Note: All of the work I do is proprietary, and so, I cannot share any of it publicly. This repo is really only meant to show that I know how to code in Python, create packages (with entry points that function as stand alone programs), and do "pythonic things" like list/dictionary comprehension, use loggers, create and use classes and functions, parse arguments to scripts, perform I/O efficiently, etc... This repo is really just an example of my coding skills. It is not meant to be an exhaustive accounting of everything I can do.
I am skilled in bash scripting, WDL, and common high-throughput sequencing tools such as GATK, Picard, VCF/BCF/Sam/Bedtools, bcl2fastq2, etc... I often use pandas and multiprocessing in Python and a long list of other packages in the standard library or available through pip. I've used Sun Grid Engine for distributed computing. I've used Docker for containerization and conda for isolated environments.
Most of my work has involved creating and validating new pipelines using OTS and custom tools for analysis and reporting, as well as, performing analysis of new assay validation data, including assessing accuracy and precision.
For more information on my other skills, see my resume, email me ([email protected]), or message me on my LinkedIn.
by M. R. Snyder 2022
Written for Python 3.6 or later
metatrim trims paired end metabarcoding reads in gzipped FASTQ files (*.fastq.gz) for subsequent merging in other programs such as Dada2, Unoise, or OBITools. metatrim trims primers from reads allowing for user specified degeneracy (sequencing error in the primer region). metatrim will create trimmed FASTQ files with the same tree structure as the input files in a user specified output directory, which will be created if it does not exist, but the program will abort if this directory is not empty. Output files will end in "metatrimmed.fastq.gz". A log and summary file will be created in the top level of this output directory as well.
First stage PCR indices may be used in metabarcoding experiments to detect index hops and/or cross contamination. A list of one or more of these indices used on the run (or for the sample) may be supplied, allowing metatrim to naively determine the appropriate index for a sample based on the most common present in the reads. Reads that do not possess this index will be removed from the results. Information about the number of reads with the index will be included in the summary file.
A target length can be specified. If so, reads will be trimmed this number of bases from the end of each primer. Alternatively, omit this argument and metatrim will search for both primers in R1 and R2 reads and trim the intervening region. If the 3' primer in the read is not found the read will be trimmed from the end of the 5' primer to the end of the sequence. Information about the number of trimmed reads and those with the 5' (and 3') will be included in the summary file.
A minimum length may also be supplied. If so, reads less than this length after trimming will be considered "primer dimers" and discarded. Information about the number of reads less than the minimum length will be included in the summary file.
Note: metatrim assumes your FASTQ files have uppercase sequences. Primer and index sequence inputs are case insensitive!
To install metatrim in your path:
pip3 install metatrim
metatrim will be available as a standalone executable in your path.
metatrim is a simple program to use. Issue metatrim -h to see the help menu.
Trim 5' primers to target length from reads with no first stage indices:
metatrim -I "</quoted/input/fastq.gz/glob>" -O </output/dir> \
-FP <forward_primer_sequence> -RP <reverse_primer_sequence> \
-FD <forward_primer_error> -RD <reverse_primer_error> \
-TL <target_length>
Trim 5' and 3' primers from reads with no first stage indices. Keep reads >= 50 bp:
metatrim -I "</quoted/input/fastq.gz/glob>" -O </output/dir> \
-FP <forward_primer_sequence> -RP <reverse_primer_sequence> \
-FD <forward_primer_error> -RD <reverse_primer_error> \
-ML 50
Trim 5' primers to target length from reads with first stage indices. Keep reads >= 50 bp:
metatrim -I "</quoted/input/fastq.gz/glob>" -O </output/dir> \
-FP <forward_primer_sequence> -RP <reverse_primer_sequence> \
-FD <forward_primer_error> -RD <reverse_primer_error> \
-R1I <R1_index1> <R1_index2> ... <R1_indexN> \
-R2I <R2_index2> <R2_index2> ... <R2_indexN> \
-TL <target_length> \
-ML 50
Trim 5' and 3' primers from reads with first stage indices. Keep reads >= 50 bp:
metatrim -I "</quoted/input/fastq.gz/glob>" -O </output/dir> \
-FP <forward_primer_sequence> -RP <reverse_primer_sequence> \
-FD <forward_primer_error> -RD <reverse_primer_error> \
-R1I <R1_index1> <R1_index2> ... <R1_indexN> \
-R2I <R2_index2> <R2_index2> ... <R2_indexN> \
-ML 50