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added how to automate chronqc using chrongen
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nilesh-tawari committed Sep 29, 2017
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6 changes: 6 additions & 0 deletions README.rst
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Expand Up @@ -90,6 +90,12 @@ If you would like the development version instead, the command is::
pip install --upgrade --force-reinstall git+https://github.com/nilesh-tawari/ChronQC.git



Automation
==========

* For details on how to automate ChronQC plot generation see, `automate_chronqc <https://github.com/nilesh-tawari/ChronQC/tree/master/automate_chronqc>`_.

Citation
========

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225 changes: 225 additions & 0 deletions automate_chronqc/CONFIG/JSON/CET_config.json
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[
{
"//": "SNP and TiTv plots",
"table_name": "CET__SNPs_Indels_Stats_Summary",
"include_samples": "all",
"exclude_samples": "HCT15, NTC",
"chart_type": "time_series_with_box_whisker_plot",
"chart_properties": {
"chart_title": "CET: Number of SNPs found in Samples Over Time (per month)",
"y_value": "Number",
"Type": "SNPs",
"y_label": "# of SNPs found in each sample"
}
},
{
"table_name": "CET__SNPs_Indels_Stats_Summary",
"include_samples": "all",
"exclude_samples": "HCT15, NTC",
"chart_type": "time_series_with_box_whisker_plot",
"chart_properties": {
"chart_title": "CET: Number of Indels found in Samples over Time (per month)",
"y_value": "Number",
"Type": "Indels",
"y_label": "# of Indels found in each sample"
}
},
{
"table_name": "CET__Ti_Tv_Ratio_Stats",
"include_samples": "all",
"exclude_samples": "HCT15, NTC",
"chart_type": "time_series_with_mean_and_stdev",
"chart_properties": {
"chart_title": "CET: Transition to Transversion Ratio of Samples (per exome)",
"y_value": "Number",
"y_label": "TiTv ratio of sample",
"window" : "365D",
"per_sample": "True"
}
},
{
"\\": "Production stats",
"table_name": "CET__Production_Run_Stats_Summary",
"include_samples": "all",
"chart_type": "time_series_with_mean_and_stdev",
"chart_properties": {
"chart_title": "CET: % Duplicates in On-target Sites (per exome)",
"y_value": "Duplicates",
"y_label": "% Duplicates",
"window" : "365D",
"per_sample": "True"
}
},
{
"table_name": "CET__Production_Run_Stats_Summary",
"include_samples": "all",
"chart_type": "time_series_with_mean_and_stdev",
"chart_properties": {
"chart_title": "CET: Average Mapping Quality of On-target Sites (per exome)",
"y_value": "MappingQuality",
"y_label": "Mapping Quality",
"window" : "365D",
"per_sample": "True"
}
},
{
"table_name": "CET__Production_Run_Stats_Summary",
"include_samples": "all",
"chart_type": "time_series_with_mean_and_stdev",
"chart_properties": {
"chart_title": "CET: Average Base Quality Scored in On-target Sites (per exome)",
"y_value": "BaseQuality",
"y_label": "Average Base Quality Score",
"per_sample": "True"
}
},
{
"\\": "Production stats",
"table_name": "CET__Production_Run_Stats_Summary",
"include_samples": "all",
"chart_type": "time_series_with_mean_and_stdev",
"chart_properties": {
"chart_title": "CET: Number of Bases In Reads within On-target Sites (per exome)",
"y_value": "BasesOfReads",
"y_label": "Bases of Reads",
"window" : "365D",
"per_sample": "True"
}
},
{
"table_name": "CET__Production_Run_Stats_Summary",
"include_samples": "all",
"chart_type": "time_series_with_mean_and_stdev",
"chart_properties": {
"chart_title": "CET: % Bases in Reads within On-target Sites (per exome)",
"y_value": "%BasesofReads",
"y_label": "% Bases of Reads",
"window" : "365D",
"per_sample": "True"
}
},
{
"table_name": "CET__Production_Run_Stats_Summary",
"include_samples": "all",
"chart_type": "time_series_with_mean_and_stdev",
"chart_properties": {
"chart_title": "CET: Depth Median (per exome)",
"y_value": "Depth",
"y_label": "Depth Median",
"per_sample": "True"
}
},
{
"table_name": "CET__Production_Run_Stats_Summary",
"include_samples": "all",
"chart_type": "time_series_with_mean_and_stdev",
"chart_properties": {
"chart_title": "CET: GC Content % (per exome)",
"y_value": "GCContent",
"y_label": "GC Content %",
"window" : "365D",
"per_sample": "True"
}
},
{
"table_name": "CET__Protein_Change",
"include_samples": "all",
"exclude_samples": "HCT15, NTC",
"chart_type": "time_series_with_mean_and_stdev",
"chart_properties": {
"chart_title": "CET: Number of Missense Variants (per exome)",
"y_value": "Missense_variant",
"y_label": "# of Variants",
"window" : "365D",
"per_sample": "True"
}
},
{
"table_name": "CET__Protein_Change",
"include_samples": "all",
"exclude_samples": "HCT15, NTC",
"chart_type": "time_series_with_mean_and_stdev",
"chart_properties": {
"chart_title": "CET: Number of Synonymous Variants (per exome)",
"y_value": "Synonymous_variant",
"y_label": "# of Variants",
"window" : "365D",
"per_sample": "True"
}
},
{
"table_name": "CET__Protein_Change",
"include_samples": "all",
"exclude_samples": "HCT15, NTC",
"chart_type": "time_series_with_mean_and_stdev",
"chart_properties": {
"chart_title": "CET: Number of Protein Truncating Variants (per exome)",
"y_value": "Protein_trunc",
"y_label": "# of Variants",
"window" : "365D",
"per_sample": "True"
}
},
{
"//": "Sequencing plots",
"table_name": "CET__NextSeq_Stats_Summary",
"include_samples": "all",
"chart_type": "time_series_with_absolute_threshold",
"chart_properties": {
"chart_title": "CET: Cluster Density (per NextSeq flowcell)",
"y_value": "MeanClusterDensity",
"lower_threshold": 170,
"upper_threshold": 230,
"y_label": "Cluster Density",
"per_sample": "True"
}
},
{
"table_name": "CET__NextSeq_Stats_Summary",
"include_samples": "all",
"chart_type": "time_series_with_absolute_threshold",
"chart_properties": {
"chart_title": "CET: % of Cluster Passing Filter (per NextSeq flowcell)",
"y_value": "MeanPFClusterDensity",
"lower_threshold": 90,
"y_label": "PassFilter %",
"per_sample": "True"
}
},
{
"table_name": "CET__NextSeq_Stats_Summary",
"include_samples": "all",
"chart_type": "time_series_with_absolute_threshold",
"chart_properties": {
"chart_title": "CET: Q30 Score (per NextSeq flowcell)",
"y_value": "Q30",
"lower_threshold": 75,
"y_label": "Q30 Score",
"per_sample": "True"
}
},
{
"table_name": "CET__NextSeq_Stats_Summary",
"include_samples": "all",
"chart_type": "time_series_with_mean_and_stdev",
"chart_properties": {
"chart_title": "CET: % Aligned on PhiX (per NextSeq flowcell)",
"y_value": "PhiXAlignment",
"y_label": "Alignment to PhiX",
"window" : "365D",
"per_sample": "True"
}
},
{
"table_name": "CET__NextSeq_Stats_Summary",
"include_samples": "all",
"chart_type": "time_series_with_mean_and_stdev",
"chart_properties": {
"chart_title": "CET: % Error Rate of PhiX (per NextSeq flowcell)",
"y_value": "ErrorRate",
"y_label": "Error Rate",
"window" : "365D",
"per_sample": "True"
}
}
]

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