From 2cf225282048b4e2fd5dd8d896e2872bd057df06 Mon Sep 17 00:00:00 2001 From: Calvin Morrison Date: Tue, 11 Jun 2013 15:55:00 -0400 Subject: cli.markdown modifications - removed reference to a download page that doesn't exist - fixed typo --- doc/cli.markdown | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/doc/cli.markdown b/doc/cli.markdown index fcec55b..3d7a636 100644 --- a/doc/cli.markdown +++ b/doc/cli.markdown @@ -6,8 +6,7 @@ utilities are written in C and utilize OpenMP for multithreading. ## Quikr\_train ## The quikr\_train is a tool to train a database for use with the quikr tool. -Before running the quikr utility, you need to generate the sensing matqrix or -download a pretrained matrix from our database\_download.html. +Before running the quikr utility, you need to generate the sensing matrix. ### Usage ### quikr\_train returns a custom sensing matrix that can be used with the quikr -- cgit v1.2.3 From aeaccefd79d17b7742c5d7348ced3f8442eca9b5 Mon Sep 17 00:00:00 2001 From: Calvin Morrison Date: Tue, 11 Jun 2013 17:00:20 -0300 Subject: cli.markdown modifications for github formatting 4 spaces for function --help 4 spaces for QIIME procedure remove extra backslash --- doc/cli.markdown | 55 +++++++++++++++++++++++++++++-------------------------- 1 file changed, 29 insertions(+), 26 deletions(-) diff --git a/doc/cli.markdown b/doc/cli.markdown index 3d7a636..587d014 100644 --- a/doc/cli.markdown +++ b/doc/cli.markdown @@ -12,11 +12,11 @@ Before running the quikr utility, you need to generate the sensing matrix. quikr\_train returns a custom sensing matrix that can be used with the quikr function. -quikr\_train's arguments: - -i, --input, the database of sequences (fasta format) - -o, --output, the sensing matrix (text file) - -k, --kmer, specifiy wha size of kmer to use. (default value is 6) - -v, --verbose, verbose mode. + quikr_train's arguments: + -i, --input, the database of sequences (fasta format) + -o, --output, the sensing matrix (text file) + -k, --kmer, specifiy wha size of kmer to use. (default value is 6) + -v, --verbose, verbose mode. ### Example ### Here is an example on how to train a database. This uses the -z flag to compress @@ -34,13 +34,13 @@ input FASTA file. You need to train a matrix or download a new matrix ### Usage ### quikr returns the solution vector as a csv file. -quikr's arguments: - -f, --fasta, the sample's fasta file of NGS READS - -o, --output OTU\_FRACTION\_PRESENT, a vector representing the percentage of - database sequence's presence in sample (csv output) - -s, --sensing-matrix the sensing matrix. (generated by quikr\_train) - -l, --lambda, the lambda size. (the default lambda value is 10,000) - -k, --kmer, this specifies the size of the kmer to use (default is 6) + quikr's arguments: + -f, --fasta, the sample's fasta file of NGS READS + -o, --output OTU\_FRACTION\_PRESENT, a vector representing the percentage of + database sequence's presence in sample (csv output) + -s, --sensing-matrix the sensing matrix. (generated by quikr\_train) + -l, --lambda, the lambda size. (the default lambda value is 10,000) + -k, --kmer, this specifies the size of the kmer to use (default is 6) ## Multifasta\_to\_otu ## The Multifasta\_to\_otu tool is a handy wrapper for quikr which lets the user @@ -61,19 +61,20 @@ with aspecified number of jobs. Otherwise python with run one job per cpu core. .fa are valid while .fna is NOT) ### Usage ### -multifasta\_to\_otu's arguments: - -i, --input, the directory containing the samples' fasta files of - reads (note each fasta file should correspond to a separate sample) - -o, --otu-table, the OTU table, with OTU\_FRACTION\_PRESENT for each sample, - which is compatible with QIIME's convert\_biom.py (or sequence table if not - OTU's) - -s, --sensing-matrix, the sensing matrix - -f, --sensing-fasta, the fasta file database of sequences - -l, --lambda, specify what size of lambda to use (the default value is 10,000) - -k, --kmer, specify what size of kmer to use, (default value is 6) - -j, --jobs, specifies how many jobs to run at once, (default=number of CPUs) - -# Post-processing of Multifasta\_to\_otu # + + multifasta\_to\_otu's arguments: + -i, --input, the directory containing the samples' fasta files of + reads (note each fasta file should correspond to a separate sample) + -o, --otu-table, the OTU table, with OTU\_FRACTION\_PRESENT for each sample, + which is compatible with QIIME's convert\_biom.py (or sequence table if not + OTU's) + -s, --sensing-matrix, the sensing matrix + -f, --sensing-fasta, the fasta file database of sequences + -l, --lambda, specify what size of lambda to use (the default value is 10,000) + -k, --kmer, specify what size of kmer to use, (default value is 6) + -j, --jobs, specifies how many jobs to run at once, (default=number of CPUs) + +### Post-processing of Multifasta\_to\_otu ### * Note: When making your QIIME Metadata file, the sample id's must match the sample fasta file prefix names @@ -89,12 +90,14 @@ Pre-requisites: 3. your-defined The QIIME procedue: + convert_biom.py -i -o .biom --biom_table_type="otu table" beta_diversity.py -i .biom -m weighted_unifrac -o beta_div -t (example: rdp7_mafft.fasttree)> principal_coordinates.py -i beta_div/weighted_unifrac_.txt -o _weighted.txt make_3d_plots.py -i _weighted.txt -o <3d_pcoa_plotdirectory> -m -#### Broken Pipe Errors #### + +#### Broken Pipe Errors #### Make sure that you have the count-kmers and probablilties-by-read in your $PATH, and that they are executable. -- cgit v1.2.3