khmer
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3.0.0a1 normalize by median
Normalize fasta or fastq reads. Eliminate reads with median k-mer abundance higher than
DESIRED_COVERAGE.
Quick Start
- To use khmer 3.0.0a1 normalize by median, import your data in fastq format. Paired end data must be interleaved and reads named with /1 and /2.
- Resources: https://khmer.readthedocs.org/en/latest/guide.html
Test Data
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Test data for this app appears directly in the Discovery Environment in the Data window under Community Data -> iplantcollaborative -> example_data -> directory. khmer |
Input File(s)
fastq files (interleaved for paired end reads).Use these files as test input:
e_coli_1000_1.fq
e_coli_1000_2.fq
Parameters Used in App
When the app is run in the Discovery Environment, use the following parameters.
- Use these parameters within the DE app interface:
- --ksize (kmer size, default 20. use 20 for digital normalization and 32 for partitioning)
- --n_hashes (default 4)
- --hashsize (default 4e9)
- --cutoff (coverage cutoff, default 20)--savehash (savehash.kh file which can be used with subsequent khmer tool runs)
- --report-to-file (report file)
Output File(s)
Expect fastq files named with extension .keep after the input files as output. For the test case, the output file you will find in the example_data directory is named <none at this time> norm-by-median_output.