Mercurial > repos > iuc > concoct
changeset 0:bf23c688912a draft
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/concoct commit 49b42f61ff37c3c33dd15c195e5705e1db066c37"
| author | iuc |
|---|---|
| date | Fri, 18 Feb 2022 14:16:53 +0000 |
| parents | |
| children | 1f4286d836a3 |
| files | concoct.xml extract_fasta_bins.py macros.xml test-data/input1.fa.gz test-data/input1.tabular test-data/inputcluster1.tabular test-data/process_log.txt |
| diffstat | 7 files changed, 612 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/concoct.xml Fri Feb 18 14:16:53 2022 +0000 @@ -0,0 +1,116 @@ +<tool id="concoct" name="CONCOCT" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@"> + <description>metagenome binning</description> + <macros> + <import>macros.xml</import> + </macros> + <expand macro="requirements"/> + <command detect_errors="exit_code"><![CDATA[ +#set pca_components_file_name = 'PCA_components_data_gt' + str($advanced.length_threshold) + '.csv' +#set pca_transformed_file_name = 'PCA_transformed_data_gt' + str($advanced.length_threshold) + '.csv' +#set clustering_file_name = 'clustering_gt' + str($advanced.length_threshold) + '.csv' + +## CONCOCT doesn't handle gzipped files. +#if $composition_file.ext.endswith(".gz") + gunzip -c '$composition_file' > composition_file.fa && +#else: + ln -s '$composition_file' composition_file.fa && +#end if + +mkdir outdir && +concoct +--coverage_file '$coverage_file' +--composition_file composition_file.fa +--clusters $advanced.clusters +--kmer_length $advanced.kmer_length +--threads \${GALAXY_SLOTS:-4} +--length_threshold $advanced.length_threshold +--read_length $advanced.read_length +--total_percentage_pca $advanced.total_percentage_pca +--basename 'outdir/' +--seed $advanced.seed +--iterations $advanced.iterations +--epsilon $advanced.epsilon +$advanced.no_cov_normalization +$advanced.no_total_coverage +--no_original_data +$advanced.converge_out + +## Convert all CONCOCT .csv outputs to tabular. +&& sed 's/\("\([^"]*\)"\)\?,/\2\t/g' outdir/$pca_components_file_name > '$output_pca_components' +&& sed 's/\("\([^"]*\)"\)\?,/\2\t/g' outdir/$pca_transformed_file_name > '$output_pca_transformed' +&& sed 's/\("\([^"]*\)"\)\?,/\2\t/g' outdir/$clustering_file_name > '$output_clustering' +#if str($advanced.output_process_log) == 'yes': + && mv outdir/log.txt '$process_log' +#end if + ]]></command> + <inputs> + <param argument="--coverage_file" type="data" format="tabular" label="Tabular coverage file" help="Columns correspond to samples and rows to contigs"/> + <param argument="--composition_file" type="data" format="fasta,fasta.gz" label="Fasta file" help="Used to calculate the kmer composition (the genomic signature) of each contig"/> + <section name="advanced" title="Advanced options"> + <param argument="--clusters" type="integer" value="400" label="Maximum number of clusters for the Variational Gaussian Mixture Model algorithm"/> + <param argument="--kmer_length" type="integer" value="4" label="Kmer length"/> + <param argument="--length_threshold" type="integer" value="1000" label="Sequence length threshold" help="Contigs shorter than this value will not be included"/> + <param argument="--read_length" type="integer" value="100" label="Read length for coverage"/> + <param argument="--total_percentage_pca" type="integer" value="100" label="Percentage of variance explained by the principal components for the combined data"/> + <param argument="--seed" type="integer" min="0" value="1" label="Integer to use as seed for clustering" help="Zero value will use random seed"/> + <param argument="--iterations" type="integer" value="500" label="Maximum number of iterations for the Variational Bayes Gaussian Mixture Models"/> + <param argument="--epsilon" type="float" value="0.000001" label="Epsilon for the Variational Gaussian Mixture Model algorithm"/> + <param argument="--no_cov_normalization" type="boolean" truevalue="--no_cov_normalization" falsevalue="" checked="false" label="Skip normalization and only do log transorm of the coverage?" help="By default, the coverage is normalized for samples, then normalized for contigs and finally log transformed"/> + <param argument="--no_total_coverage" type="boolean" truevalue="--no_total_coverage" falsevalue="" checked="false" label="Eliminate the total coverage column from the coverage data matrix?" help="By default, total coverage is included, independently of coverage normalization but previous to log transformation"/> + <param argument="--converge_out" type="boolean" truevalue="--converge_out" falsevalue="" checked="false" label="Output convergence information?"/> + <param name="output_process_log" type="select" label="Output process log file?"> + <option value="no" selected="true">No</option> + <option value="yes">Yes</option> + </param> + </section> + </inputs> + <outputs> + <data name="process_log" format="txt" label="${tool.name} on ${on_string} (process log)"> + <filter>advanced['output_process_log'] == 'yes'</filter> + </data> + <data name="output_pca_components" format="tabular" label="${tool.name} on ${on_string} (PCA components)"/> + <data name="output_pca_transformed" format="tabular" label="${tool.name} on ${on_string} (PCA transformed)"/> + <data name="output_clustering" format="tabular" label="${tool.name} on ${on_string} (Clusters)"/> + </outputs> + <tests> + <test expect_num_outputs="4"> + <param name="coverage_file" value="input1.tabular" ftype="tabular"/> + <param name="composition_file" value="input1.fa.gz" ftype="fasta.gz"/> + <param name="output_process_log" value="yes"/> + <output name="process_log" file="process_log.txt" ftype="txt" compare="contains"/> + <output name="output_pca_components" ftype="tabular"> + <assert_contents> + <has_size value="367636"/> + <has_text text="7377051e-02"/> + </assert_contents> + </output> + <output name="output_pca_transformed" ftype="tabular"> + <assert_contents> + <has_size value="737926"/> + <has_text text="NODE_103_length_20202_cov_8.395357.0"/> + </assert_contents> + </output> + <output name="output_clustering" ftype="tabular"> + <assert_contents> + <has_size value="12167"/> + <has_text text="NODE_103_length_20202_cov_8.395357"/> + </assert_contents> + </output> + </test> + </tests> + <help><![CDATA[ +**What it does** + +CONCOCT (Clustering cONtigs with COverage and ComposiTion) performs unsupervised binning of metagenomic contigs by +using nucleotide composition - kmer frequencies - and coverage data for multiple samples. CONCOCT can accurately +(up to species level) bin metagenomic contigs. + +The tool accepts 2 inputs; a tabular file where each row corresponds to a contig and each column corresponds to a +sample (the values are the average coverage for this contig in that sample) and a file containing sequences in +fasta format. + +Three are produced; clustering of the > 1000 kmer count, the PCA transformed matrix and the PCA components. + + ]]></help> + <expand macro="citations"/> +</tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/extract_fasta_bins.py Fri Feb 18 14:16:53 2022 +0000 @@ -0,0 +1,49 @@ +#!/usr/bin/env python + +import argparse +import gzip +import os +import sys +from collections import defaultdict +from functools import partial + +import pandas as pd +from Bio import SeqIO + +parser = argparse.ArgumentParser(description=__doc__) + +parser.add_argument('--gzipped', action='store_true', dest='gzipped', help='Input files are gzipped') +parser.add_argument("--input_fasta", action="store", dest="input_fasta", help="Input Fasta file") +parser.add_argument("--input_cluster", action="store", dest="input_cluster", help="Concoct output cluster file") +parser.add_argument("--output_path", help="Output directory") + +args = parser.parse_args() + +all_seqs = {} +if args.gzipped: + _open = partial(gzip.open, mode='rt') +else: + _open = open + +with _open(args.input_fasta) as fh: + for seq in SeqIO.parse(fh, "fasta"): + all_seqs[seq.id] = seq + +# Make sure we're reading the file as tabular! +df = pd.read_csv(args.input_cluster, sep='\t') +try: + assert df.columns[0] == 'contig_id' + assert df.columns[1] == 'cluster_id' +except AssertionError: + sys.stderr.write("ERROR! Header line was not 'contig_id, cluster_id', please adjust your input file. Exiting!\n") + sys.exit(-1) + +cluster_to_contigs = defaultdict(list) +for i, row in df.iterrows(): + cluster_to_contigs[row['cluster_id']].append(row['contig_id']) + +for cluster_id, contig_ids in cluster_to_contigs.items(): + output_file = os.path.join(args.output_path, "{0}.fa".format(cluster_id)) + seqs = [all_seqs[contig_id] for contig_id in contig_ids] + with open(output_file, 'w') as ofh: + SeqIO.write(seqs, ofh, 'fasta')
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/macros.xml Fri Feb 18 14:16:53 2022 +0000 @@ -0,0 +1,17 @@ +<macros> + <token name="@TOOL_VERSION@">1.0.0</token> + <token name="@VERSION_SUFFIX@">0</token> + <token name="@PROFILE@">21.01</token> + <xml name="requirements"> + <requirements> + <requirement type="package" version="@TOOL_VERSION@">concoct</requirement> + <requirement type="package" version="0.19.2">pandas</requirement> + <requirement type="package" version="1.79">biopython</requirement> + </requirements> + </xml> + <xml name="citations"> + <citations> + <citation type="doi">10.1038/nmeth.3103</citation> + </citations> + </xml> +</macros>
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0.668300 0.060000 6.016100 4.997700 0.480000 2.290000 0 2.547800 4.837900 1.620000 0 0.310000 0.149100 0 +NODE_246_length_206288_cov_6.775057.16 10000 1.937400 0.050000 0.710000 0 5.833700 4.857500 0.240000 1.998900 0 2.627600 5.225200 1.320000 0 0.220000 0.180000 0 +NODE_246_length_206288_cov_6.775057.17 10000 1.458800 0.070000 0.758600 0.040000 5.416100 6.212700 0.360000 2.259200 0 2.927600 5.205300 1.610000 0 0.280000 0.180000 0 +NODE_246_length_206288_cov_6.775057.18 10000 1.617500 0.090000 0.980000 0.060000 6.303000 6.396800 0.398800 2.126900 0 2.628300 5.746800 1.528600 0 0.330000 0.309700 0 +NODE_246_length_206288_cov_6.775057.19 16358 1.795635 0.079472 0.788117 0.036679 5.620613 6.077637 0.396870 2.187616 0 2.510636 5.137795 1.606923 0 0.385133 0.140604 0 +NODE_246_length_206288_cov_6.775057.2 10000 1.739800 0.090000 0.779200 0.080000 6.272700 5.946100 0.300000 2.519200 0 2.898000 4.937800 1.648700 0 0.390000 0.189200 0 +NODE_246_length_206288_cov_6.775057.3 10000 1.797400 0.160000 0.569900 0.080000 6.195800 5.305100 0.378200 2.318000 0 2.485400 4.937600 1.559800 0 0.350000 0.049400 0 +NODE_246_length_206288_cov_6.775057.4 10000 1.537600 0.020000 0.508100 0 6.157100 6.135400 0.180000 2.427500 0 2.747500 4.943800 1.519000 0 0.280000 0.180000 0 +NODE_246_length_206288_cov_6.775057.5 10000 1.879300 0.040000 1.029500 0.280000 6.475200 6.084000 0.500000 3.205600 0.210000 2.799300 5.198200 2.445500 0 0.509700 0.849300 0.459900 +NODE_246_length_206288_cov_6.775057.6 10000 1.689300 0.060000 0.769000 0.020000 5.736400 6.167200 0.449000 2.058600 0 2.598700 5.423600 1.458300 0 0.380000 0.140000 0 +NODE_246_length_206288_cov_6.775057.7 10000 1.438200 0.100000 0.678700 0.040000 6.535800 5.674300 0.390000 2.375200 0 3.034700 5.145900 1.499400 0 0.468800 0.100000 0 +NODE_246_length_206288_cov_6.775057.8 10000 1.738100 0.019400 0.679800 0.060000 5.993100 5.795800 0.350000 2.029300 0 3.274900 5.829700 1.530000 0 0.408800 0.160000 0 +NODE_246_length_206288_cov_6.775057.9 10000 1.589800 0.120000 0.749000 0.100000 6.382400 5.938600 0.469400 2.298800 0 3.099600 5.901400 1.349000 0 0.390000 0.198700 0 +NODE_247_length_147_cov_4.074830 217 0.921659 0 0.460829 0 0 0 0.460829 0 0 0 0 0 0.460829 0 0.460829 1.843316 +NODE_248_length_650_cov_2.520000 720 0.694445 0.263889 1.250000 0 0 0 0.277778 0 0.277778 0.972223 0 0.555555 0.694444 0 0.138889 2.218057 +NODE_249_length_152_cov_4.210526 222 0.450450 1.351350 1.351353 0 0 0 0.450450 0 0 0.450450 0.900900 0.450450 0.450450 0 0.450450 3.567567 +NODE_24_length_115_cov_8.556521 185 1.081080 2.621622 3.632429 0 0 0 2.075676 0 4.772976 1.081081 0 2.605405 3.135135 3.102702 1.016215 1.621623 +NODE_250_length_251161_cov_8.263253.0 10000 2.300000 5.045200 4.533100 0 0 0 4.447400 0 4.544800 2.350000 0.980000 1.659700 4.807100 4.436100 3.209600 3.583800 +NODE_250_length_251161_cov_8.263253.1 10000 1.548600 4.458100 2.588600 0 0 0 3.748000 0 4.565000 0.889100 0.370000 1.098700 4.176600 5.054400 2.259100 1.449200 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4.158469 0 2.715847 0.502732 0.546448 1.568306 3.683064 2.601093 1.005465 0.546448 +NODE_254_length_191233_cov_8.270398.0 10000 1.438900 5.056200 3.207600 0 0 0 4.118500 0 4.606800 1.129500 0.250000 1.120000 4.013300 5.088500 2.866900 1.248500 +NODE_254_length_191233_cov_8.270398.1 10000 1.529300 4.077000 3.059100 0 0 0 4.108900 0 4.221300 1.009700 0.240000 1.129400 3.835100 4.448500 2.608800 1.830000 +NODE_254_length_191233_cov_8.270398.10 10000 2.049900 4.227300 2.988400 0 0 0 3.405900 0 4.016400 1.448100 0.569900 1.218600 4.097800 4.867900 2.976600 1.887100 +NODE_254_length_191233_cov_8.270398.11 10000 2.067900 4.644800 3.338500 0 0 0 4.284900 0 4.566100 1.246900 0.550000 1.348500 4.584300 4.404900 3.196700 2.427300 +NODE_254_length_191233_cov_8.270398.12 10000 1.489900 4.314200 3.087900 0 0 0 4.216400 0 4.036000 1.108800 0.340000 1.316100 4.037900 4.525200 2.834900 1.856800 +NODE_254_length_191233_cov_8.270398.13 10000 1.899300 4.357300 3.443800 0 0 0 3.847200 0 4.273400 1.249400 0.280000 1.160000 4.266600 4.796900 2.618300 1.939500 +NODE_254_length_191233_cov_8.270398.14 10000 2.637600 5.067000 3.467400 0 0 0 4.265800 0 4.416700 2.329400 0.420000 1.549000 4.795900 5.035400 2.715000 3.445500 +NODE_254_length_191233_cov_8.270398.15 10000 1.827000 4.536000 2.968300 0 0 0 3.587500 0 4.325600 1.307500 0.370000 1.218800 4.918000 5.306100 3.225200 2.049600 +NODE_254_length_191233_cov_8.270398.16 10000 1.939400 4.778600 2.776300 0 0 0 3.496800 0 4.277200 0.919700 0.200000 1.228800 3.864900 4.857800 2.808500 1.630000 +NODE_254_length_191233_cov_8.270398.17 10000 1.668700 4.275400 2.978100 0 0 0 4.047300 0 4.408700 0.968600 0.239700 0.949400 3.745200 4.714500 2.697000 1.507900 +NODE_254_length_191233_cov_8.270398.18 11303 1.882509 4.382906 3.174469 0 0 0 4.081393 0 4.119083 1.335573 0.353712 1.237460 4.322480 4.898871 2.704239 1.449438 +NODE_254_length_191233_cov_8.270398.2 10000 2.219900 4.766800 2.957200 0 0 0 4.237600 0 4.406700 1.379600 0.338600 1.180000 4.106100 4.938300 3.097300 1.569800 +NODE_254_length_191233_cov_8.270398.3 10000 1.997000 4.448200 2.728100 0 0 0 4.124900 0 4.576300 0.949700 0.480000 1.028700 4.744900 4.926300 2.487000 1.609700 +NODE_254_length_191233_cov_8.270398.4 10000 1.598600 4.305700 3.276600 0 0 0 4.377700 0 3.837800 0.899100 0.300000 1.058600 4.116900 4.785700 2.898200 1.508400 +NODE_254_length_191233_cov_8.270398.5 10000 1.799200 4.536300 3.108000 0 0 0 3.558300 0 4.385000 1.020000 0.350000 1.399000 4.178500 4.336100 2.857800 1.519100 +NODE_254_length_191233_cov_8.270398.6 10000 1.767700 4.935800 2.938900 0 0 0 4.194800 0 4.533100 0.949400 0.298900 1.250000 4.289100 4.097800 2.699700 1.380000 +NODE_254_length_191233_cov_8.270398.7 10000 1.969800 4.558000 3.164900 0 0 0 3.754700 0 4.387900 1.028500 0.460000 1.359500 4.426700 4.604500 2.697200 1.649300 +NODE_254_length_191233_cov_8.270398.8 10000 1.700000 3.986200 3.137500 0 0 0 3.698000 0 4.124100 0.979400 0.379900 1.178900 3.617500 4.915900 2.748100 1.210000 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4.736500 2.828200 0 0 0 3.627800 0 4.207900 0.849200 0.220000 1.039700 4.236500 4.327700 3.097700 1.579200 +NODE_260_length_165083_cov_8.801846.1 10000 1.800000 4.266200 3.248600 0 0 0 3.864600 0 4.884800 0.979300 0.340000 1.189700 4.128100 4.585000 2.508900 1.646900 +NODE_260_length_165083_cov_8.801846.10 10000 1.729300 4.398800 3.075000 0 0 0 4.029300 0 4.568900 1.049400 0.260000 1.490000 3.926800 4.886400 2.938900 1.598200 +NODE_260_length_165083_cov_8.801846.11 10000 1.809800 4.793100 2.867800 0 0 0 4.627900 0 4.114700 1.119100 0.329600 1.239400 4.354900 5.135200 3.236100 1.169700 +NODE_260_length_165083_cov_8.801846.12 10000 1.878600 4.047400 3.158700 0 0 0 3.577200 0 4.595500 0.998200 0.260000 1.509700 3.909100 4.506000 2.386200 1.557700 +NODE_260_length_165083_cov_8.801846.13 10000 1.989900 4.305000 3.365700 0 0 0 4.178100 0 4.444500 1.099300 0.459300 1.118700 4.229700 4.786800 3.176000 2.007600 +NODE_260_length_165083_cov_8.801846.14 10000 1.817100 4.684600 3.418600 0 0 0 4.145500 0 3.856000 1.040000 0.310000 1.438000 4.027700 4.721700 3.005400 1.729400 +NODE_260_length_165083_cov_8.801846.15 15153 1.845510 4.213490 2.995645 0 0 0 4.153892 0 4.604239 1.135089 0.303439 1.174554 4.173763 4.606741 2.764270 1.740845 +NODE_260_length_165083_cov_8.801846.2 10000 2.368500 4.128000 4.257100 0 0 0 4.338300 0 4.554200 2.566900 0.609400 1.539200 5.044900 4.844600 3.523800 3.646200 +NODE_260_length_165083_cov_8.801846.3 10000 2.647800 5.085700 3.876100 0 0 0 3.997800 0 5.074500 2.519700 0.560000 1.569300 4.833300 4.923500 3.528800 3.793000 +NODE_260_length_165083_cov_8.801846.4 10000 2.708100 4.908400 3.973800 0 0 0 4.525800 0 4.629300 2.827800 0.659400 1.458100 4.978300 4.476600 3.418900 3.988900 +NODE_260_length_165083_cov_8.801846.5 10000 2.008700 5.047700 3.518000 0 0 0 4.038500 0 4.767100 2.589200 0.629100 1.619200 5.103500 5.079200 2.808000 3.598200 +NODE_260_length_165083_cov_8.801846.6 10000 1.958200 5.246000 3.217200 0 0 0 3.955400 0 4.465100 1.748900 0.639100 1.476600 4.926500 4.874700 3.576300 3.098400 +NODE_260_length_165083_cov_8.801846.7 10000 1.608600 4.727600 3.016500 0 0 0 3.549400 0 4.024200 1.070000 0.290000 1.018000 4.088000 4.786800 3.029900 1.510000 +NODE_260_length_165083_cov_8.801846.8 10000 1.769300 4.343800 3.167800 0 0 0 3.985900 0 4.618500 1.009600 0.320000 1.040000 4.328800 4.863900 2.777800 1.639100 +NODE_260_length_165083_cov_8.801846.9 10000 2.089200 4.026000 3.399800 0 0 0 3.454900 0 4.154100 0.958500 0.329400 1.196200 3.426600 4.525200 2.899300 1.529500 +NODE_261_length_321461_cov_8.199894.0 10000 1.979100 4.825600 2.926100 0 0 0 3.968900 0 4.216300 1.178200 0.340000 1.148500 3.825600 4.675000 3.064900 1.398500 +NODE_261_length_321461_cov_8.199894.1 10000 1.618300 5.045100 3.257700 0 0 0 4.257700 0 3.848000 0.997600 0.210000 1.178800 3.738500 5.115300 2.736600 1.569200 +NODE_261_length_321461_cov_8.199894.10 10000 1.398400 4.062300 3.256500 0 0 0 4.106000 0 4.704800 1.048200 0.230000 1.248800 4.019200 5.045600 3.249700 1.440000 +NODE_261_length_321461_cov_8.199894.11 10000 1.919600 4.318100 3.083800 0 0 0 4.178900 0 5.137600 0.670000 0.260000 0.980000 4.576600 4.976200 2.998600 1.629700 +NODE_261_length_321461_cov_8.199894.12 10000 1.627000 4.104200 3.037200 0 0 0 3.927600 0 4.576600 1.069400 0.260000 1.188500 4.028400 4.632200 3.009100 1.427200 +NODE_261_length_321461_cov_8.199894.13 10000 1.698900 4.537200 3.057700 0 0 0 4.183300 0 4.527800 1.118600 0.400000 1.046300 3.859000 4.865300 3.266800 1.508500 +NODE_261_length_321461_cov_8.199894.14 10000 1.896800 4.205500 3.148900 0 0 0 3.587400 0 4.698200 0.998600 0.299500 0.968900 3.915200 4.946600 2.546500 1.679200 +NODE_261_length_321461_cov_8.199894.15 10000 1.848100 4.377100 2.958600 0 0 0 4.086000 0 4.282200 0.880000 0.388100 1.210000 4.723500 5.207000 2.787200 1.928400 +NODE_261_length_321461_cov_8.199894.16 10000 1.869700 4.804000 3.156900 0 0 0 3.605600 0 4.785000 1.019800 0.309900 1.129700 4.138100 4.036300 2.639600 1.649000 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+NODE_29_length_44540_cov_9.429951.1 10000 2.258300 4.988600 3.198400 0 0 0 3.565800 0 4.268500 2.740000 0.570000 1.366900 4.895400 4.835200 3.426900 4.108300 +NODE_29_length_44540_cov_9.429951.2 10000 2.716900 5.218600 3.607200 0 0 0 3.996700 0 4.797500 3.179400 0.770000 1.508700 4.924600 4.254900 3.564600 4.146500 +NODE_29_length_44540_cov_9.429951.3 14610 2.230117 5.066739 3.647501 0 0 0 4.351748 0 4.827725 1.531828 0.342231 1.298221 4.664888 5.032990 3.008352 2.216154 +NODE_2_length_16156_cov_8.219856 16226 1.545114 4.323432 2.912856 0 0 0 3.922715 0 4.290770 0.992173 0.388265 1.182792 4.050168 5.099648 2.813631 1.411069
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/inputcluster1.tabular Fri Feb 18 14:16:53 2022 +0000 @@ -0,0 +1,3 @@ +contig_id cluster_id +NODE_1_length_2054_cov_17.474684 77 +NODE_2_length_16156_cov_8.219856 93
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/process_log.txt Fri Feb 18 14:16:53 2022 +0000 @@ -0,0 +1,10 @@ +Results created at +Successfully loaded composition data. +Successfully loaded coverage data. +Performed PCA, resulted in 154 dimensions +Wrote PCA transformed file. +Wrote PCA components file. +PCA transformed data. +Will call vbgmm with parameters: outdir/, 400, 1000, 1 +Wrote assign file. +CONCOCT Finished