288_ASHLEY_VISIUM_axolotl_visium_control_11dpa/alignment_files/V19S23-109-A1.json"

• RNA velocity:

nextflow run kallisto_velocity_pipeline.nf --transcriptome /links/groups/treutlein/USERS/tomasgomes/gene_refs/axolotl/Amex_T_v47/introns/AmexT_v47_artificial_introns.fa --transindex AmexT_v47_artificial_introns.kalid --t2g /links/groups/treutlein/USERS/tomasgomes/gene_refs/axolotl/Amex_T_v47/introns/AmexT_v47_artificial_introns_genenames_t2g.txt --white /links/groups/treutlein/USERS/tomasgomes/gene_refs/other/10xv3_whitelist.txt --samplename "a1_2_GEX" --outdir /local1/USERS/tomasgomes/kallisto_velocity/ --protocol 10xv3 --reads "/links/groups/treutlein/DATA/sequencing/20210518_P1567_ASHLEY_10X_axolotl_whole_pallium_multiome/raw/a1_2_GEX/*.fastq.gz"

Files in other_files/:

• instructions_Amex_transcriptome.txt - (older) instructions on how to format the axolotl transcriptome to fit with kallisto, as well as overall use of the pipeline
• nextflowenv.yaml - conda environment used to run the pipeline
• kallisto_batch.txt - example batch file for Smart-seq2
• barcode_whitelists/ - several files with barcode whitelists vor various 10x protocols (compressed)
• axolotl_genome_cut.config - an example config file to index the axolotl (cut) genome for cellranger-ARC
• chrNameLength.txt - example file with chromosome name and length (a STAR indexing output)

Files in other_scripts/:

• convertCoords.py - convert chromosome coordinates in a BED file from a chopped down genome back into the original
• example: python3 convertCoords.py chrNameLength.txt input.bed output.bed
• convertCoords_indiv.py - convert specific chromosome coordinates from a chopped down genome back into the original
• example: python3 convertCoords_indiv.py chrNameLength.txt chr1ps3:213318726-213320220
• cutChroms.py - script to cut chromosomes into a specific maximum length. also prevents cutting in the middle of genes, including giving additional space around its ends
• requires preparation:

# split genome into individual chromosomes
faidx --split-files ../AmexG_v6.DD.corrected.round2.chr.fa
# return chromosome sizes
faidx ../AmexG_v6.DD.corrected.round2.chr.fa -i chromsizes > AmexG_v6.DD.corrected.round2.chr.sizes

• example: python cutChroms.py AmexG_v6_chr/AmexG_v6.DD.corrected.round2.chr.sizes ../AmexT_v47.FULL_corr_chr.gtf AmexG_v6_chr/AmexT_v47.FULL_corr_chr_cut.gtf AmexG_v6_chr/cutcoord.txt AmexG_v6_chr 500000000 2000
• get_t2g_gtf.py - script to extract gene ID and gene names from gtf file, and compile a t2g.txt file for kallisto. Returns gene ID and gene name versions, as well as a full annotation version.
• this is taylored to the axolotl GTF file
• example: python get_t2g_gtf.py AmexT_v47.FULL_corr_chr.gtf t2g.txt t2g_genenames.txt t2g_note.txt
• get_t2g_gtf_introns.py - script to extract gene ID and gene names from gtf file, for use in a gtf file with introns (for kallisto RNA velocity)
• example: python get_t2g_gtf.py AmexT_v47.FULL_corr_chr.gtf AmexT_v47.introns_t2g.txt AmexT_v47.introns_genenames_t2g.txt AmexT_v47.introns_t2g_note.txt AmexT_v47.introns_list.txt
• getTranscriptFastaHead.py - simplifies fasta header to only have gene ID
• example: python getTranscriptFastaHead.py AmexT_v47_CDS_reformatted.fa AmexT_v47.FULL.fa
• getExonFastaHead.py - simplifies fasta header to only have gene ID, for a fasta with exon sequences. each gene name will get an added number (.1, .2, ...) depending on the exon number
• I couldn't find the original use case for this...
• example: python getExonFastaHead.py AmexT_v47_CDS_reformatted.fa AmexT_v47.FULL.fa exon_list.txt
• getExont2g.py - make a t2g.txt file from a GTF, for exons
• example: python getExont2g.py AmexT_v47.FULL_corr_chr.gtf exons_t2g.txt
• list_annotations.py - create a new file with gene annotations
• I couldn't find the original use case for this, and not entirely sure what the input and output is...
• simplify_gtf_ids.py - simplify the gene annotations in a gtf file
• I couldn't find the original use case for this
• simplifyExonsDesc.py - simplify exon description
• I couldn't find the original use case for this, and not entirely sure what the input and output is...