These scripts are for identifying potential full-length (FL) subreads or CCS reads using the 5' and 3' primer ligated to the transcripts during the cDNA library preparation step.

IMPORTANT: usage of the scripts is detailed in the wiki section. Please read it!!

Identifying full-length subreads/CCS reads using cDNA kit primers

See this page on how to use the full-length identification scripts.

usage: hmmer_wrapper.py

[-h] [-p PRIMER_FILENAME] [-i INPUT_FILENAME] [-d DIRECTORY] [-k PRIMER_SEARCH_WINDOW] [--cpus CPUS] [--left-nosee-ok] [--right-nosee-ok] [--output-anyway] [--change-seqid] [--min-seqlen MIN_SEQLEN] [--min-score MIN_SCORE] -o OUTPUT_FILENAME

This script requires phmmer from HMMER 3.0. If the output directory already exists, will skip running phmmer and directory go to primer trimming. If you want to re-run HMMER you must first delete the output directory manually. Refer to wiki: https://github.com/PacificBiosciences/cDNA_primer/wiki for more details.

optional arguments:

-h, --help

show this help message and exit

HMMER options:

-p PRIMER_FILENAME, --primer_filename PRIMER_FILENAME
	Primer fasta file
-i INPUT_FILENAME, --input_filename INPUT_FILENAME
	Input fasta file (usually filtered_subreads.fasta or filtered_CCS_subreads.fasta)
-d DIRECTORY, --directory DIRECTORY
	Directory to store HMMER output (default: output/)
-k PRIMER_SEARCH_WINDOW, --primer_search_window PRIMER_SEARCH_WINDOW
	Search in the first/last k-bp for primers. Must be longer than the longest primer. (default: 100)
--cpus CPUS	Number of CPUs to run HMMER (default: 8)

Primer trimming options:

--left-nosee-ok
	OK if 5' end not detected (default: off)
--right-nosee-ok
	OK if 3' end not detected (default: off)
--output-anyway
	Still output seqs w/ no primer (default: off)
--change-seqid	Change seq id to reflect trimming (default: off)
--min-seqlen MIN_SEQLEN
	Minimum seqlength to output (default: 50)
--min-score MIN_SCORE
	Minimum bit score for primer hit (default: 10)
-o OUTPUT_FILENAME, --output_filename OUTPUT_FILENAME
	Output fasta filename

Extra filtering to eliminate subreads with missed adapters

If SMRTbell adapters are missed, sometimes it'll still be considered full-length by barcode_trimmer.py (especially when the 5' and 3' primers are identical or highly similar). To further eliminate these subreads, after running barcode_trimmer.py, you can run this extra script:

usage: filter_53seen.py TRIMMED_FASTA PRIMER_INFO OUTPUT_FILENAME

You should use the output fasta and .primer_info.txt from barcode_trimmer.py.

Currently, this filtering is done by simply looking at the FL subread length distributions in the same ZMW and eliminate those that have too short or too long subread length (despite seeing both 5' and 3').

The output from this script are all subreads that: (1) have 5' and 3' seen and (2) are likely not to contain a missing adapter.

Aligning subreads to known transcripts and plotting results

The alignQC.py is a lot more demanding on prerequisites. Read here for a detailed tutorial.

usage: alignQC.py [-h] -d OUTPUT_DIRECTORY -m PRIMER_MATCH_FILE -p OUTPUT_PREFIX [--read_pickle READ_PICKLE] [--ref_size REF_SIZE] [--refStrandPickle REFSTRANDPICKLE] [--restrictByPM] job_directory

Create some plots for transcript analyses.

positional arguments:

job_directory

optional arguments:

-h, --help	show this help message and exit
-d OUTPUT_DIRECTORY
	OUTPUT_DIRECTORY
-m PRIMER_MATCH_FILE
	PRIMER_MATCH_FILE
-p OUTPUT_PREFIX
	OUTPUT_PREFIX
--read_pickle	READ_PICKLE
--ref_size	REF_SIZE
--refStrandPickle
	REFSTRANDPICKLE
--restrictByPM	Using .primer_info.txt to restrict what subreads to look at