peresay/selectset repository overview

⁠selectSet

Creates a select set of novel allele sequences from 'raw data' for submission

⁠Input and output for SelectSet:

⁠Input arguments:

-f forward (R1) fastq sequence file. Example P1_I1_S1_R1.fastq -r reverse (R2) fastq sequence file. Example P1_I1_S1_R2.fastq -a Novel allele reference fasta file. An example of such a file is in the bitbucket repository (https://bitbucket.org/yaarilab/selectset/src/master/novel_alleles.fasta⁠) -m fastq merger. 1 - for PANDASEQ, 2 - for ASSEMBLEPAIRS. Default is using pandaseq.

The output is a folder name submission_set, containing the forward and reverse raw fastq files with the md5sum of each file, for each novel allele with the selected sequences.

⁠Example command:

docker run -it -v "$HOME/projects:/data:z" peresay/selectset:v1 SelectSet -f /data/P4_I7_S1_R1.fastq -r /data/P4_I7_S1_R2.fastq -a /data/P4_I7_S1.fasta -m 1

⁠Example output files in the submission_set folder:

• P4_I7_S1_R1_IGHV5-51_01_C45G.fastq.gz
• P4_I7_S1_R2_IGHV5-51_01_C45G.fastq.gz
• P4_I7_S1_R1_IGHV5-51_01_C45G_md5sum.txt
• P4_I7_S1_R2_IGHV5-51_01_C45G_md5sum.txt

⁠Working pipeline:

• Merging reads using one of the methods
• Aligning merged reads to the novel allele reference using balst
• Filtering blast output to an identity of at least 96%
• Filtering reads to match novel alleles SNPs

⁠More information can be found in the bitbucket repository: yaarilab/selectset