From 14124e13fe99bd33aa645227f01b5d9fac51af29 Mon Sep 17 00:00:00 2001 From: Jedidiah Carlson Date: Fri, 8 Jun 2018 17:36:22 -0400 Subject: [PATCH 1/6] update docs --- docs/index.md | 255 -------------------------------------- docs/usage.md | 335 ++++++++++++++++++++++++++++++++++++++++++++++++++ mkdocs.yml | 1 + 3 files changed, 336 insertions(+), 255 deletions(-) create mode 100644 docs/usage.md diff --git a/docs/index.md b/docs/index.md index 797bf38..92445a1 100644 --- a/docs/index.md +++ b/docs/index.md @@ -97,258 +97,3 @@ Due to the resource constraints of the public BinderHub server, this should not ------------------------------------ -# Usage - -``` -usage: doomsayer.py [-h] [-c [INT]] [-S [INT]] [-v] [-V] [-M [STR]] -i - [/path/to/input.vcf] [-f [/path/to/genome.fa]] - [-g [/path/to/sample_batches.txt]] - [-s [/path/to/kept_samples.txt]] [-C [INT]] [-X [INT]] - [-p [/path/to/project_directory]] [-m [STR]] [-o] - [-d [STR]] [-r [INT]] [-F [STR]] [-t [FLOAT]] [-l [INT]] - [-R] [-G] [-T [STR]] - -optional arguments: - -h, --help show this help message and exit - -c [INT], --cpus [INT] - number of CPUs. Must be integer value between 1 and 10 - -S [INT], --seed [INT] - random seed for NMF and outlier detection - -v, --verbose Enable verbose logging - -V, --version show program's version number and exit - -M [STR], --mode [STR] - Mode for parsing input. Must be one of {vcf, agg, - txt}. Defaults to VCF mode. - -i [/path/to/input.vcf], --input [/path/to/input.vcf] - In VCF mode (default) input file is a VCF or text file - containing paths of multiple VCFs. Defaults to accept - input from STDIN with "--input -". In aggregation - mode, input file is a text file containing mutation - subtype count matrices, or paths of multiple such - matrices. In plain text mode, input file is tab- - delimited text file containing 5 columns: CHR, POS, - REF, ALT, ID - -f [/path/to/genome.fa], --fastafile [/path/to/genome.fa] - reference fasta file - -g [/path/to/sample_batches.txt], --groupfile [/path/to/sample_batches.txt] - two-column tab-delimited file containing sample IDs - (column 1) and group membership (column 2) for pooled - analysis - -s [/path/to/kept_samples.txt], --samplefile [/path/to/kept_samples.txt] - file with sample IDs to include (one per line) - -C [INT], --minsnvs [INT] - minimum # of SNVs per individual to be included in - analysis. Default is 0. - -X [INT], --maxac [INT] - maximum allele count for SNVs to keep in analysis. - Defaults to 1 (singletons) Set to 0 to include all - variants. - -p [/path/to/project_directory], --projectdir [/path/to/project_directory] - directory to store output files (do NOT include a - trailing '/'). Defaults to ./doomsayer_output - -m [STR], --matrixname [STR] - filename prefix for M matrix [without extension] - -o, --filterout in VCF or plain text modes, re-reads input file and - writes to STDOUT, omitting records that occur in the - detected outliers. To write to a new file, use - standard output redirection [ > out.vcf] at the end of - the doomsayer.py command - -d [STR], --decomp [STR] - mode for matrix decomposition. Must be one of {nmf, - pca}. Defaults to pca. - -r [INT], --rank [INT] - Rank for Matrix decomposition. If --decomp pca, will - select first r components. Default [0] will force - Doomsayer to iterate through multiple ranks to find an - optimal choice. - -F [STR], --filtermode [STR] - Method for detecting outliers. Must be one of {ee, - lof, if, any, any2, all, none}. Defaults to ee. - -t [FLOAT], --threshold [FLOAT] - threshold for fraction of potential outliers - -l [INT], --length [INT] - motif length. Allowed values are 1,3,5,7 - -R, --report automatically generates an HTML-formatted report in R. - -G, --staticplots use static ggplot figures instead of interactive - plotly figures - -T [STR], --template [STR] - Template for diagnostic report. Must be one of - {diagnostics, msa}. Defaults to diagnostics. -``` - -## Program options - -`--cpus [INT]` - -Set the number of CPUs to use if input is a list of files. - -`--seed [INT]` - -Set the random seed to be used for NMF decomposition and outlier detection algorithms. If not specified, a random seed will be assigned and printed to the output if you need to reproduce results of a particular run. - -`--verbose` - -This flag enables debug logging for troubleshooting. - -`--version` - -Show program's version number and exit. - -## Input options - -These options together specify the data to be processed by Doomsayer. Each mode and the possible inputs it can accept are described in the [input modes](#input-modes) section. - -`--input [/path/to/input.vcf]` - -Doomsayer can accept multiple types of input: -- a single VCF file (either uncompressed or [bgzip](http://www.htslib.org/doc/tabix.html)-compressed) -- a text file containing the file paths of multiple VCF files (e.g., one per chromosome) -- a tab-delimited text file with one variant per row -- a text file containing the file paths of multiple matrices to be aggregated together - -By default, Doomsayer assumes input is a VCF file or text file containing file paths of multiple VCF files. To parse tab-delimited text files or aggregate data from multiple previous runs, use the `--mode txt` or `--mode agg` options, respectively. - -`--fastafile [/path/to/genome.fa]` - -In VCF mode and plain text mode, you **must** specify the fasta-formatted reference genome to be used to look up the local sequence context for each SNV. This file must corresponding to the same reference genome build used to call the variants contained in the input VCF file, with [consistently-formatted records](#reference-file-incompatibilities). The fasta file may be either uncompressed or bgzip-compressed. - -## Input modes - -`--mode vcf` - -### Single VCF file -A VCF file formatted with mandatory columns (#CHROM, POS, ID, REF, ALT, QUAL, FILTER, and INFO). This VCF must contain an allele count field in the INFO column ([AC=N]), and include individual genotypes (i.e., the VCF cannot be a "sites-only" file). - -The VCF input can be either a file on disk or piped from STDIN (using `--input -`), enabling compatibility with a wide range of existing pipelines and workflows. The VCF can contain any combination of variant types (e.g., SNVs, indels, CNVs), allele counts, or filter flags. By default, Doomsayer will only analyze singleton SNVs with a "PASS" value in the FILTER column of the VCF. This can be disabled with the `--novarfilter` flag. - -### Multiple VCF files -If your data are spread across multiple files (e.g., one VCF per chromosome), Doomsayer will accept a plain text file containing the absolute file paths (one per line) for the VCF files to process. This assumes all VCF files contain the exact same sample IDs and that the IDs in the VCF header are ordered identically across all subfiles. This option is best used in conjunction with the `--cpus {N}` argument to enable parallel processing of the files. - -`--mode txt` - -When using this mode, input must be a tab-delimited text file containing a list of SNVs with the following 5 columns (order must be maintained): -- Chromosome -- Position -- Reference allele -- Alternative allele -- Identifier variable - -The identifier variable can be any factor by which we wish to compare mutation patterns. This could be a population, gene ID, sample ID, variant quality level, etc. - -This is the most flexible input mode, as it allows the user to curate the set of variants and identifier variables as they see fit, though we leave it to the user to coerce their data into the requisite format. - -`--mode agg` - -This mode can be used to run Doomsayer on pre-existing sample x subtype SNV count matrices, which can be obtained either from the [output](#output-options) of previous Doomsayer runs, or generated by the user. Input should be a plain text file containing the absolute paths of the count matrices to aggregate. - -If generating these subtype count matrices outside of Doomsayer, files should be formatted as tab-delimited text files where the ith row of each file is a sample ID (or some other identifier variable) and the jth column is a mutation subtype. Row and column names must be included. - -Aggregation mode is useful if you are combining output from previous Doomsayer runs (e.g., adding data from a new batch of samples or aggregating across subregions) or wish to run Doomsayer with different filtering/output options without needing to re-run the more computationally demanding VCF processing. This could also be used to compare mutation patterns across different species or alignments. - -In aggregation mode, the input should be named either `m_regions.txt`, where each count matrix contains the same set of samples with subtype counts across a nonoverlapping set of regions, or `m_samples.txt`, where each file contains a nonoverlapping set of samples. If running regional aggregation, a final M matrix will be generated by summing subtype count matrices element-wise; if running sample aggregation, the M matrix will be generated by row-wise concatenation of the sub-matrices. - -If you plan on generating subtype count matrices via Doomsayer to aggregate at a later point, you should use the `--matrixname custom_output_name` to create unique file names for the matrices to combine. - -## Filtering options - -Doomsayer is designed to integrate in existing VCF processing workflows, so if you wish to apply sample-level or variant-level filters to your input data prior to running Doomsayer, we advise pre-filtering your data (e.g., using bcftools) for greater flexibility and efficiency. However, we have included options that enable the user to perform a few common filtering tasks directly in Doomsayer. - -`--samplefile [/path/to/kept_samples.txt]` - -*Currently only applies to VCF mode* - -To run Doomsayer on a subset of samples present in the input VCF, this parameter will read a list of sample IDs to keep (one per line) and skip all other samples in the VCF. - -`--groupfile [/path/to/sample_batches.txt]` - -*Currently only applies to VCF mode* - -This parameter forces Doomsayer to evaluate mutation spectra across pooled groups of samples. The GROUPFILE should be a tab-delimited text file containing sample IDs in the first column and a grouping variable (e.g., plate number, sequencing date, sub-study) in the second column. This option is particularly useful if you wish to explicitly filter for batch effects in your data, e.g., by setting the grouping variable to be the sequencing date, study of origin, sequencing plate, or some other batch variable. - -Note that this option will assume the GROUPFILE contains all samples in the input VCF. If your GROUPFILE contains only a subset of samples, other samples will not be evaluated. - -`--minsnvs [INT]` - -In some cases, samples may appear as outliers simply because they have very few observed SNVs. The `--minsnvs` parameter forces Doomsayer to only evaluate individuals with at least X observed SNVs. By default, `minsnvs=0`, and all samples are retained. If this option is enabled, the low-SNV outliers will be written to a separate file named `doomsayer_snvs_lt{X}.txt` in the output directory, and the keep/drop lists will be derived from the remaining subset of samples. - -Note that the `chisq` outlier detection mode is generally more robust to low-SNV outliers. - -`--maxac [INT]` - -By default, Doomsayer will evaluate only singleton SNVs (`--maxac 1`). To include more common SNVs, increase the value of this parameter. To include all SNVs, use `--maxac 0`. This is not recommended when using Doomsayer for QC functionality, but may be useful for more general mutation signature analysis. - -## Output options -The default output consists of two plain-text files: `doomsayer_keep.txt`, containing the IDs of samples that passed the filter, and `doomsayer_drop.txt`, containing the IDs of samples that failed the filter. These lists can be easily integrated into bcftools, vcftools, PLINK, and other tools to exclude outlier samples from your downstream analyses. - -By default, Doomsayer will also write three data files from the NMF decomposition to the output directory: -1. the M matrix of observed mutation spectra per sample -2. the H matrix containing loadings of the mutation subtypes in each signature -3. the W matrix containing the contributions of each signature within each sample's mutation spectrum - -`--projectdir [/path/to/project_directory]` - -By default, output files are stored in a subfolder named `/doomsayer_output/` in your current directory. The `--projectdir` parameter will specify a custom name/location for the Doomsayer output directory. - -`--matrixname [STR]` - -This parameter allows you to specify a custom name for the mutation spectra matrix file. The default is `--matrixname subtype_count_matrix`. This is particularly useful if you wish to generate an initial count matrix then play around with the outlier detection parameters. - -`--filterout` - -If the input is a single VCF or text file of sites, this flag will force Doomsayer to re-read the input file and write a new file of the same format, removing any samples specified in the `doomsayer_drop.txt` list that has been generated. - -This command will print the VCF header and records to STDOUT, which can then be piped to compatible programs, or redirected to a file using standard UNIX redirection (i.e., adding `> /path/to/output.vcf` at the end of the command), allowing Doomsayer to be used as an intermediate step of more complex VCF processing pipelines. - -As far as possible, all records present in the original input will be preserved in the output, with three notable exceptions: -1. All samples in the drop list (and their genotypes) will be omitted -2. **Variants that were unique to the set of dropped samples will be automatically removed.** -3. Four of the INFO fields will be updated to reflect the smaller set of retained samples: - 1. The total number of alleles (AN) - 2. allele count in genotypes (AC) - 3. number of samples (NS) - 4. combined depth (DP) - -## Matrix decomposition and outlier detection options - -`--decomp [STR]` - -Doomsayer will decompose the subtype count matrix using either Principal Components Analysis (PCA), or Nonnegative Matrix Factorization (NMF). - -`--rank [INT]` - -Set the rank of the NMF decomposition to R components if using `--decomp nmf`, or select the first R principal components if using `--decomp pca` - -`--filtermode [STR]` - -Once we have reduced the input matrix to R components, we want to identify which individuals are outliers in that R-dimensional space. Doomsayer can apply three different outlier detection algorithms: elliptic envelopes, local outlier factors, and isolation forests. - -- `--filtermode ee`: Outliers are determined by assuming components follow a multivariate Gaussian distribution, and computing an elliptic envelope. -- `--filtermode lof`: Outliers are determined using local outlier factors. -- `--filtermode if`: Outliers are determined using isolation forests. - -In addition, Doomsayer can perform omnibus filtering using two or more of the above methods: -- `--filtermode any2`: Outliers must be called by at least two of the above methods -- `--filtermode all`: Outliers must be called by all three of the above methods (will call the fewest outliers) - -To disable outlier detection, use `--filtermode none` - -For a detailed overview of these methods, see the [scikit-learn outlier detection tutorial](http://scikit-learn.org/stable/modules/outlier_detection.html). - -`--threshold [FLOAT]` - -This parameter specifies the fraction of the sample to flag as potential outliers by a given algorithm. If we set `--threshold 0.05` (the default) and use either the ee, lof, or if filter modes, Doomsayer will always flag ~5% of the sample as outliers. - -When using the omnibus filtering modes, - -`--length {1,3,5,7}` - -This parameter specifies the (symmetric) motif length to be considered in determining the mutation subtypes. The default (3) produces 96 3-mer subtypes, which is likely sufficient for QC of whole-genome germline variants. If you are using Doomsayer for QC of whole-exome germline variants, you will likely need to specify `--length 1`, as most individuals will not have enough singleton variants to accurately infer higher-order mutation signatures. Values greater than 3 will likely lead to extremely noisy or unreliable QC results for germline variants, but may be useful for examining somatic sequencing data. - -## Generate a diagnostic report -`--report` + `--template` - -The `--report` option will tell Doomsayer to execute the `generate_report.r` script. This script will copy an [RMarkdown template](report_templates) (specified with the `-T, --template` parameter) into `~/doomsayer_output/` (or the user-specified project directory) and render an HTML-formatted report detailing the results of your Doomsayer run. - -By default, plots are fully interactive using the Plotly engine. If you want to download static .png images, just mouse over the upper right corner of the figure and click the camera icon. - -Alternatively, you can set the `--staticplots` option in your command, which will generate a report without any interactive elements. The standalone .png images will be saved to `~/doomsayer_output/report_files/figure-html/`. diff --git a/docs/usage.md b/docs/usage.md new file mode 100644 index 0000000..1f0d802 --- /dev/null +++ b/docs/usage.md @@ -0,0 +1,335 @@ +# Usage + +Running `python helmsman.py -h` will display a help message with detailed information for each option. + +``` +usage: doomsayer.py [-h] [-c [INT]] [-S [INT]] [-v] [-V] [-M [STR]] -i + [/path/to/input.vcf] [-f [/path/to/genome.fa]] + [-g [/path/to/sample_batches.txt]] + [-s [/path/to/kept_samples.txt]] [-C [INT]] [-X [INT]] + [-p [/path/to/project_directory]] [-m [STR]] [-o] + [-d [STR]] [-r [INT]] [-F [STR]] [-t [FLOAT]] [-l [INT]] + [-R] [-G] [-T [STR]] + +optional arguments: + -h, --help show this help message and exit + -c [INT], --cpus [INT] + number of CPUs. Must be integer value between 1 and 10 + -S [INT], --seed [INT] + random seed for NMF and outlier detection + -v, --verbose Enable verbose logging + -V, --version show program's version number and exit + -M [STR], --mode [STR] + Mode for parsing input. Must be one of {vcf, agg, + txt}. Defaults to VCF mode. + -i [/path/to/input.vcf], --input [/path/to/input.vcf] + In VCF mode (default) input file is a VCF or text file + containing paths of multiple VCFs. Defaults to accept + input from STDIN with "--input -". In aggregation + mode, input file is a text file containing mutation + subtype count matrices, or paths of multiple such + matrices. In plain text mode, input file is tab- + delimited text file containing 5 columns: CHR, POS, + REF, ALT, ID + -f [/path/to/genome.fa], --fastafile [/path/to/genome.fa] + reference fasta file + -g [/path/to/sample_batches.txt], --groupfile [/path/to/sample_batches.txt] + two-column tab-delimited file containing sample IDs + (column 1) and group membership (column 2) for pooled + analysis + -s [/path/to/kept_samples.txt], --samplefile [/path/to/kept_samples.txt] + file with sample IDs to include (one per line) + -C [INT], --minsnvs [INT] + minimum # of SNVs per individual to be included in + analysis. Default is 0. + -X [INT], --maxac [INT] + maximum allele count for SNVs to keep in analysis. + Defaults to 1 (singletons) Set to 0 to include all + variants. + -p [/path/to/project_directory], --projectdir [/path/to/project_directory] + directory to store output files (do NOT include a + trailing '/'). Defaults to ./doomsayer_output + -m [STR], --matrixname [STR] + filename prefix for M matrix [without extension] + -o, --filterout in VCF or plain text modes, re-reads input file and + writes to STDOUT, omitting records that occur in the + detected outliers. To write to a new file, use + standard output redirection [ > out.vcf] at the end of + the doomsayer.py command + -d [STR], --decomp [STR] + mode for matrix decomposition. Must be one of {nmf, + pca}. Defaults to pca. + -r [INT], --rank [INT] + Rank for Matrix decomposition. If --decomp pca, will + select first r components. Default [0] will force + Doomsayer to iterate through multiple ranks to find an + optimal choice. + -F [STR], --filtermode [STR] + Method for detecting outliers. Must be one of {ee, + lof, if, any, any2, all, none}. Defaults to ee. + -t [FLOAT], --threshold [FLOAT] + threshold for fraction of potential outliers + -l [INT], --length [INT] + motif length. Allowed values are 1,3,5,7 + -R, --report automatically generates an HTML-formatted report in R. + -G, --staticplots use static ggplot figures instead of interactive + plotly figures + -T [STR], --template [STR] + Template for diagnostic report. Must be one of + {diagnostics, msa}. Defaults to diagnostics. +``` + +## Program options + +`--cpus [INT]` + +Set the number of CPUs to use if input is a list of files. + +`--seed [INT]` + +Set the random seed to be used for NMF decomposition and outlier detection algorithms. If not specified, a random seed will be assigned and printed to the output if you need to reproduce results of a particular run. + +`--verbose` + +This flag enables debug logging for troubleshooting. + +`--version` + +Show program's version number and exit. + +## Input options + +These options specify the data to be processed by *Doomsayer*. By default, *Doomsayer* assumes input is a VCF file or text file containing file paths of multiple VCF files. + +### Reference genome + +`--fastafile [/path/to/genome.fa]` + +In VCF mode, MAF mode, and plain text mode, you **must** specify the fasta-formatted reference genome to be used to look up the local sequence context for each SNV. This file must corresponding to the same reference genome build used to call the variants contained in the input file. The fasta file may be either uncompressed or bgzip-compressed. + +### VCF mode + +`--mode vcf` + +*Doomsayer* can accept variant call format (VCF) or binary call format (BCF) files, either uncompressed or [bgzip](http://www.htslib.org/doc/tabix.html)-compressed. VCF/BCF files are assumed to be formatted with mandatory columns (`#CHROM, POS, ID, REF, ALT, QUAL, FILTER, INFO`). This VCF must contain an allele count field in the INFO column (`[AC=N]`), and include individual genotypes (i.e., the VCF cannot be a "sites-only" file). + +#### Single VCF file + +`--mode vcf --input /path/to/input.vcf` + +The VCF input can be either a file on disk or piped from STDIN (using `--input -`), enabling compatibility with a wide range of existing pipelines and workflows. The VCF can contain any combination of variant types (e.g., SNVs, indels, CNVs), allele counts, or filter flags. By default, *Doomsayer* will only analyze singleton SNVs with a "PASS" value in the FILTER column of the VCF. + +#### Multiple VCF files, same samples + +`--mode vcf --input /path/to/vcfs.txt` + +If your data are spread across multiple files, each containing the same samples (e.g., one VCF per chromosome), *Doomsayer* will accept a plain text file containing the absolute file paths (one per line) for the VCF files to process. This assumes all VCF files contain the exact same sample IDs and that the IDs in the VCF header are ordered identically across all subfiles. This option is best used in conjunction with the `--cpus {N}` argument to enable parallel processing of the files. + +#### Multiple VCF files, different samples + +`--mode vcf --input /path/to/vcfs.txt --rowwise` + +If you instead have VCFs containing non-overlapping subsets of the sample (e.g., one per individual), use the `--rowwise` flag to properly generate the mutation spectra matrix. + +#### Restrict to specific samples + +`--samplefile /path/to/samples.txt` + +If your input VCF file(s) contains samples that you do not wish to analyze, provide a tab-delimited text file containing the sample IDs you wish to **keep**. This file can contain any number of columns, as long as the sample IDs are contained in the first column, and the file has a header with column names (the first column must be named `ID`). + +#### Pool samples together + +`--samplefile /path/to/samples.txt --groupvar GROUP` + +In some cases it may be necessary (or desired) to run *Doomsayer* with samples pooled together in some way. For example, if samples were sequenced on different dates and we want to explicitly look for batch effects, we can supply a file containing sample IDs in the `ID` column and the sequencing date in the `DATE`. If the `--groupvar DATE` option is used, *Doomsayer* will pool samples by the value present in the `DATE` column rather than the `ID` column. + +Note that the `--samplefile` option will operate as above--only samples present in this file will be considered when generating the mutation spectra matrix. + +### MAF mode + +`--mode maf --input /path/to/input.maf` + +*Doomsayer* can also accept [Mutation Annotation Format](https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/) files. By default, SNVs will be counted per unique identifier in the `Tumor_Sample_Barcode` column, but any column can be specified using the `--groupvar` option. + +### TXT mode + +`--mode txt --input /path/to/input.txt` + +*Doomsayer* can also accept a tab-delimited text file, containing a list of SNVs with the following 5 columns (order must be maintained): + +- Chromosome +- Position +- Reference allele +- Alternative allele +- Sample ID (or other identifier variable) + +### Aggregation mode + +This mode can be used to run *Doomsayer* on one or more existing mutation spectra matrices, which can be obtained from the [output](#output-options) of previous *Doomsayer* runs. + +#### Re-run on a single previously-generated matrix + +`--mode agg --input /path/to/subtype_count_matrix.txt` + +Suppose you have already run *Doomsayer* on a large dataset and generated the mutation spectra matrix, but wish to re-run it with different outlier detection parameters. Rather than re-running on the original data, you can use aggregation mode with the existing mutation spectra matrix as the input file. + +#### Combine multiple matrices with different samples + +`--mode agg --input /path/to/m_samples.txt` + +If you have generated mutation spectra matrices from different **non-overlapping** subsamples (e.g., one VCF per individual), you can use aggregation mode to run a combined analysis on all samples together. Simply put the absolute file paths for each of the matrices (one per line) into a text file named `/path/to/m_samples.txt` + +For example, if you have run *Doomsayer* on one sample of N individuals and another of M individuals, this will create an (N+M)x96 matrix and run the combined analysis. + +We advise users to exercise caution with interpreting results of aggregated samples, as different datasets can have different SNV distributions. + +#### Combine multiple matrices from different genomic regions + +`--mode agg --input /path/to/m_regions.txt` + +Similarly, if you have generated mutation spectra matrices from different **non-overlapping** genomic regions (e.g., one per chromsome), but in the same sample, put the absolute file paths for each of the matrices (one per line) into a text file named `/path/to/m_regions.txt`, and *Doomsayer* will sum the elements of each matrix. When combining by region, it is essential that the matrices have the **exact** same number of samples. + +If you anticipate generating multiple mutation spectra matrices by sample or by region to be aggregated at a later point, we recommend setting a unique name for the output file using the [`--matrixname custom_output_name`](#customize-matrix-prefix) option and/or putting the results of each run in a different directory with the `--projectdir` option, to avoid mixing up which output files are being generated. + +## Filtering options + +*Doomsayer* is designed to integrate in existing VCF processing workflows, so if you wish to apply sample-level or variant-level filters to your input data prior to running *Doomsayer*, we advise pre-filtering your data (e.g., using bcftools) for greater flexibility and efficiency. However, we have included options that enable the user to perform a few common filtering tasks directly in *Doomsayer*. + +### Exclude samples with too few SNVs + +`--minsnvs [INT]` + +In some cases, samples may appear as outliers simply because they have very few observed SNVs. The `--minsnvs` parameter forces *Doomsayer* to only evaluate individuals with at least X observed SNVs. By default, `minsnvs=0`, and all samples are retained. If this option is enabled, the low-SNV outliers will be written to a separate file named `doomsayer_snvs_lt{X}.txt` in the output directory, and the keep/drop lists will be derived from the remaining subset of samples. + +Note that the `chisq` outlier detection mode is generally more robust to low-SNV outliers. + +### Specify maximum allele count of SNVs to analyze + +`--maxac [INT]` + +By default, *Doomsayer* will evaluate only singleton SNVs (`--maxac 1`). To include more common SNVs, increase the value of this parameter. To include all SNVs, use `--maxac 0`. This is not recommended when using *Doomsayer* for QC functionality, but may be useful for more general mutation signature analysis. + +## Output options + +### Output directory + +`--projectdir [/path/to/project_directory]` + +By default, output files are stored in a subfolder named `/doomsayer_output/` in your current directory. The `--projectdir` parameter will specify a custom name/location for the *Doomsayer* output directory. + +The output folder will contain the following data files (depending on which options are used): + +1. the M matrix of observed mutation spectra per sample +2. the H matrix containing loadings of the mutation subtypes in each signature +3. the W matrix containing the contributions of each signature within each sample's mutation spectrum + +The default output consists of two plain-text files: `doomsayer_keep.txt`, containing the IDs of samples that passed the filter, and `doomsayer_drop.txt`, containing the IDs of samples that failed the filter. These lists can be easily integrated into bcftools, vcftools, PLINK, and other utilities to exclude outlier samples from your downstream analyses. + +### Customize matrix prefix + +`--matrixname [STR]` + +This parameter allows you to specify a custom name for the mutation spectra matrix file. The default is `--matrixname subtype_count_matrix`. This is particularly useful if you wish to generate an initial count matrix then play around with the outlier detection parameters. + +### Auto-filter flagged outliers + +`--filterout` + +If the input is a single VCF or text file of sites, this flag will force *Doomsayer* to re-read the input file and write a new file of the same format, removing any samples specified in the `doomsayer_drop.txt` list that has been generated. + +This command will print the VCF header and records to STDOUT, which can then be piped to compatible programs, or redirected to a file using standard UNIX redirection (i.e., adding `> /path/to/output.vcf` at the end of the command), allowing *Doomsayer* to be used as an intermediate step of more complex VCF processing pipelines. + +As far as possible, all records present in the original input will be preserved in the output, with three notable exceptions: +1. All samples in the drop list (and their genotypes) will be omitted +2. **Variants that were unique to the set of dropped samples will be automatically removed.** +3. Four of the INFO fields will be updated to reflect the smaller set of retained samples: + 1. The total number of alleles (AN) + 2. allele count in genotypes (AC) + 3. number of samples (NS) + 4. combined depth (DP) + +## Matrix decomposition options + +### NMF decomposition + +`--decomp nmf` + +*Doomsayer* will decompose the subtype count matrix using Nonnegative Matrix Factorization (NMF), as implemented in the [nimfa]() Python library. + + +### PCA decomposition + +`--decomp pca` + +*Doomsayer* will decompose the subtype count matrix using Principal Component Analysis (PCA). + +### Motif length + +`--length {1,3,5,7}` + +This parameter specifies the (symmetric) motif length to be considered in determining the mutation subtypes. The default (3) produces 96 3-mer subtypes, which is likely sufficient for QC of whole-genome germline variants. If you are using *Doomsayer* for QC of whole-exome germline variants, you will likely need to specify `--length 1`, as most individuals will not have enough singleton variants to accurately infer higher-order mutation signatures. Values greater than 3 will likely lead to extremely noisy or unreliable QC results for germline variants, but may be useful for examining somatic sequencing data. + +### Decomposition rank + +`--rank [INT]` + +Set the rank of the NMF decomposition to R components if using `--decomp nmf`, or select the first R principal components if using `--decomp pca`. + +## Outlier detection options + +`--filtermode [STR]` + +Once we have reduced the input matrix to R components, we want to identify which individuals are outliers in that R-dimensional space. *Doomsayer* can apply three different outlier detection algorithms: elliptic envelopes, local outlier factors, and isolation forests. For a detailed overview of these methods, see the [scikit-learn outlier detection tutorial](http://scikit-learn.org/stable/modules/outlier_detection.html). + +### Detection modes + +#### Elliptic envelope +- `--filtermode ee`: Outliers are determined by assuming components follow a multivariate Gaussian distribution, and computing an elliptic envelope. + + +#### Local outlier factor + +- `--filtermode lof`: Outliers are determined using local outlier factors. + +#### Isolation forests +- `--filtermode if`: Outliers are determined using isolation forests. + + +#### Omnibus filtering + +In addition, *Doomsayer* can perform omnibus filtering using two or more of the above methods: +- `--filtermode any2`: Outliers must be called by at least two of the above methods +- `--filtermode all`: Outliers must be called by all three of the above methods (will call the fewest outliers) + +#### Skip outlier detection + +To disable outlier detection, use `--filtermode none` (useful if you plan on aggregating data from multiple runs) + +### Detection threshold + +`--threshold [FLOAT]` + +This parameter specifies the fraction of the sample to flag as potential outliers by a given algorithm. If we set `--threshold 0.05` (the default) and use either the `ee`, `lof`, or `if` filter modes, *Doomsayer* will always flag ~5% of the sample as outliers. + +When using the omnibus filtering modes, fewer outliers will be flagged, as they must meet more stringent criteria. + +## Generate a diagnostic report +`--report` + `--template` + +The `--report` option will tell *Doomsayer* to execute the `generate_report.r` script. This script will copy an [RMarkdown template](report_templates) (specified with the `-T, --template` parameter) into `~/doomsayer_output/` (or the user-specified project directory) and render an HTML-formatted report detailing the results of your *Doomsayer* run. + +By default, plots are fully interactive using the Plotly engine. If you want to download static .png images, just mouse over the upper right corner of the figure and click the camera icon. + +Alternatively, you can set the `--staticplots` option in your command, which will generate a report without any interactive elements. The standalone .png images will be saved to `~/doomsayer_output/report_files/figure-html/`. + +### Use static images in report + +`--staticplots` + +By default, figures in the *Doomsayer* report will be fully interactive. This option will force the report to include only static figures. + +### Evaluate sample-level variables + +`--svars [COLUMN1,COLUMN2,COLUMN3]` + +If you have run *Doomsayer* with a sample file, you can include the `--svars` option, specifying a comma-separated list of variables to evaluate in the diagnostic report. This report will include boxplots showing the distribution of each variable for inliers compared to the different outlier clusters. Variables are assumed to be numeric. \ No newline at end of file diff --git a/mkdocs.yml b/mkdocs.yml index 7781608..b769519 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -3,6 +3,7 @@ site_url: https://github.com/carjed/doomsayer repo_url: https://github.com/carjed/doomsayer pages: - Home: index.md + - Usage: usage.md - FAQ: faq.md - Support: support.md theme: cinder From 68fea375768eb1dde14b8f1eb302ed51e176786e Mon Sep 17 00:00:00 2001 From: Jedidiah Carlson Date: Fri, 8 Jun 2018 19:54:54 -0400 Subject: [PATCH 2/6] update path to logo --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index ff87873..c21d577 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ -![](assets/doomsayer_logo2.png) +![](https://raw.githubusercontent.com/carjed/doomsayer/master/assets/doomsayer_logo2.png) [![DOI](https://zenodo.org/badge/95728792.svg?style=flat)](https://zenodo.org/badge/latestdoi/95728792) [![Docs](https://img.shields.io/badge/docs-latest-blue.svg)](http://www.jedidiahcarlson.com/docs/doomsayer) [![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg?style=flat)](https://opensource.org/licenses/MIT) [![Binder](https://img.shields.io/badge/launch-binder-d06681.svg?style=flat)](https://mybinder.org/v2/gh/carjed/doomsayer/master) [![Build Status](https://travis-ci.org/carjed/doomsayer.svg?style=flat?branch=master)](https://travis-ci.org/carjed/doomsayer) From 66097ff426d89abb2f50807b908aaeca67a2bc92 Mon Sep 17 00:00:00 2001 From: Jedidiah Carlson Date: Fri, 8 Jun 2018 20:18:21 -0400 Subject: [PATCH 3/6] replace tutorial data with properly formatted subtypes --- tutorial_data/NMF_M_spectra.txt | 6271 +++++++++++++++++++------------ 1 file changed, 3766 insertions(+), 2505 deletions(-) diff --git a/tutorial_data/NMF_M_spectra.txt b/tutorial_data/NMF_M_spectra.txt index b86c73b..9bc8e8b 100644 --- a/tutorial_data/NMF_M_spectra.txt +++ b/tutorial_data/NMF_M_spectra.txt @@ -1,2505 +1,3766 @@ -ID A_C.AAA A_C.AAC A_C.AAG A_C.AAT A_C.CAA A_C.CAC A_C.CAG A_C.CAT A_C.GAA A_C.GAC A_C.GAG A_C.GAT A_C.TAA A_C.TAC A_C.TAG A_C.TAT A_G.AAA A_G.AAC A_G.AAG A_G.AAT A_G.CAA A_G.CAC A_G.CAG A_G.CAT A_G.GAA A_G.GAC A_G.GAG A_G.GAT A_G.TAA A_G.TAC A_G.TAG A_G.TAT A_T.AAA A_T.AAC A_T.AAG A_T.AAT A_T.CAA A_T.CAC A_T.CAG A_T.CAT A_T.GAA A_T.GAC A_T.GAG A_T.GAT A_T.TAA A_T.TAC A_T.TAG A_T.TAT C_A.ACA C_A.ACC C_A.ACG C_A.ACT C_A.CCA C_A.CCC C_A.CCG C_A.CCT C_A.GCA C_A.GCC C_A.GCG C_A.GCT C_A.TCA C_A.TCC C_A.TCG C_A.TCT C_G.ACA C_G.ACC C_G.ACG C_G.ACT C_G.CCA C_G.CCC C_G.CCG C_G.CCT C_G.GCA C_G.GCC C_G.GCG C_G.GCT C_G.TCA C_G.TCC C_G.TCG C_G.TCT C_T.ACA C_T.ACC C_T.ACG C_T.ACT C_T.CCA C_T.CCC C_T.CCG C_T.CCT C_T.GCA C_T.GCC C_T.GCG C_T.GCT C_T.TCA C_T.TCC C_T.TCG C_T.TCT -HG00096 17999.0 5646.0 8632.0 8707.0 9519.0 6197.0 7374.0 9133.0 5929.0 2307.0 4671.0 3770.0 9668.0 3131.0 4347.0 7970.0 28558.0 22853.0 20658.0 51592.0 17959.0 16535.0 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468.0 332.0 331.0 360.0 447.0 345.0 -HG02006 211.0 39.0 116.0 102.0 119.0 76.0 111.0 111.0 83.0 25.0 64.0 49.0 77.0 35.0 41.0 66.0 365.0 285.0 242.0 632.0 223.0 227.0 326.0 682.0 176.0 127.0 176.0 233.0 301.0 249.0 225.0 722.0 92.0 57.0 44.0 112.0 42.0 79.0 74.0 121.0 59.0 50.0 70.0 134.0 95.0 38.0 40.0 102.0 158.0 206.0 42.0 101.0 125.0 116.0 28.0 101.0 153.0 127.0 46.0 84.0 122.0 129.0 31.0 184.0 137.0 105.0 29.0 159.0 105.0 135.0 37.0 146.0 81.0 83.0 20.0 96.0 121.0 117.0 21.0 247.0 565.0 375.0 752.0 433.0 407.0 343.0 682.0 458.0 302.0 339.0 526.0 354.0 318.0 370.0 486.0 367.0 -HG02008 18081.0 5670.0 8662.0 8746.0 9553.0 6220.0 7418.0 9179.0 5955.0 2313.0 4690.0 3785.0 9709.0 3137.0 4369.0 8016.0 28678.0 22979.0 20758.0 51898.0 18063.0 16641.0 22484.0 48378.0 16384.0 11748.0 13089.0 19127.0 23409.0 20293.0 18181.0 59331.0 10318.0 6664.0 5808.0 11303.0 5665.0 5468.0 6402.0 12407.0 5505.0 5353.0 4808.0 12208.0 9196.0 3967.0 4221.0 11117.0 17556.0 17780.0 3051.0 10585.0 11987.0 9485.0 2134.0 9383.0 14154.0 10645.0 3135.0 8384.0 12323.0 10712.0 2196.0 19363.0 12669.0 6939.0 2022.0 12884.0 7316.0 7716.0 1960.0 10326.0 5756.0 5275.0 1224.0 7147.0 10816.0 8972.0 1931.0 19673.0 46979.0 29098.0 55345.0 35005.0 31361.0 27807.0 45315.0 38931.0 24662.0 25522.0 36587.0 30259.0 28241.0 29080.0 36869.0 32485.0 -HG02009 18137.0 5683.0 8692.0 8778.0 9593.0 6236.0 7441.0 9187.0 5980.0 2324.0 4713.0 3797.0 9726.0 3147.0 4390.0 7998.0 28710.0 22988.0 20782.0 51906.0 18106.0 16679.0 22541.0 48511.0 16405.0 11771.0 13125.0 19151.0 23428.0 20315.0 18205.0 59380.0 10328.0 6662.0 5794.0 11304.0 5675.0 5476.0 6413.0 12423.0 5516.0 5357.0 4804.0 12189.0 9189.0 3983.0 4236.0 11110.0 17568.0 17801.0 3070.0 10612.0 12033.0 9520.0 2134.0 9392.0 14165.0 10669.0 3142.0 8407.0 12331.0 10752.0 2204.0 19378.0 12682.0 6944.0 2032.0 12938.0 7349.0 7735.0 1974.0 10352.0 5755.0 5326.0 1229.0 7188.0 10811.0 8999.0 1944.0 19737.0 47036.0 29135.0 55454.0 35038.0 31417.0 27839.0 45513.0 39007.0 24721.0 25539.0 36675.0 30282.0 28359.0 29106.0 36937.0 32526.0 -HG02010 193.0 58.0 109.0 106.0 129.0 91.0 118.0 139.0 81.0 33.0 66.0 44.0 94.0 35.0 54.0 78.0 398.0 276.0 290.0 706.0 267.0 259.0 333.0 718.0 215.0 101.0 174.0 240.0 307.0 216.0 230.0 794.0 120.0 58.0 58.0 123.0 63.0 75.0 66.0 127.0 65.0 66.0 65.0 119.0 109.0 47.0 50.0 121.0 203.0 235.0 50.0 129.0 144.0 117.0 38.0 89.0 172.0 152.0 60.0 101.0 140.0 139.0 31.0 205.0 149.0 106.0 33.0 186.0 108.0 145.0 34.0 191.0 77.0 101.0 27.0 123.0 142.0 148.0 25.0 283.0 662.0 397.0 757.0 447.0 438.0 335.0 731.0 502.0 314.0 370.0 591.0 390.0 355.0 352.0 555.0 398.0 -HG02012 187.0 68.0 101.0 101.0 110.0 69.0 80.0 112.0 76.0 29.0 72.0 34.0 91.0 47.0 37.0 77.0 342.0 230.0 249.0 628.0 186.0 184.0 305.0 553.0 210.0 126.0 161.0 199.0 247.0 183.0 193.0 640.0 93.0 56.0 67.0 125.0 45.0 49.0 68.0 107.0 59.0 50.0 52.0 118.0 83.0 22.0 38.0 84.0 144.0 169.0 38.0 104.0 121.0 108.0 26.0 104.0 151.0 128.0 32.0 102.0 107.0 124.0 26.0 181.0 138.0 92.0 31.0 151.0 93.0 92.0 21.0 146.0 93.0 74.0 21.0 88.0 122.0 116.0 26.0 231.0 519.0 305.0 637.0 361.0 376.0 292.0 612.0 443.0 266.0 295.0 471.0 309.0 294.0 309.0 420.0 320.0 -HG02013 18085.0 5681.0 8672.0 8765.0 9542.0 6226.0 7417.0 9169.0 5949.0 2319.0 4686.0 3788.0 9692.0 3140.0 4369.0 8005.0 28670.0 22956.0 20752.0 51825.0 18057.0 16603.0 22433.0 48329.0 16362.0 11716.0 13110.0 19077.0 23357.0 20310.0 18148.0 59209.0 10303.0 6645.0 5803.0 11290.0 5672.0 5472.0 6403.0 12410.0 5502.0 5356.0 4777.0 12182.0 9167.0 3976.0 4224.0 11081.0 17569.0 17752.0 3052.0 10595.0 11981.0 9483.0 2123.0 9371.0 14157.0 10633.0 3133.0 8395.0 12308.0 10700.0 2195.0 19328.0 12679.0 6927.0 2015.0 12906.0 7332.0 7699.0 1946.0 10323.0 5766.0 5277.0 1224.0 7150.0 10804.0 8952.0 1934.0 19695.0 46947.0 29068.0 55294.0 34967.0 31315.0 27775.0 45314.0 38866.0 24615.0 25455.0 36567.0 30225.0 28215.0 29046.0 36823.0 32469.0 -HG02014 18129.0 5691.0 8708.0 8777.0 9561.0 6238.0 7448.0 9180.0 5952.0 2319.0 4712.0 3793.0 9711.0 3156.0 4366.0 8006.0 28771.0 23041.0 20770.0 51981.0 18121.0 16662.0 22539.0 48521.0 16408.0 11764.0 13164.0 19144.0 23441.0 20310.0 18223.0 59349.0 10312.0 6660.0 5808.0 11312.0 5668.0 5489.0 6406.0 12415.0 5511.0 5376.0 4804.0 12240.0 9200.0 3976.0 4233.0 11119.0 17572.0 17786.0 3065.0 10615.0 12011.0 9530.0 2140.0 9395.0 14177.0 10654.0 3159.0 8428.0 12322.0 10725.0 2201.0 19402.0 12701.0 6952.0 2025.0 12905.0 7333.0 7756.0 1971.0 10350.0 5758.0 5289.0 1227.0 7187.0 10833.0 8971.0 1952.0 19728.0 47035.0 29170.0 55430.0 35017.0 31435.0 27827.0 45480.0 38939.0 24735.0 25508.0 36735.0 30256.0 28298.0 29122.0 36931.0 32530.0 -HG02016 158.0 44.0 73.0 85.0 90.0 48.0 54.0 68.0 58.0 31.0 35.0 51.0 66.0 25.0 33.0 49.0 290.0 193.0 184.0 510.0 169.0 166.0 243.0 475.0 150.0 95.0 113.0 183.0 215.0 188.0 178.0 573.0 83.0 66.0 51.0 94.0 51.0 63.0 55.0 113.0 39.0 43.0 37.0 85.0 70.0 29.0 29.0 80.0 136.0 156.0 32.0 79.0 92.0 84.0 29.0 73.0 97.0 81.0 51.0 56.0 99.0 80.0 28.0 116.0 130.0 60.0 22.0 127.0 54.0 71.0 15.0 110.0 64.0 47.0 6.0 68.0 88.0 105.0 24.0 207.0 404.0 259.0 513.0 287.0 316.0 261.0 498.0 339.0 208.0 244.0 386.0 271.0 231.0 226.0 339.0 265.0 -HG02017 18047.0 5660.0 8651.0 8734.0 9540.0 6217.0 7410.0 9155.0 5963.0 2313.0 4691.0 3787.0 9679.0 3136.0 4368.0 7983.0 28634.0 22924.0 20720.0 51771.0 18053.0 16598.0 22432.0 48269.0 16338.0 11740.0 13098.0 19077.0 23320.0 20268.0 18120.0 59170.0 10284.0 6668.0 5790.0 11285.0 5658.0 5469.0 6384.0 12405.0 5501.0 5348.0 4787.0 12176.0 9160.0 3960.0 4227.0 11097.0 17514.0 17759.0 3057.0 10589.0 11965.0 9483.0 2131.0 9371.0 14121.0 10618.0 3146.0 8385.0 12294.0 10695.0 2190.0 19326.0 12655.0 6932.0 2016.0 12870.0 7319.0 7710.0 1955.0 10303.0 5741.0 5281.0 1228.0 7138.0 10808.0 8950.0 1937.0 19672.0 46855.0 29014.0 55217.0 34918.0 31271.0 27748.0 45287.0 38837.0 24619.0 25434.0 36524.0 30189.0 28184.0 29020.0 36789.0 32438.0 -HG02019 128.0 39.0 57.0 70.0 76.0 54.0 64.0 72.0 58.0 16.0 30.0 29.0 52.0 18.0 28.0 45.0 231.0 165.0 189.0 401.0 133.0 122.0 199.0 399.0 105.0 75.0 89.0 120.0 195.0 157.0 140.0 469.0 67.0 44.0 46.0 58.0 39.0 42.0 56.0 80.0 41.0 34.0 41.0 74.0 68.0 23.0 32.0 66.0 113.0 104.0 24.0 79.0 66.0 66.0 20.0 57.0 111.0 78.0 30.0 59.0 86.0 72.0 16.0 101.0 95.0 62.0 18.0 110.0 64.0 65.0 18.0 86.0 36.0 33.0 11.0 56.0 87.0 87.0 26.0 144.0 326.0 230.0 490.0 221.0 246.0 218.0 421.0 277.0 179.0 187.0 331.0 229.0 186.0 214.0 281.0 236.0 -HG02020 18058.0 5679.0 8665.0 8738.0 9561.0 6249.0 7444.0 9181.0 5954.0 2322.0 4699.0 3785.0 9693.0 3136.0 4376.0 7990.0 28679.0 22942.0 20738.0 51851.0 18085.0 16641.0 22506.0 48361.0 16362.0 11743.0 13118.0 19089.0 23381.0 20291.0 18165.0 59185.0 10299.0 6658.0 5804.0 11301.0 5663.0 5469.0 6397.0 12415.0 5489.0 5361.0 4791.0 12184.0 9181.0 3976.0 4231.0 11090.0 17533.0 17732.0 3053.0 10601.0 11992.0 9483.0 2137.0 9374.0 14129.0 10630.0 3150.0 8388.0 12316.0 10706.0 2199.0 19338.0 12646.0 6928.0 2008.0 12878.0 7324.0 7725.0 1971.0 10330.0 5759.0 5290.0 1221.0 7160.0 10816.0 8973.0 1944.0 19681.0 46909.0 29046.0 55314.0 34986.0 31353.0 27798.0 45381.0 38854.0 24635.0 25469.0 36609.0 30224.0 28221.0 29067.0 36865.0 32451.0 -HG02023 18084.0 5654.0 8663.0 8729.0 9564.0 6238.0 7418.0 9164.0 5955.0 2318.0 4687.0 3772.0 9693.0 3137.0 4362.0 8006.0 28663.0 22954.0 20729.0 51776.0 18051.0 16593.0 22445.0 48305.0 16354.0 11724.0 13123.0 19099.0 23376.0 20294.0 18133.0 59121.0 10285.0 6653.0 5794.0 11278.0 5668.0 5463.0 6395.0 12405.0 5505.0 5348.0 4786.0 12180.0 9146.0 3974.0 4220.0 11099.0 17540.0 17757.0 3058.0 10590.0 11978.0 9485.0 2142.0 9373.0 14132.0 10635.0 3142.0 8379.0 12301.0 10694.0 2199.0 19306.0 12636.0 6923.0 2020.0 12877.0 7314.0 7702.0 1970.0 10328.0 5734.0 5278.0 1228.0 7141.0 10784.0 8957.0 1938.0 19660.0 46885.0 29049.0 55321.0 34943.0 31293.0 27763.0 45313.0 38874.0 24641.0 25463.0 36591.0 30191.0 28215.0 29061.0 36791.0 32442.0 -HG02025 275.0 79.0 109.0 122.0 162.0 105.0 119.0 132.0 89.0 28.0 80.0 52.0 115.0 47.0 51.0 96.0 456.0 296.0 295.0 754.0 261.0 294.0 427.0 820.0 250.0 153.0 195.0 298.0 328.0 287.0 248.0 899.0 127.0 98.0 76.0 156.0 83.0 84.0 92.0 184.0 70.0 89.0 76.0 160.0 133.0 49.0 38.0 135.0 222.0 289.0 55.0 140.0 141.0 142.0 43.0 135.0 184.0 168.0 51.0 96.0 139.0 148.0 27.0 214.0 203.0 111.0 34.0 163.0 118.0 156.0 59.0 200.0 89.0 92.0 28.0 123.0 159.0 140.0 32.0 309.0 705.0 423.0 900.0 526.0 470.0 398.0 788.0 593.0 392.0 399.0 652.0 421.0 394.0 447.0 591.0 463.0 -HG02026 18152.0 5699.0 8731.0 8771.0 9610.0 6240.0 7460.0 9195.0 5997.0 2330.0 4726.0 3803.0 9743.0 3156.0 4389.0 8026.0 28801.0 23030.0 20820.0 52028.0 18147.0 16741.0 22583.0 48603.0 16402.0 11772.0 13168.0 19161.0 23483.0 20355.0 18234.0 59504.0 10352.0 6684.0 5833.0 11325.0 5680.0 5491.0 6434.0 12441.0 5516.0 5386.0 4817.0 12233.0 9212.0 3991.0 4237.0 11143.0 17596.0 17839.0 3084.0 10628.0 12038.0 9537.0 2157.0 9411.0 14202.0 10659.0 3164.0 8430.0 12340.0 10751.0 2205.0 19383.0 12714.0 6944.0 2028.0 12943.0 7347.0 7764.0 1977.0 10388.0 5761.0 5324.0 1234.0 7188.0 10864.0 8997.0 1950.0 19756.0 47091.0 29156.0 55555.0 35128.0 31422.0 27879.0 45536.0 39036.0 24761.0 25553.0 36776.0 30352.0 28351.0 29156.0 36985.0 32579.0 -HG02028 131.0 38.0 56.0 62.0 76.0 44.0 66.0 70.0 51.0 25.0 39.0 40.0 75.0 25.0 22.0 43.0 261.0 156.0 161.0 424.0 131.0 137.0 210.0 359.0 135.0 81.0 105.0 140.0 163.0 128.0 144.0 422.0 53.0 37.0 53.0 71.0 33.0 55.0 73.0 91.0 38.0 34.0 38.0 82.0 58.0 30.0 29.0 73.0 112.0 152.0 19.0 65.0 93.0 91.0 31.0 82.0 93.0 103.0 36.0 75.0 84.0 97.0 19.0 126.0 81.0 65.0 13.0 96.0 66.0 82.0 25.0 76.0 45.0 55.0 10.0 57.0 91.0 79.0 16.0 164.0 340.0 217.0 457.0 251.0 283.0 264.0 496.0 312.0 214.0 201.0 387.0 228.0 211.0 234.0 312.0 256.0 -HG02029 18087.0 5693.0 8700.0 8733.0 9558.0 6245.0 7446.0 9178.0 5971.0 2318.0 4698.0 3793.0 9706.0 3143.0 4375.0 7998.0 28689.0 22965.0 20762.0 51817.0 18071.0 16647.0 22490.0 48399.0 16388.0 11755.0 13153.0 19115.0 23402.0 20304.0 18167.0 59275.0 10295.0 6664.0 5807.0 11275.0 5671.0 5469.0 6399.0 12442.0 5513.0 5355.0 4786.0 12190.0 9181.0 3970.0 4228.0 11113.0 17549.0 17772.0 3057.0 10601.0 12005.0 9506.0 2142.0 9379.0 14185.0 10644.0 3145.0 8404.0 12316.0 10730.0 2202.0 19349.0 12676.0 6947.0 2030.0 12898.0 7318.0 7743.0 1959.0 10344.0 5751.0 5296.0 1227.0 7167.0 10813.0 8982.0 1943.0 19710.0 46941.0 29069.0 55346.0 34917.0 31368.0 27800.0 45448.0 38929.0 24704.0 25512.0 36684.0 30275.0 28276.0 29098.0 36895.0 32473.0 -HG02031 140.0 37.0 85.0 74.0 97.0 75.0 78.0 96.0 50.0 18.0 47.0 29.0 68.0 27.0 24.0 50.0 241.0 180.0 201.0 458.0 150.0 185.0 254.0 449.0 138.0 103.0 143.0 171.0 167.0 166.0 158.0 501.0 61.0 44.0 50.0 62.0 38.0 66.0 57.0 99.0 42.0 66.0 49.0 98.0 59.0 25.0 38.0 55.0 117.0 151.0 34.0 83.0 86.0 105.0 34.0 70.0 131.0 140.0 44.0 71.0 71.0 104.0 17.0 101.0 100.0 78.0 16.0 100.0 85.0 100.0 28.0 110.0 59.0 69.0 12.0 97.0 104.0 97.0 13.0 214.0 381.0 269.0 568.0 305.0 318.0 323.0 610.0 404.0 255.0 296.0 460.0 282.0 278.0 310.0 376.0 275.0 -HG02032 18082.0 5683.0 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61.0 46.0 61.0 82.0 51.0 14.0 33.0 32.0 69.0 19.0 25.0 47.0 219.0 147.0 166.0 377.0 114.0 121.0 177.0 368.0 111.0 81.0 75.0 141.0 189.0 136.0 135.0 410.0 57.0 38.0 33.0 66.0 54.0 30.0 53.0 77.0 42.0 36.0 38.0 67.0 61.0 27.0 32.0 80.0 81.0 110.0 25.0 63.0 68.0 60.0 22.0 59.0 88.0 64.0 31.0 39.0 70.0 75.0 14.0 93.0 99.0 61.0 20.0 79.0 51.0 66.0 19.0 93.0 47.0 55.0 17.0 52.0 82.0 65.0 16.0 170.0 316.0 161.0 374.0 253.0 257.0 222.0 376.0 270.0 159.0 177.0 299.0 163.0 205.0 209.0 266.0 225.0 -HG02155 139.0 36.0 66.0 54.0 75.0 48.0 64.0 83.0 67.0 22.0 42.0 31.0 41.0 29.0 24.0 38.0 189.0 170.0 143.0 384.0 152.0 143.0 231.0 391.0 117.0 91.0 86.0 137.0 187.0 141.0 131.0 410.0 75.0 40.0 38.0 50.0 50.0 49.0 35.0 85.0 39.0 34.0 41.0 81.0 48.0 18.0 42.0 67.0 114.0 128.0 22.0 69.0 69.0 93.0 24.0 77.0 85.0 94.0 30.0 62.0 73.0 77.0 20.0 123.0 93.0 50.0 12.0 92.0 57.0 80.0 24.0 96.0 50.0 54.0 14.0 76.0 80.0 95.0 24.0 172.0 321.0 221.0 464.0 234.0 283.0 234.0 488.0 305.0 200.0 210.0 356.0 254.0 193.0 253.0 316.0 259.0 -HG02156 102.0 28.0 72.0 52.0 67.0 50.0 66.0 64.0 36.0 15.0 39.0 35.0 50.0 22.0 25.0 46.0 189.0 153.0 124.0 335.0 128.0 117.0 186.0 340.0 102.0 69.0 106.0 104.0 144.0 124.0 98.0 328.0 57.0 38.0 21.0 45.0 36.0 38.0 51.0 59.0 31.0 30.0 28.0 64.0 49.0 23.0 29.0 49.0 76.0 102.0 17.0 73.0 62.0 62.0 19.0 61.0 89.0 76.0 25.0 44.0 68.0 61.0 14.0 86.0 61.0 56.0 11.0 81.0 37.0 73.0 20.0 80.0 42.0 46.0 13.0 54.0 72.0 79.0 18.0 121.0 274.0 173.0 396.0 198.0 192.0 204.0 431.0 277.0 164.0 187.0 333.0 180.0 168.0 195.0 290.0 166.0 -HG02164 108.0 41.0 57.0 45.0 90.0 70.0 57.0 93.0 51.0 18.0 41.0 32.0 44.0 24.0 27.0 50.0 181.0 142.0 175.0 343.0 146.0 145.0 231.0 402.0 115.0 91.0 103.0 139.0 146.0 148.0 136.0 418.0 60.0 40.0 39.0 64.0 35.0 36.0 45.0 96.0 39.0 29.0 43.0 67.0 57.0 32.0 22.0 55.0 105.0 128.0 27.0 54.0 64.0 92.0 20.0 62.0 85.0 109.0 25.0 57.0 57.0 91.0 14.0 119.0 90.0 61.0 25.0 104.0 73.0 101.0 35.0 117.0 40.0 65.0 12.0 54.0 84.0 82.0 20.0 158.0 319.0 224.0 456.0 232.0 263.0 263.0 496.0 321.0 177.0 215.0 388.0 232.0 204.0 239.0 339.0 219.0 -HG02165 138.0 43.0 64.0 44.0 90.0 61.0 78.0 82.0 51.0 13.0 47.0 30.0 61.0 21.0 37.0 45.0 224.0 188.0 184.0 407.0 136.0 140.0 226.0 415.0 113.0 109.0 106.0 154.0 190.0 149.0 148.0 414.0 61.0 35.0 43.0 74.0 37.0 46.0 53.0 105.0 36.0 39.0 33.0 84.0 58.0 27.0 19.0 73.0 102.0 131.0 30.0 81.0 77.0 85.0 25.0 71.0 107.0 101.0 37.0 50.0 79.0 91.0 15.0 118.0 90.0 67.0 18.0 86.0 65.0 83.0 19.0 95.0 44.0 74.0 11.0 68.0 89.0 89.0 19.0 176.0 343.0 228.0 437.0 240.0 265.0 266.0 463.0 357.0 198.0 208.0 385.0 223.0 207.0 242.0 320.0 225.0 -HG02166 118.0 23.0 72.0 75.0 79.0 52.0 69.0 74.0 51.0 26.0 42.0 30.0 70.0 22.0 25.0 45.0 229.0 167.0 189.0 393.0 136.0 186.0 220.0 398.0 118.0 104.0 128.0 150.0 176.0 130.0 139.0 448.0 67.0 41.0 38.0 63.0 41.0 60.0 42.0 95.0 35.0 31.0 44.0 97.0 63.0 31.0 31.0 64.0 95.0 140.0 29.0 59.0 80.0 90.0 21.0 77.0 85.0 104.0 37.0 62.0 89.0 90.0 24.0 120.0 83.0 71.0 21.0 104.0 69.0 85.0 25.0 104.0 63.0 47.0 18.0 79.0 90.0 94.0 13.0 195.0 345.0 231.0 479.0 275.0 289.0 255.0 514.0 364.0 230.0 213.0 377.0 250.0 203.0 207.0 338.0 239.0 -HG02178 127.0 31.0 65.0 58.0 84.0 49.0 72.0 63.0 48.0 15.0 40.0 23.0 61.0 26.0 35.0 43.0 225.0 186.0 160.0 356.0 162.0 145.0 232.0 391.0 103.0 88.0 103.0 128.0 176.0 157.0 147.0 420.0 64.0 42.0 29.0 63.0 41.0 54.0 70.0 98.0 41.0 29.0 46.0 73.0 48.0 31.0 24.0 53.0 100.0 141.0 31.0 61.0 65.0 94.0 26.0 71.0 92.0 101.0 41.0 71.0 88.0 85.0 20.0 92.0 91.0 62.0 20.0 106.0 78.0 97.0 24.0 99.0 62.0 60.0 11.0 69.0 77.0 68.0 26.0 172.0 359.0 244.0 478.0 245.0 257.0 274.0 512.0 299.0 178.0 222.0 399.0 243.0 219.0 256.0 351.0 232.0 -HG02179 107.0 22.0 58.0 50.0 64.0 38.0 44.0 71.0 58.0 8.0 34.0 22.0 53.0 29.0 20.0 45.0 209.0 171.0 166.0 387.0 132.0 128.0 152.0 362.0 96.0 72.0 84.0 118.0 163.0 111.0 118.0 440.0 71.0 30.0 31.0 55.0 30.0 30.0 44.0 83.0 27.0 36.0 39.0 80.0 48.0 17.0 28.0 56.0 83.0 125.0 17.0 59.0 62.0 47.0 22.0 59.0 81.0 84.0 26.0 44.0 70.0 69.0 17.0 84.0 88.0 53.0 21.0 98.0 65.0 59.0 22.0 89.0 39.0 55.0 16.0 58.0 77.0 58.0 16.0 148.0 317.0 181.0 389.0 233.0 208.0 188.0 398.0 274.0 153.0 174.0 320.0 206.0 205.0 182.0 255.0 212.0 -HG02180 125.0 35.0 58.0 49.0 75.0 41.0 71.0 52.0 46.0 19.0 49.0 33.0 62.0 26.0 29.0 47.0 236.0 153.0 155.0 353.0 132.0 117.0 182.0 347.0 111.0 83.0 98.0 142.0 175.0 132.0 126.0 432.0 56.0 36.0 33.0 69.0 37.0 34.0 44.0 78.0 33.0 33.0 23.0 77.0 42.0 22.0 31.0 75.0 92.0 133.0 26.0 70.0 79.0 69.0 15.0 55.0 79.0 87.0 25.0 58.0 65.0 70.0 17.0 107.0 93.0 63.0 14.0 93.0 57.0 66.0 17.0 100.0 39.0 47.0 11.0 63.0 77.0 79.0 14.0 144.0 318.0 202.0 450.0 226.0 238.0 220.0 417.0 281.0 181.0 176.0 308.0 196.0 189.0 201.0 263.0 232.0 -HG02181 117.0 42.0 67.0 77.0 82.0 51.0 75.0 80.0 66.0 14.0 42.0 34.0 65.0 24.0 34.0 43.0 264.0 153.0 171.0 442.0 161.0 161.0 251.0 439.0 118.0 90.0 111.0 163.0 170.0 151.0 150.0 470.0 79.0 53.0 25.0 62.0 42.0 48.0 54.0 104.0 41.0 46.0 51.0 91.0 82.0 20.0 31.0 71.0 107.0 152.0 37.0 76.0 71.0 72.0 39.0 61.0 106.0 101.0 35.0 73.0 82.0 89.0 15.0 120.0 104.0 59.0 18.0 116.0 60.0 105.0 22.0 103.0 66.0 54.0 12.0 76.0 100.0 94.0 18.0 189.0 364.0 232.0 517.0 266.0 284.0 244.0 537.0 354.0 226.0 222.0 375.0 255.0 231.0 235.0 313.0 230.0 -HG02182 120.0 48.0 72.0 70.0 82.0 64.0 52.0 55.0 58.0 19.0 37.0 27.0 43.0 25.0 35.0 51.0 194.0 151.0 158.0 362.0 140.0 121.0 198.0 362.0 115.0 75.0 122.0 126.0 201.0 133.0 109.0 393.0 58.0 34.0 34.0 65.0 28.0 42.0 42.0 98.0 37.0 30.0 36.0 85.0 54.0 24.0 27.0 68.0 84.0 132.0 22.0 63.0 91.0 91.0 16.0 67.0 80.0 75.0 27.0 64.0 63.0 67.0 15.0 105.0 81.0 46.0 24.0 96.0 54.0 83.0 27.0 85.0 33.0 43.0 7.0 55.0 78.0 81.0 14.0 134.0 308.0 196.0 399.0 220.0 230.0 211.0 404.0 264.0 143.0 211.0 324.0 203.0 189.0 202.0 278.0 203.0 -HG02184 156.0 56.0 92.0 78.0 74.0 59.0 68.0 74.0 49.0 27.0 51.0 41.0 90.0 31.0 46.0 58.0 256.0 139.0 201.0 365.0 160.0 144.0 205.0 375.0 118.0 80.0 113.0 163.0 190.0 152.0 135.0 432.0 73.0 39.0 39.0 100.0 50.0 52.0 66.0 108.0 36.0 33.0 51.0 79.0 69.0 24.0 35.0 65.0 113.0 117.0 25.0 73.0 93.0 81.0 24.0 85.0 113.0 108.0 35.0 50.0 87.0 83.0 26.0 140.0 105.0 48.0 23.0 86.0 77.0 76.0 25.0 85.0 50.0 47.0 21.0 59.0 71.0 89.0 26.0 145.0 325.0 220.0 441.0 239.0 268.0 226.0 498.0 322.0 193.0 210.0 360.0 203.0 200.0 222.0 340.0 253.0 -HG02185 128.0 29.0 52.0 59.0 87.0 63.0 70.0 68.0 34.0 19.0 41.0 38.0 52.0 25.0 26.0 50.0 230.0 176.0 182.0 374.0 152.0 150.0 232.0 398.0 123.0 98.0 97.0 142.0 157.0 127.0 131.0 421.0 65.0 45.0 43.0 61.0 37.0 36.0 49.0 76.0 28.0 34.0 40.0 81.0 54.0 25.0 25.0 62.0 95.0 108.0 21.0 61.0 61.0 62.0 19.0 66.0 86.0 95.0 28.0 58.0 71.0 76.0 15.0 106.0 76.0 64.0 13.0 95.0 54.0 86.0 20.0 110.0 52.0 56.0 11.0 64.0 80.0 98.0 18.0 154.0 325.0 236.0 476.0 261.0 235.0 257.0 423.0 309.0 188.0 234.0 320.0 226.0 229.0 232.0 324.0 212.0 -HG02186 117.0 35.0 79.0 74.0 74.0 43.0 75.0 73.0 31.0 18.0 57.0 29.0 64.0 33.0 30.0 48.0 233.0 150.0 164.0 345.0 133.0 131.0 208.0 410.0 128.0 88.0 98.0 136.0 194.0 151.0 136.0 446.0 49.0 29.0 50.0 71.0 45.0 35.0 51.0 93.0 37.0 44.0 41.0 71.0 57.0 24.0 21.0 65.0 122.0 145.0 19.0 65.0 78.0 88.0 12.0 76.0 86.0 95.0 38.0 71.0 100.0 87.0 14.0 114.0 100.0 54.0 12.0 91.0 56.0 69.0 26.0 109.0 44.0 55.0 11.0 66.0 82.0 83.0 18.0 172.0 335.0 237.0 463.0 259.0 252.0 238.0 472.0 313.0 178.0 234.0 352.0 235.0 226.0 259.0 302.0 225.0 -HG02187 102.0 23.0 46.0 38.0 78.0 49.0 76.0 67.0 38.0 13.0 31.0 21.0 47.0 23.0 26.0 40.0 194.0 145.0 149.0 334.0 130.0 126.0 151.0 318.0 85.0 75.0 95.0 115.0 139.0 147.0 105.0 389.0 59.0 31.0 34.0 45.0 34.0 35.0 56.0 75.0 30.0 31.0 34.0 68.0 44.0 23.0 24.0 52.0 104.0 106.0 24.0 66.0 43.0 66.0 22.0 61.0 81.0 68.0 30.0 47.0 71.0 74.0 14.0 78.0 77.0 46.0 8.0 75.0 60.0 65.0 22.0 104.0 44.0 55.0 14.0 65.0 77.0 72.0 25.0 155.0 274.0 216.0 401.0 223.0 247.0 204.0 435.0 264.0 174.0 200.0 307.0 182.0 160.0 181.0 269.0 182.0 -HG02188 95.0 33.0 52.0 45.0 64.0 41.0 36.0 49.0 31.0 13.0 26.0 23.0 29.0 13.0 18.0 30.0 167.0 123.0 116.0 307.0 108.0 109.0 147.0 294.0 82.0 57.0 82.0 99.0 125.0 109.0 100.0 311.0 38.0 24.0 31.0 39.0 34.0 32.0 44.0 55.0 25.0 24.0 29.0 51.0 49.0 24.0 14.0 40.0 83.0 103.0 20.0 52.0 67.0 61.0 26.0 61.0 76.0 45.0 26.0 41.0 60.0 65.0 16.0 97.0 57.0 54.0 9.0 73.0 46.0 43.0 12.0 69.0 43.0 30.0 11.0 30.0 66.0 77.0 12.0 105.0 243.0 150.0 352.0 198.0 155.0 174.0 346.0 255.0 143.0 145.0 244.0 152.0 146.0 157.0 242.0 176.0 -HG02190 141.0 44.0 57.0 69.0 85.0 42.0 69.0 109.0 46.0 16.0 39.0 25.0 68.0 23.0 39.0 57.0 244.0 178.0 197.0 423.0 164.0 140.0 221.0 417.0 140.0 109.0 126.0 157.0 199.0 161.0 166.0 471.0 83.0 54.0 52.0 74.0 45.0 41.0 60.0 94.0 45.0 38.0 41.0 73.0 59.0 26.0 34.0 83.0 135.0 136.0 37.0 85.0 102.0 92.0 26.0 60.0 106.0 112.0 38.0 56.0 78.0 77.0 12.0 127.0 132.0 61.0 26.0 128.0 62.0 96.0 29.0 89.0 53.0 57.0 14.0 69.0 87.0 76.0 28.0 183.0 350.0 243.0 451.0 269.0 267.0 264.0 500.0 323.0 211.0 252.0 386.0 258.0 237.0 253.0 313.0 254.0 -HG02215 155.0 43.0 84.0 76.0 88.0 50.0 70.0 70.0 62.0 20.0 40.0 30.0 67.0 23.0 34.0 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698.0 114.0 50.0 53.0 106.0 48.0 62.0 99.0 149.0 59.0 54.0 52.0 134.0 99.0 38.0 35.0 96.0 171.0 179.0 32.0 92.0 135.0 113.0 29.0 81.0 157.0 145.0 44.0 86.0 130.0 125.0 27.0 210.0 150.0 91.0 17.0 155.0 92.0 100.0 31.0 138.0 71.0 89.0 20.0 106.0 120.0 130.0 42.0 242.0 518.0 380.0 759.0 417.0 395.0 379.0 703.0 462.0 286.0 353.0 498.0 363.0 346.0 384.0 471.0 405.0 -HG03947 157.0 46.0 85.0 95.0 94.0 71.0 93.0 97.0 83.0 27.0 57.0 59.0 93.0 20.0 34.0 59.0 321.0 235.0 214.0 622.0 220.0 186.0 304.0 619.0 172.0 88.0 168.0 205.0 298.0 216.0 210.0 690.0 118.0 57.0 65.0 106.0 57.0 62.0 61.0 134.0 55.0 48.0 49.0 117.0 91.0 38.0 34.0 108.0 143.0 174.0 44.0 90.0 124.0 121.0 27.0 102.0 139.0 111.0 43.0 80.0 128.0 107.0 24.0 197.0 142.0 66.0 20.0 159.0 87.0 102.0 34.0 131.0 76.0 85.0 21.0 82.0 114.0 104.0 24.0 231.0 537.0 345.0 620.0 415.0 362.0 344.0 636.0 431.0 282.0 310.0 476.0 320.0 332.0 367.0 447.0 365.0 -HG03949 153.0 45.0 107.0 80.0 84.0 58.0 69.0 89.0 74.0 28.0 59.0 37.0 77.0 32.0 33.0 74.0 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46.0 17.0 23.0 53.0 29.0 43.0 39.0 68.0 103.0 +1497-RMM-4006 127.0 150.0 32.0 75.0 81.0 82.0 22.0 76.0 130.0 95.0 30.0 84.0 100.0 67.0 16.0 117.0 116.0 56.0 15.0 106.0 60.0 54.0 20.0 96.0 35.0 59.0 11.0 56.0 89.0 77.0 21.0 137.0 361.0 212.0 499.0 246.0 222.0 216.0 470.0 245.0 227.0 268.0 374.0 222.0 240.0 223.0 375.0 237.0 73.0 87.0 96.0 64.0 31.0 52.0 64.0 37.0 31.0 30.0 42.0 43.0 73.0 40.0 49.0 72.0 424.0 149.0 413.0 375.0 155.0 125.0 211.0 144.0 136.0 91.0 155.0 162.0 183.0 119.0 133.0 212.0 36.0 32.0 83.0 65.0 32.0 32.0 53.0 45.0 26.0 29.0 64.0 41.0 50.0 51.0 73.0 118.0 +1497-RMM-4007 121.0 109.0 15.0 68.0 89.0 65.0 25.0 68.0 90.0 105.0 43.0 47.0 64.0 74.0 20.0 102.0 73.0 40.0 18.0 80.0 61.0 66.0 25.0 91.0 34.0 47.0 17.0 49.0 78.0 67.0 24.0 146.0 329.0 194.0 472.0 222.0 203.0 178.0 421.0 233.0 199.0 197.0 379.0 185.0 220.0 205.0 301.0 200.0 55.0 67.0 72.0 62.0 32.0 45.0 40.0 23.0 26.0 30.0 46.0 33.0 62.0 39.0 36.0 58.0 394.0 128.0 335.0 305.0 145.0 115.0 196.0 138.0 132.0 72.0 134.0 131.0 155.0 108.0 120.0 202.0 34.0 21.0 65.0 57.0 33.0 34.0 60.0 46.0 18.0 18.0 53.0 39.0 52.0 46.0 54.0 125.0 +1497-RMM-4008 134.0 102.0 22.0 78.0 89.0 82.0 21.0 77.0 109.0 106.0 37.0 66.0 106.0 78.0 22.0 107.0 92.0 53.0 17.0 87.0 48.0 56.0 23.0 79.0 38.0 44.0 11.0 55.0 78.0 75.0 16.0 133.0 319.0 182.0 434.0 216.0 219.0 189.0 431.0 237.0 200.0 244.0 371.0 233.0 199.0 196.0 271.0 194.0 42.0 45.0 67.0 78.0 36.0 31.0 44.0 36.0 39.0 38.0 35.0 32.0 53.0 26.0 37.0 71.0 376.0 115.0 353.0 320.0 117.0 109.0 190.0 184.0 103.0 79.0 109.0 133.0 156.0 106.0 152.0 205.0 50.0 22.0 60.0 49.0 28.0 37.0 59.0 41.0 17.0 12.0 44.0 31.0 60.0 42.0 62.0 105.0 +1497-RMM-4009 124.0 102.0 22.0 61.0 137.0 96.0 34.0 129.0 164.0 135.0 43.0 110.0 131.0 82.0 18.0 121.0 66.0 47.0 18.0 76.0 53.0 54.0 27.0 64.0 36.0 36.0 16.0 66.0 86.0 59.0 16.0 138.0 309.0 184.0 424.0 230.0 227.0 162.0 413.0 252.0 236.0 257.0 377.0 195.0 234.0 199.0 291.0 225.0 69.0 66.0 77.0 55.0 30.0 45.0 54.0 36.0 29.0 28.0 43.0 34.0 59.0 41.0 35.0 64.0 374.0 117.0 333.0 339.0 162.0 136.0 223.0 167.0 121.0 70.0 170.0 127.0 147.0 110.0 124.0 189.0 46.0 31.0 60.0 45.0 26.0 30.0 57.0 38.0 15.0 24.0 59.0 24.0 56.0 42.0 61.0 88.0 +1497-RMM-4010 104.0 108.0 19.0 68.0 94.0 92.0 17.0 70.0 107.0 104.0 41.0 70.0 102.0 85.0 23.0 121.0 105.0 50.0 19.0 87.0 56.0 65.0 21.0 97.0 44.0 40.0 16.0 47.0 68.0 79.0 14.0 143.0 380.0 204.0 455.0 227.0 236.0 185.0 430.0 241.0 211.0 261.0 355.0 218.0 220.0 232.0 319.0 218.0 64.0 61.0 90.0 59.0 25.0 38.0 58.0 40.0 27.0 42.0 48.0 26.0 67.0 38.0 33.0 57.0 418.0 128.0 349.0 300.0 127.0 120.0 187.0 151.0 125.0 75.0 111.0 125.0 158.0 104.0 112.0 181.0 33.0 30.0 73.0 43.0 18.0 37.0 47.0 59.0 22.0 22.0 54.0 45.0 54.0 47.0 70.0 106.0 +1497-RMM-4011 120.0 134.0 26.0 60.0 73.0 96.0 29.0 58.0 106.0 101.0 27.0 78.0 95.0 87.0 18.0 110.0 86.0 48.0 19.0 100.0 49.0 90.0 29.0 96.0 48.0 61.0 14.0 60.0 81.0 77.0 25.0 151.0 376.0 249.0 493.0 259.0 278.0 221.0 512.0 309.0 202.0 258.0 458.0 221.0 219.0 250.0 356.0 241.0 83.0 84.0 85.0 80.0 24.0 33.0 52.0 38.0 30.0 36.0 35.0 44.0 61.0 46.0 32.0 57.0 436.0 160.0 427.0 430.0 138.0 139.0 231.0 160.0 155.0 91.0 159.0 173.0 183.0 107.0 161.0 226.0 52.0 24.0 71.0 68.0 29.0 39.0 61.0 83.0 27.0 26.0 64.0 52.0 54.0 58.0 72.0 134.0 +1497-RMM-4012 127.0 134.0 27.0 73.0 68.0 56.0 21.0 61.0 79.0 82.0 25.0 54.0 106.0 64.0 14.0 124.0 104.0 61.0 20.0 83.0 50.0 67.0 26.0 114.0 39.0 52.0 9.0 60.0 86.0 94.0 19.0 150.0 353.0 205.0 481.0 233.0 231.0 192.0 439.0 247.0 188.0 188.0 361.0 196.0 200.0 174.0 298.0 197.0 60.0 84.0 71.0 56.0 23.0 33.0 56.0 32.0 30.0 37.0 32.0 43.0 68.0 34.0 42.0 68.0 456.0 115.0 415.0 364.0 140.0 91.0 240.0 137.0 128.0 62.0 137.0 144.0 172.0 119.0 130.0 206.0 46.0 26.0 57.0 52.0 25.0 42.0 60.0 66.0 31.0 29.0 56.0 34.0 68.0 46.0 76.0 104.0 From de1b1b6e8b4644d94d40a896a42b10cc11a00c08 Mon Sep 17 00:00:00 2001 From: Jedidiah Carlson Date: Mon, 11 Jun 2018 16:01:06 -0400 Subject: [PATCH 4/6] remove restriction on file name for single matrix in agg mode --- util.py | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/util.py b/util.py index c0c2cef..f0fb55d 100644 --- a/util.py +++ b/util.py @@ -513,11 +513,8 @@ def aggregateM(inputM, subtypes_dict): M_colnames = colnames + list(sorted(subtypes_dict.keys())) colrange = range(1,len(M_colnames)) - if inputM.lower().endswith('nmf_m_spectra.txt'): - samples = getSamples(inputM) - M = np.loadtxt(inputM, skiprows=1, usecols=colrange) - M = M.astype(np.float) - else: + if (inputM.lower().endswith('m_samples.txt') or + inputM.lower().endswith('m_regions.txt')): with open(inputM) as f: file_list = f.read().splitlines() @@ -548,6 +545,11 @@ def aggregateM(inputM, subtypes_dict): M = M_out.astype(np.float) + else: + samples = getSamples(inputM) + M = np.loadtxt(inputM, skiprows=1, usecols=colrange) + M = M.astype(np.float) + out = collections.namedtuple('Out', ['M', 'samples'])(M, samples) return out From 8bba0eadcb584a537ce0570260b67b9c79405254 Mon Sep 17 00:00:00 2001 From: Jedidiah Carlson Date: Mon, 11 Jun 2018 16:15:28 -0400 Subject: [PATCH 5/6] add interactive option to qc boxplots --- report_templates/R/stat_boxplots.Rmd | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/report_templates/R/stat_boxplots.Rmd b/report_templates/R/stat_boxplots.Rmd index 6f5f153..f28e5bd 100644 --- a/report_templates/R/stat_boxplots.Rmd +++ b/report_templates/R/stat_boxplots.Rmd @@ -17,12 +17,15 @@ if(exists("samples") & exists("svars")){ # figure showing that simple cutoffs for quality indicators would not easily # differentiate inliers vs. Doomsayer's flagged outliers - ggplot(sumdat, aes(x=group, y=val, group=group, fill=group))+ + p <- ggplot(sumdat, aes(x=group, y=val, group=group, fill=group))+ geom_boxplot()+ scale_fill_manual(values=c("gray30", group_col_vals))+ facet_wrap(~var, scales="free")+ theme_bw()+ theme(axis.text.x=element_text(angle=45, hjust=1)) + + sggplotly(p) + } else { sigs2 <- merge(sig_contribs, cluster_mems, by="ID", all.x=T) %>% mutate(outlier=ifelse(ID %in% outlier_IDs, T, F)) From 25f3a350edf5ce9b300f015c45a0387bcef76be4 Mon Sep 17 00:00:00 2001 From: Jedidiah Carlson Date: Mon, 11 Jun 2018 18:51:02 -0400 Subject: [PATCH 6/6] add ungrouped qc boxplots; rearrange diagnostic report code --- report_templates/R/stat_boxplots.Rmd | 36 ------------------- report_templates/R/stat_boxplots1.Rmd | 52 +++++++++++++++++++++++++++ report_templates/R/stat_boxplots2.Rmd | 28 +++++++++++++++ report_templates/diagnostics.Rmd | 11 +++--- 4 files changed, 84 insertions(+), 43 deletions(-) delete mode 100644 report_templates/R/stat_boxplots.Rmd create mode 100644 report_templates/R/stat_boxplots1.Rmd create mode 100644 report_templates/R/stat_boxplots2.Rmd diff --git a/report_templates/R/stat_boxplots.Rmd b/report_templates/R/stat_boxplots.Rmd deleted file mode 100644 index f28e5bd..0000000 --- a/report_templates/R/stat_boxplots.Rmd +++ /dev/null @@ -1,36 +0,0 @@ -```{r boxplots, message=FALSE, warning=FALSE, echo=FALSE, fig.height = 8, fig.width = 12, dpi=100, fig.align="center"} - -if(exists("samples") & exists("svars")){ - sigs2 <- merge(sig_contribs, samples, by="ID") %>% - mutate(outlier=ifelse(ID %in% outlier_IDs, T, F)) - - sigs2 <- merge(sigs2, cluster_mems, by="ID", all.x=T) - sigs2[is.na(sigs2$group),]$group <- "keep" - - sumdat <- sigs2 %>% - # filter(sig!=2) %>% - group_by(group) %>% - dplyr::select(c("ID","group",svars)) %>% - # filter(coverage < 15) %>% - gather(var, val, svars[1]:svars[length(svars)]) %>% - group_by(group, var) - - # figure showing that simple cutoffs for quality indicators would not easily - # differentiate inliers vs. Doomsayer's flagged outliers - p <- ggplot(sumdat, aes(x=group, y=val, group=group, fill=group))+ - geom_boxplot()+ - scale_fill_manual(values=c("gray30", group_col_vals))+ - facet_wrap(~var, scales="free")+ - theme_bw()+ - theme(axis.text.x=element_text(angle=45, hjust=1)) - - sggplotly(p) - -} else { - sigs2 <- merge(sig_contribs, cluster_mems, by="ID", all.x=T) %>% - mutate(outlier=ifelse(ID %in% outlier_IDs, T, F)) - sigs2[is.na(sigs2$group),]$group <- "keep" -} - - -``` \ No newline at end of file diff --git a/report_templates/R/stat_boxplots1.Rmd b/report_templates/R/stat_boxplots1.Rmd new file mode 100644 index 0000000..ebc6f29 --- /dev/null +++ b/report_templates/R/stat_boxplots1.Rmd @@ -0,0 +1,52 @@ +```{r boxplots1, results='asis', message=FALSE, warning=FALSE, echo=FALSE, fig.height = 8, fig.width = 12, dpi=100, fig.align="center"} + +if(exists("samples") & exists("svars")){ + + cat("## Outlier QC statistic boxplots \n") + + cat("### Plot description \n") + + cat("If the user has included a file of sample-level summary statistics with the --samplefile` option and has specified variables to analyze with the `--svars` option, this plot will show the distributions of those variables for the outliers compared to the inlier samples. \n \n") + + cat("### Interpreting this plot \n") + + cat("These boxplots tell us whether the outliers detected by *Doomsayer* show differences in other sample-level summary statistics. \n") + + sigs2 <- merge(sig_contribs, samples, by="ID") %>% + mutate(outlier=ifelse(ID %in% outlier_IDs, T, F)) + + sigs2 <- merge(sigs2, cluster_mems, by="ID", all.x=T) + sigs2[is.na(sigs2$group),]$group <- "keep" + + sumdat <- sigs2 %>% + # filter(sig!=2) %>% + group_by(group) %>% + dplyr::select(c("ID","group",svars)) %>% + # filter(coverage < 15) %>% + gather(var, val, svars[1]:svars[length(svars)]) %>% + group_by(group, var) + + # figure showing that simple cutoffs for quality indicators would not easily + # differentiate inliers vs. Doomsayer's flagged outliers + sumdat1 <- sumdat %>% + ungroup() %>% + mutate(group = gsub(" .*", "", group)) + + p1 <- ggplot(sumdat1, aes(x=group, y=val, group=group, fill=group))+ + geom_boxplot()+ + scale_fill_manual(values=c("gray30", "red"))+ + facet_wrap(~var, scales="free")+ + theme_bw()+ + theme(axis.text.x=element_text(angle=45, hjust=1), + axis.title.x=element_blank(), + legend.position="none") + + sggplotly(p1) + +} else { + sigs2 <- merge(sig_contribs, cluster_mems, by="ID", all.x=T) %>% + mutate(outlier=ifelse(ID %in% outlier_IDs, T, F)) + sigs2[is.na(sigs2$group),]$group <- "keep" +} + +``` \ No newline at end of file diff --git a/report_templates/R/stat_boxplots2.Rmd b/report_templates/R/stat_boxplots2.Rmd new file mode 100644 index 0000000..5d5b2aa --- /dev/null +++ b/report_templates/R/stat_boxplots2.Rmd @@ -0,0 +1,28 @@ +```{r boxplots2, results='asis', message=FALSE, warning=FALSE, echo=FALSE, fig.height = 8, fig.width = 12, dpi=100, fig.align="center"} + +if(exists("samples") & exists("svars")){ + + cat("### Plot description \n") + + cat("The plot below shows the distributions of user-specified QC variables for the inlier samples compared to the outlier samples grouped according to the cluster assignment shown in the [heatmap](#error_profile_heatmap) \n \n") + + cat("### Interpreting this plot \n") + + cat("These boxplots tell us whether **specific groups** of outliers detected by *Doomsayer* show differences in other sample-level summary statistics. \n") + + # figure showing that simple cutoffs for quality indicators would not easily + # differentiate inliers vs. Doomsayer's flagged outliers + p2 <- ggplot(sumdat, aes(x=group, y=val, group=group, fill=group))+ + geom_boxplot()+ + scale_fill_manual(values=c("gray30", group_col_vals))+ + facet_wrap(~var, scales="free")+ + theme_bw()+ + theme(axis.text.x=element_text(angle=45, hjust=1), + axis.title.x=element_blank(), + legend.position="none") + + sggplotly(p2) + +} + +``` \ No newline at end of file diff --git a/report_templates/diagnostics.Rmd b/report_templates/diagnostics.Rmd index dcb4016..91756cf 100644 --- a/report_templates/diagnostics.Rmd +++ b/report_templates/diagnostics.Rmd @@ -43,13 +43,10 @@ Note that a lack of obvious clustering patterns does not necessarily mean the fl ```{r child="R/heatmap.Rmd"} ``` -## Outlier QC statistic boxplots - -### Plot description - -If the user has included a file of sample-level summary statistics with the `--samplefile` option and has specified variables to analyze with the `--svars` option, this plot will show the distributions of those variables for the outliers in each cluster, compared to the inlier samples. +```{r child="R/stat_boxplots1.Rmd"} +``` -```{r child="R/stat_boxplots.Rmd"} +```{r child="R/stat_boxplots2.Rmd"} ``` ## Compare component distributions @@ -77,7 +74,7 @@ If you are using NMF decomposition and two or more components are perfectly corr ### Plot description -Each bar represents the fraction of observations contained within that K-mer subtype across all samples of a particular group. +Each bar represents the fraction of observations contained within that K-mer subtype across all samples of a particular group. Bars that are solid colors indicate the outliers in that group have a significantly higher or lower proportion of those SNVs compared to the inlier group (FDR-adjusted; Q-value < 0.05), whereas greyed-out bars indicate no significant difference. ```{r child="R/spectra.Rmd"} ```