Mercurial > repos > onnodg > cdhit_analysis
annotate README.md @ 4:e64af72e1b8f draft default tip
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| author | onnodg |
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| date | Mon, 15 Dec 2025 16:44:40 +0000 |
| parents | 706b7acdb230 |
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| rev | line source |
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planemo upload for repository https://github.com/Onnodg/Naturalis_NLOOR/tree/main/NLOOR_scripts/process_clusters_tool commit 4017d38cf327c48a6252e488ba792527dae97a70-dirty
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1 # CDHIT Cluster Analysis Script |
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2 |
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3 This script processes a single **cluster file** together with an **excel file containing annotated reads**, generating multiple output files for downstream visualization and reporting. |
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4 |
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5 It is designed for clustering-based taxonomic pipelines and provides a detailed overview of cluster composition, similarity metrics, and taxonomic consistency within and between clusters. |
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6 |
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7 ## Usage |
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8 |
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9 The script performs the following main tasks: |
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10 |
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11 1. Parse command-line arguments. |
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12 2. Load the CD-HIT cluster results and annotated read information. |
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13 3. Group reads per cluster and compute similarity statistics (e.g., identity, alignment coverage). |
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14 4. Resolve taxonomic inconsistencies within clusters using uncertainty and minimum-count thresholds. |
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15 5. Generate visual and tabular summaries of cluster composition, similarity distribution, and annotation quality. |
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16 |
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17 ### Command Line Interface |
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18 The CD-HIT cluster analysis tool can be run as a Python script: |
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19 |
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20 ```bash |
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21 python cdhit_analysis.py [options] |
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22 ``` |
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23 |
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24 Below are detailed examples for a common use case. |
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25 |
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26 #### General use case |
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27 This example demonstrates the general usage of the tool for analyzing CD-HIT clustering results. |
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28 |
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29 **Requirements**: |
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30 |
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31 Requirements as listed in the cdhit_analysis.xml file: |
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32 |
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33 - Python version = 3.12.3 |
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34 - Matplotlib version = 3.12.3 |
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35 - Pandas version = 2.3.2 |
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36 - Openpyxl version = 3.1.5 |
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37 |
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38 **Input requirements** |
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39 |
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40 - CD-HIT cluster file (.clstr) containing sequence clusters with similarity information. |
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41 - Excel file containing annotated reads with corresponding taxonomic or metadata columns. |
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42 - The read identifiers in both files must match — the script merges cluster membership with read annotations using these IDs. |
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43 |
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44 **Example: Analyzing CD-HIT clusters with taxonomic annotations** |
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45 |
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46 ``` |
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47 process_clusters_tool/cdhit_analysis.sh' |
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48 --input_cluster 'clusters.txt' |
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49 --input_annotation 'annotations.xlsx' |
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50 --output_similarity_txt 'similarity_summary.txt' |
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51 --output_similarity_plot 'similairy_plot.png' |
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52 --output_evalue_txt 'evalue_summary.txt' |
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53 --output_evalue_plot 'evalue_plot.png' |
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54 --output_count 'cluster_count.txt' |
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55 --output_taxa_clusters 'taxa_clustered.xlsx' |
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56 --output_taxa_processed 'taxa_processed.xlsx.' |
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57 --simi_plot_y_min '95' |
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58 --simi_plot_y_max '100' |
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59 --uncertain_taxa_use_ratio '0.5' |
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60 --min_to_split '0.45' |
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61 --min_count_to_split '10' |
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62 --show_unannotated_clusters |
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63 --make_taxa_in_cluster_split |
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64 --print_empty_files |
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65 ``` |
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66 |
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67 **Example Input (`clusters.txt`)** |
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68 |
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69 |
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70 ``` |
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71 >Cluster 0 |
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72 0 357nt, >M01687:476:000000000-LL5F5:1:2113:18579:17490_CONS(1)... * |
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73 >Cluster 1 |
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74 0 85nt, >M01687:476:000000000-LL5F5:1:1102:21316:1191_CONS(59577)... at 1:85:1:85/+/98.82% |
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75 1 85nt, >M01687:476:000000000-LL5F5:1:1102:19793:1302_CONS(106)... at 1:85:1:85/+/97.65% |
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76 2 84nt, >M01687:476:000000000-LL5F5:1:1102:18943:1430_CONS(15)... at 1:84:1:85/+/98.81% |
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77 3 85nt, >M01687:476:000000000-LL5F5:1:1102:9619:1460_CONS(38)... at 1:85:1:85/+/97.65% |
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78 4 85nt, >M01687:476:000000000-LL5F5:1:1102:8280:1614_CONS(1)... at 1:85:1:85/+/97.65% |
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79 ... |
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80 1 39nt, >M01687:476:000000000-LL5F5:1:1116:4266:19390_CONS(1)... at 1:39:1:38/+/97.44% |
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81 >Cluster 530 |
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82 0 39nt, >M01687:476:000000000-LL5F5:1:2112:21268:1323_CONS(1)... * |
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83 >Cluster 531 |
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84 0 38nt, >M01687:476:000000000-LL5F5:1:2103:25634:11346_CONS(1)... * |
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85 >Cluster 532 |
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86 0 33nt, >M01687:476:000000000-LL5F5:1:2106:13260:18932_CONS(1)... * |
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87 >Cluster 533 |
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88 0 31nt, >M01687:476:000000000-LL5F5:1:1110:28179:10205_CONS(1)... * |
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89 >Cluster 534 |
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90 0 30nt, >M01687:476:000000000-LL5F5:1:1110:23278:23216_CONS(1)... * |
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91 >Cluster 535 |
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92 0 29nt, >M01687:476:000000000-LL5F5:1:2117:17691:6487_CONS(1)... * |
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93 >Cluster 536 |
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94 0 28nt, >M01687:476:000000000-LL5F5:1:1104:7756:22829_CONS(1)... * |
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95 |
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96 ``` |
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97 |
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98 **Example FASTA (`annotations.xlsx`)** |
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99 |
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100 |
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101 ```header e_value identity percentage coverage bitscore count source taxa kingdom phylum class order family genus species |
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102 M01687:476:000000000-LL5F5:1:1102:8926:6561_CONS 2.33E-41 98.889 100 161 12 NCBI Viridiplantae / Streptophyta / Magnoliopsida / Asterales / Asteraceae / Achillea / Achillea millefolium Viridiplantae Streptophyta Magnoliopsida Asterales Asteraceae Achillea Achillea millefolium |
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103 M01687:476:000000000-LL5F5:1:2114:16883:18620_CONS 1.08E-39 97.778 100 156 1 NCBI Viridiplantae / Streptophyta / Magnoliopsida / Asterales / Asteraceae / Achillea / Achillea millefolium Viridiplantae Streptophyta Magnoliopsida Asterales Asteraceae Achillea Achillea millefolium |
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104 M01687:476:000000000-LL5F5:1:1102:20658:7882_CONS 1.63E-37 98.795 100 148 29 NCBI Viridiplantae / Streptophyta / Magnoliopsida / Apiales / Apiaceae / Aegopodium / Aegopodium podagraria Viridiplantae Streptophyta Magnoliopsida Apiales Apiaceae Aegopodium Aegopodium podagraria |
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105 ... |
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106 M01687:476:000000000-LL5F5:1:2114:19155:4308_CONS 1.07E-39 100 94 156 13 NCBI Viridiplantae / Streptophyta / Magnoliopsida / Gentianales / Apocynaceae / Vinca / Vinca minor Viridiplantae Streptophyta Magnoliopsida Gentianales Apocynaceae Vinca Vinca minor |
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107 M01687:476:000000000-LL5F5:1:1117:11316:6653_CONS 4.96E-38 98.81 94 150 1 NCBI Viridiplantae / Streptophyta / Magnoliopsida / Gentianales / Apocynaceae / Vinca / Vinca minor Viridiplantae Streptophyta Magnoliopsida Gentianales Apocynaceae Vinca Vinca minor |
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108 M01687:476:000000000-LL5F5:1:1106:28052:14441_CONS 8.25E-41 98.876 100 159 1 NCBI Viridiplantae / Streptophyta / Magnoliopsida / Asterales / Asteraceae / Xanthium / Xanthium strumarium Viridiplantae Streptophyta Magnoliopsida Asterales Asteraceae Xanthium Xanthium strumarium |
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109 M01687:476:000000000-LL5F5:1:2118:15258:6790_CONS 8.25E-41 98.876 100 159 1 NCBI Viridiplantae / Streptophyta / Magnoliopsida / Asterales / Asteraceae / Xanthium / Xanthium strumarium Viridiplantae Streptophyta Magnoliopsida Asterales Asteraceae Xanthium Xanthium strumarium |
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110 ``` |
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111 **Outputs** |
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112 |
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113 | Output Type | Format | Description | |
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114 |--------------|--------|-------------| |
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115 | **Similarity summary** | `.txt` | Text file listing average and per-cluster similarity statistics, derived from the CD-HIT `.clstr` file. | |
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116 | **Similarity plot** | `.png` | Histogram or density plot showing sequence similarity distribution across all clusters; useful for identifying thresholds or anomalies. | |
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117 | **E-value summary** | `.txt` | Text file containing aggregated E-value statistics for all clusters (if available from annotation data). | |
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118 | **E-value plot** | `.png` | Visualization of E-value distribution, helping to identify potential low-confidence clusters. | |
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119 | **Cluster count summary** | `.txt` | Summary of the number of clusters, total reads per cluster, and counts of annotated vs. unannotated reads. | |
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120 | **Taxa per cluster** | `.txt` | Text file showing the dominant or representative taxon assigned to each cluster, including uncertainty ratios. | |
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121 | **Processed taxa summary** | `.txt` | Aggregated view of taxonomic composition after filtering and cluster-based reassignment. | |
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122 |
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123 |
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4
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124 **Output files (example)** |
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125 |
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126 outputs/ |
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127 ├── similarity_plot.png |
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128 <img width="3570" height="1765" alt="afbeelding" src="https://github.com/user-attachments/assets/f1ad5105-fcd1-4c2d-a5aa-7e8419b46281" /> |
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129 |
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130 ├── similarity_summary.txt |
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131 ``` |
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132 # Average similarity: 98.94 |
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133 # Standard deviation: 0.68 |
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134 similarity count |
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135 100.0 23803 |
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136 99.47 1 |
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137 99.46 1 |
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138 ... |
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139 97.18 1 |
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140 97.17 2 |
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141 97.14 11 |
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142 97.12 2 |
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143 97.1 1 |
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144 97.03 5 |
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145 97.0 946 |
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146 ``` |
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147 ├── evalue_plot.png |
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148 <img width="3565" height="1765" alt="afbeelding" src="https://github.com/user-attachments/assets/278fdfe3-882e-4f0e-901b-a2acbbcace24" /> |
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149 |
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150 ├── evalue_summary.txt |
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151 ``` |
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152 evalue count |
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153 unannotated 11754.0 |
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154 2.8e-40 59691 |
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155 2.16e-52 6595 |
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156 1.3e-38 6105 |
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157 2.57e-35 3332 |
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158 ... |
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159 7.3e-13 1 |
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160 2.06e-12 1 |
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161 5.4e-12 1 |
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162 8.73e-11 1 |
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163 ``` |
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164 ├── cluster_count.txt |
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165 ``` |
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166 cluster unannotated annotated total perc_unannotated perc_annotated |
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167 0 1.0 0 1.0 100.00 0.00 |
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168 1 16.0 68214 68230.0 0.02 99.98 |
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169 ... |
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170 535 1.0 0 1.0 100.00 0.00 |
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171 536 1.0 0 1.0 100.00 0.00 |
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172 TOTAL 11754.0 99826 111580.0 10.53 89.47 |
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173 ``` |
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174 ├── taxa_clusters.xlsx |
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175 ``` |
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176 cluster count taxa_full kingdom phylum class order family genus species |
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177 0 1 Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read |
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178 1 16 Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read |
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179 1 68189 Viridiplantae / Streptophyta / Magnoliopsida / Rosales / Ulmaceae / Ulmus / Uncertain taxa Viridiplantae Streptophyta Magnoliopsida Rosales Ulmaceae Ulmus Uncertain taxa |
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180 ... |
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181 534 1 Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read |
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182 535 1 Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read |
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183 536 1 Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read Unannotated read |
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184 ``` |
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185 └── taxa_processed.xlsx |
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186 ``` |
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187 cluster count taxa_full kingdom phylum class order family genus species |
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188 1 68189 Viridiplantae / Streptophyta / Magnoliopsida / Rosales / Ulmaceae / Ulmus / Uncertain taxa Viridiplantae Streptophyta Magnoliopsida Rosales Ulmaceae Ulmus Uncertain taxa |
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189 2 7781 Viridiplantae / Streptophyta / Magnoliopsida / Malpighiales / Salicaceae / Populus / Populus tremula Viridiplantae Streptophyta Magnoliopsida Malpighiales Salicaceae Populus Populus tremula |
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190 ... |
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191 518 1 Viridiplantae / Streptophyta / Magnoliopsida / Myrtales / Onagraceae / Circaea / Circaea lutetiana Viridiplantae Streptophyta Magnoliopsida Myrtales Onagraceae Circaea Circaea lutetiana |
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192 522 1 Viridiplantae / Streptophyta / Magnoliopsida / Rosales / Rosaceae / Rubus / Rubus idaeus Viridiplantae Streptophyta Magnoliopsida Rosales Rosaceae Rubus Rubus idaeus |
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193 532 1 Viridiplantae / Streptophyta / Magnoliopsida / Malpighiales / Euphorbiaceae / Euphorbia / Euphorbia myrsinites Viridiplantae Streptophyta Magnoliopsida Malpighiales Euphorbiaceae Euphorbia Euphorbia myrsinites |
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194 ``` |
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195 |
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196 #### **CLI Arguments (common)** |
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197 |
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198 | Argument | Description | |
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199 |-----------|--------------| |
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200 | `--input_cluster` | Path to the input CD-HIT cluster file (`.clstr`). | |
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201 | `--input_annotation` | Path to the annotation file (optional, e.g. `.out` from BLAST or other source). | |
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202 | `--output_similarity_txt` | Output path for similarity summary text file. | |
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203 | `--output_similarity_plot` | Output path for similarity plot image (`.png`). | |
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204 | `--output_evalue_txt` | Output path for E-value summary text file. | |
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205 | `--output_evalue_plot` | Output path for E-value plot image (`.png`). | |
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206 | `--output_count` | Output path for cluster count summary file. | |
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207 | `--output_taxa_clusters` | Output path for taxa-per-cluster file. | |
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208 | `--output_taxa_processed` | Output path for processed taxa summary file. | |
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209 | `--simi_plot_y_min` | Minimum value for the Y-axis in the similarity plot (default: `95.0`). | |
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210 | `--simi_plot_y_max` | Maximum value for the Y-axis in the similarity plot (default: `100.0`). | |
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211 | `--uncertain_taxa_use_ratio` | Ratio (0–1) determining how uncertain taxa contribute to the dominant taxon (default: `0.5`). | |
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212 | `--min_to_split` | Minimum taxonomic percentage threshold for splitting multi-taxon clusters (default: `0.45`). | |
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213 | `--min_count_to_split` | Minimum number of reads required to split a cluster by taxonomy (default: `10`). | |
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214 | `--show_unannotated_clusters` | Include clusters without any annotation in the output when specified. | |
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215 | `--make_taxa_in_cluster_split` | Enable splitting clusters containing multiple taxa into subclusters. | |
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216 | `--print_empty_files` | Print a message if an expected output file (e.g., annotation file) is empty. | |
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217 |
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218 |
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219 ### Galaxy integration |
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220 |
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221 The tool is also available through the Galaxy platform: |
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222 |
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223 - **Galaxy Toolshed**: The CDHIT cluster analysis tool is available in the Galaxy Toolshed, |
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224 enabling easy installation into any Galaxy instance. |
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225 - **Web-based interface**: Users can upload annotation and cluster files, configure validation parameters through the GUI, |
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226 run validations, and download results. |
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227 - **Workflow integration**: The tool can be incorporated into Galaxy workflows for automated processing pipelines. |
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228 |
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229 To use the tool in Galaxy: |
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230 1. Install the tool from the Galaxy Toolshed (search for "cdhit_analysis") |
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231 2. Upload your cluster and excel annotations files to your Galaxy history |
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232 3. Configure parameters through the GUI |
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233 4. Run the tool |
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234 5. View results and download validation reports and cluster annotations |
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235 |
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236 ## License |
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237 |
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238 No license yet |
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239 |
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240 ## Citation |
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241 |
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242 If you use this software in your research, please cite this repository. |
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243 |
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244 ## Contact |
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245 |
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246 For questions or issues: |
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247 - GitHub Issues: https://github.com/Onnodg/Naturalis_NLOOR/issues |
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248 - Email: onno.gorter@naturalis.nl (until Febuary 2026) |
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249 |
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250 ## Acknowledgments |
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251 |
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252 This tool was developed to support the New lights on old remedies project, a PhD project by Anja Fischer. |
