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PhenoGenRESTR - R Package to access PhenoGen Data via REST API

Sections:

Functions

Example Usage

Example Function Calls

Rest API

We will continue to develop this. Initially this will primarily be a file with a set of functions. We will work to turn this into a package and submit it to a repository.

Check for updates frequently we will try to update along with new REST API functions.

As downloaded this will call the production REST API version (https://rest.phenogen.org).
Please use this for all analysis. You are welcome to use the development and test version, by changing the phenogenURL variable to (https://rest-test.phenogen.org), but please only use this for testing and please be aware the rate of calls allows is more limited.

New functions that haven't been deployed to production will appear in testing first and will be implemented in development branch first.


Currently supported functions

Data Sets

Markers

Utility Functions


Data Sets

getDatasetExpression()

getDatasetExpression( annotation ,level,tissue,version="",genomeVersion="",strainMeans=FALSE, help) - returns a dataframe containing the most recent expression data table matching the annotation["Ensembl","Reconstruction"], level=["Gene","Transcript"],and tissue["Brain","Liver","Heart","Kidney"]. If you specify any version or genomeVersion the version or most recent version matching those criteria will be selected. It will default to individual values, but by specifying strainMeans=TRUE you can get a dataFrame of strain means.

Example

brainGeneExpression=getDatasetExpression(annotation="Ensembl",level="Gene",tissue="Brain")

geneID ACI_1_batch11 ACI_2_batch10 ACI_3_batch8 BN_1_batch16 BN_2_batch17 BN_3_batch17 BNLx_1_batch3 ...
ENSRNOG00000000001 5.4926754 5.4582437 5.4799894 5.4593561 5.6670520 5.5736410 5.523891 ...
ENSRNOG00000000007 13.4155761 13.2379013 13.4139346 13.3752669 13.6202354 13.4379441 13.095286 ...
ENSRNOG00000000008 4.5838578 4.0120344 4.0284626 4.0093282 4.0500272 4.2187905 3.505616 ...
ENSRNOG00000000010 11.3641079 10.8430474 11.3009947 11.3939719 11.2973067 11.4022849 11.410452 ...
ENSRNOG00000000012 4.2356596 4.1371101 3.7849114 4.3626185 4.2039562 4.1742752 4.219597 ...
ENSRNOG00000000017 5.7874644 6.2132814 5.7661025 5.3906472 5.3842575 5.6754122 5.381001 ...

getDatasetExpressionTPM()

getDatasetExpressionTPM( annotation ,level,tissue,version="",genomeVersion="",strainMeans=FALSE, help) - returns a dataframe containing the most recent expression data table containing TPM values matching the annotation["Ensembl","Reconstruction"], level=["Gene","Transcript"],and tissue["Brain","Liver","Heart","Kidney"]. If you specify any version or genomeVersion the version or most recent version matching those criteria will be selected. It will default to individual values, but by specifying strainMeans=TRUE you can get a dataFrame of strain means.

Example

brainGeneExpressionTPM=getDatasetExpressionTPM(annotation="Ensembl",level="Gene",tissue="Brain")

geneID ACI_1_batch11 ACI_1_batch8 ACI_2_batch10 ACI_2_batch8 ACI_3_batch8 BN_1_batch16 BN_2_batch17 ...
ENSRNOG00000000001 0.06 0.00 0.08 0.07 0.09 0.07 0.21 ...
ENSRNOG00000000007 13.73 7.90 18.07 10.82 20.76 20.92 50.75 ...
ENSRNOG00000000008 0.27 0.00 0.12 0.22 0.09 0.05 0.11 ...
ENSRNOG00000000009 0.01 0.00 0.00 0.07 0.00 0.00 0.00 ...
ENSRNOG00000000010 1.64 2.17 1.02 0.91 1.48 6.53 14.14 ...
ENSRNOG00000000012 0.14 0.53 0.16 0.10 0.06 0.29 0.32 ...

getDatasets()

getDatasets( genomeVer, organism, panel, type, tissue, help) - returns a dataframe containing a list of datasets available. If you specify any parameters it will filter the list based on the parameters. (type must be either "totalRNA" or "smallRNA")

Example

phenoGenDatasets=getDatasets()

datasetID organism panel description created tissue SeqType GenomeVer
3 Mm ILS/ISS Whole Brain from ILS/ISS Parental Strains 2017-10-26 00:00:00 Whole Brain smallRNA mm10
4 Mm ILS/ISS Panel Whole Brain from ILS/ISS RI Panel 2017-10-30 00:00:00 Whole Brain smallRNA mm10
5 Rn HRDP HRDP v5 Whole Brain 45 Strains 2020-06-20 00:00:00 Whole Brain ribosome depleted totalRNA rn6
6 Rn HRDP HRDP v5 Liver 45 Strains 2020-06-20 00:00:00 Liver ribosome depleted totalRNA rn6
7 Rn HRDP HRDP v5 Kidney 28 Strains 2020-06-20 00:00:00 Kidney ribosome depleted totalRNA rn6
8 Rn HRDP HRDP v5 Heart BNLx/SHR 2021-08-07 00:00:00 Heart ribosome depleted totalRNA rn6

getDatasetResults()

getDatasetResults( datasetID, help ) - returns a list of results for the dataset.
Results reflect different types of data, transcriptome reconstruction, RSEM results on a specific version of the transcriptome. From the results you can request a list of files( getDatasetResultFiles() ).

Example

phenoGenDataset=getDatasetResults(datasetID=6)

resultID type genomeVersion hrdpVersion dateCreated
5 Quantification-RSEM - Ensembl rn6 5 2020-06-20 00:00:00
6 Transcriptome Reconstruction rn6 5 2020-06-20 00:00:00
7 Quantification-RSEM - Reconstruction rn6 5 2020-06-20 00:00:00

getDatasetResultFiles()

getDatasetResultFiles( datasetID, resultID, help ) - returns a list of files for the dataset/result specified. The results include the URL to download the file and can be given to getDatasetResultFile() to load the file into R.

Example

phenoGenDatasetFiles=getDatasetResultFiles(datasetID=6,resultID=7)

fileID uploadDate fileName URL checksum genomeVersion description annotation level strainMeans
15 2020-06-20 00:00:00 PhenoGen.HRDP.v5.totalRNA.Liver.gene.reconstruction.strainMeans.txt.gz https://phenogen.org/downloads/RNASeq/RSEM/PhenoGen.HRDP.v5.totalRNA.Liver.gene.reconstruction.strainMeans.txt.gz 339492503250921c1e12f062fd538598 rn6 NA Reconstruction Gene TRUE
16 2020-06-20 00:00:00 PhenoGen.HRDP.v5.totalRNA.Liver.transcript.reconstruction.strainMeans.txt.gz https://phenogen.org/downloads/RNASeq/RSEM/PhenoGen.HRDP.v5.totalRNA.Liver.transcript.reconstruction.strainMeans.txt.gz 8f2fa86774aed5602432ba20a898f116 rn6 NA Reconstruction Transcript TRUE
19 2020-06-20 00:00:00 PhenoGen.HRDP.v5.totalRNA.Liver.gene.reconstruction.txt.gz https://phenogen.org/downloads/RNASeq/RSEM/PhenoGen.HRDP.v5.totalRNA.Liver.gene.reconstruction.txt.gz e7f4a4ef7d3aa94db0323abcbf7bd1f1 rn6 NA Reconstruction Gene FALSE
20 2020-06-20 00:00:00 PhenoGen.HRDP.v5.totalRNA.Liver.transcript.reconstruction.txt.gz https://phenogen.org/downloads/RNASeq/RSEM/PhenoGen.HRDP.v5.totalRNA.Liver.transcript.reconstruction.txt.gz fad306dc42914bd071556b65f45f8eae rn6 NA Reconstruction Transcript FALSE

getDatasetResultFile()

getDatasetResultFile( URL ) - tries to read a table from the given file and return the dataframe. It does support gzipped files and unzipped files. Currently it assumes tab delimited for anything other than .csv. It will change the delimiter if the file ends in .csv.

Example

phenoGenData=getDatasetResultFile(URL="https://phenogen.org/downloads/RNASeq/RSEM/PhenoGen.HRDP.v5.totalRNA.Liver.gene.reconstruction.strainMeans.txt.gz")

ACI.SegHsd BNLx BXH10 BXH11 BXH12 BXH13 BXH2 BXH3 BXH5 BXH6 BXH8 BXH9 Cop.CrCrl DA F344.NCl F344.NHsd F344.Stm HXB1 HXB10 HXB13 HXB15 HXB17 HXB18 HXB2 HXB20 HXB21 HXB22 HXB23 HXB24 HXB25 HXB27 HXB29 HXB3 HXB31 HXB4 HXB5 HXB7 LE.Stm LEW.Crl LEW.SsNHsd SHR SHRSP SR SS WKY
PRN6.5G0000002 2.471885 2.843376 2.988058 2.008068 2.803343 3.226419 2.690378 2.929471 2.899790 2.443884 2.979799 3.013484 3.344496 3.232358 3.859046 3.642551 3.162583 2.990749 3.571474 3.218356 2.849306 3.283459 3.291732 2.895224 2.301590 2.735003 3.224193 3.818431 2.636773 2.314870 3.309808 2.427989 2.829324 4.047287 3.250463 2.388294 2.550821 2.800644 2.594503 2.753139 2.611620 3.154226 3.356459 2.359043 2.032995
PRN6.5G0000018 7.972751 7.988188 8.327635 7.483179 8.308570 8.493277 7.656435 8.034155 7.419229 7.744099 7.772140 7.879737 8.892710 8.674106 8.926560 8.524224 9.830253 7.921848 7.782879 8.230908 7.810042 7.817220 7.938246 7.742655 7.662234 7.349877 7.665480 8.443167 7.403185 7.390368 8.295641 7.716124 7.821002 8.286780 7.841284 8.102923 7.772143 8.351444 8.188147 8.261466 7.580521 8.472662 8.664102 9.273093 7.726402
PRN6.5G0000023 3.635240 3.919247 4.123028 3.633602 4.865721 4.749075 4.191927 3.862219 3.688691 4.015154 3.978780 4.069461 4.312069 4.604477 4.507873 3.462370 4.377501 4.080252 4.425630 4.695526 4.251516 4.135177 4.516254 3.947551 4.046057 3.536359 4.247595 4.381584 3.699361 3.071000 4.919601 4.383471 4.343141 4.698016 4.225777 4.241549 4.812240 4.069986 4.749160 3.400256 3.408126 3.401887 3.625541 5.008848 3.008453
...

getDatasetGTF()

getDatasetGTF( URL, splitIDColumn=FALSE, select="ALL" ) - can be used for GTF files instead of getDatasetResultFile() splitting the ID(9th) column or filtering for just exons or transcripts is desired.

The options can be used seperately or together.

  • splitIDColumn - indicates if the 9th column of additional annotations should be split into multiple columns. Currently this is limited to 2 columns Gene and Transcript.

  • select - can be used to filter rows to contain only: transcripts (select="TRANSCRIPTS") or exons (select="EXONS")

getDatasetSamples()

getDatasetSamples( datasetID, help ) - creates a table of sample details from the metadata of the dataset.

getDatasetPipelineDetails()

getDatasetPipelineDetails( datasetID, help ) - creates a table of pipelines used to process the data in the results. Each pipeline has steps associated with it that can be viewed that can include the programs used with versions, URL for the program, and even the command line used if provided.

getDatasetProtocolDetails()

getDatasetProtocolDetails( datasetID, help ) - creates a table of protocols used in the library preparation. Beyond title and description details are provided as a download. When available the URL will be provided to download the protocol used. Further detail not yet provided can include notes on individual samples.


Markers

getMarkerSets()

getMarkerSets( genomeVer="",organism="" ) - returns a dataFrame of MarkerSets available.If a genomeVer or organism is specified then it will return matching datasets.

Example

phenoGenMarkerSets=getMarkerSets()

download_group_id display_name organism genome_version panel description type
1 HRDPv6 Markers Rat rn7.2 HRDP HRDP v6 markers from strain sequencing variant calls Marker
2 HRDPv4 Markers Rat rn6 HRDP STAR Consortium Genotype Arrays ( http://oct2012.archive.ensembl.org/Rattus_norvegicus/Info/Content?file=star.html ) Marker
3 HXB/BXH Markers Rat rn5 HXB/BXH STAR Consortium Genotype Arrays ( http://oct2012.archive.ensembl.org/Rattus_norvegicus/Info/Content?file=star.html ) Marker
4 BXD Markers Mouse mm9 BXD Wellcome-CTC Mouse Strain SNP Genotype Set Marker
5 LXS Markers Mouse mm10 LXS Affymetrix Mouse Diversity SNP Array Marker

getMarkerFiles()

getMarkerFiles( markerSetID, help )- returns a dataFram with a list of marker set files available.

Example

phenoGenMarkerFiles=getMarkerFiles(markerSetID=1)

download_file_id marker_set_id description filename checksum URL
1 1 HRDPv6 Marker Genotypes HRDP.v6.rn7.genotypes.2023-01-17.txt.gz 110da4cb07901b7e8fcec0778d89a141 https://phenogen.org/web/sysbio/downloadLink.jsp?url=/downloads/Markers/HRDP.v6.rn7.genotypes.2023-01-17.txt.gz
2 1 HRDPv6 Marker Positions HRDP.v6.rn7.positions.2023-01-17.txt.gz 22e76bcdb6a8b4aa6cf75ea73f969bd1 https://phenogen.org/web/sysbio/downloadLink.jsp?url=/downloads/Markers/HRDP.v6.rn7.positions.2023-01-17.txt.gz

getMarkerFile()

getMarkerFile( URL, help ) - returns a dataFrame with the marker set file contents.

Example

phenogenMarkerData=getMarkerFile(URL="https://phenogen.org/web/sysbio/downloadLink.jsp?url=/downloads/Markers/HRDP.v6.rn7.genotypes.2023-01-17.txt.gz")

BN.Lx_Cub_mRatNor1 BXH10_mRatNor1 BXH11_mRatNor1 BXH12_mRatNor1 BXH13_mRatNor1 BXH2_mRatNor1 BXH3_mRatNor1 BXH5_mRatNor1 BXH6_mRatNor1 BXH8_mRatNor1 BXH9_mRatNor1 HXB1_mRatNor1 HXB10_mRatNor1 HXB13_mRatNor1 HXB15_mRatNor1 HXB17_mRatNor1 HXB18_mRatNor1 HXB2_mRatNor1 HXB20_mRatNor1 HXB21_mRatNor1 HXB22_mRatNor1 HXB23_mRatNor1 HXB24_mRatNor1 HXB25_mRatNor1 HXB27_mRatNor1 HXB29_mRatNor1 HXB3_mRatNor1 HXB31_mRatNor1 HXB4_mRatNor1 HXB5_mRatNor1 HXB7_mRatNor1 SHR_OlaIpcv_mRatNor1 ACI_EurMcwi_2019NOV BN_NHsdMcwi_2019 BUF_N_2020 DA_OlaHsd_2019NOV F344_NCrl_2019NOV F344_NHsd_2021 F344_Stm_2019 FHH_EurMcwi_2019NOV FXLE12_Stm_2019NOV FXLE13_Stm_2019NOV FXLE14_Stm_2019NOV FXLE15_Stm_2019NOV FXLE16_Stm_2019 FXLE17_Stm_2019NOV FXLE18_Stm_2019 FXLE20_Stm_2019NOV GK_FarMcwi_2019NOV LE_Stm_2019 LEW_Crl_2019 LXF10A_StmMcwi_2020 LEXF11_Stm_2020 LEXF1A_Stm_2019 LEXF1C_Stm_2019 LEXF2B_Stm_2019 LEXF3_Stm_2020 LEXF4_Stm_2020 LEXF5_Stm_2019NOV LEXF6B_Stm_2019NOV LEXF6B_Stm_2021_A LEXF6B_Stm_2021_BH LEXF6B_Stm_2021_FH LEXF7A_Stm_2019NOV LEXF8A_Stm_2021 LH_MavRrrcAek_2020 LL_MavRrrcAek_2020 LN_MavRrrcAek_2020 M520_N_2020 MR_N_2020 MWF_Hsd_2019NOV PVG_Seac_2019 RCS_LavRrrc_2021 SHR_NCrl_2021 SHRSP_A3NCrl_2019NOV SR_JrHsd_2020 SS_JrHsd_2021 WAG_RijCrl_2020 WKY_N_2020 WKY_NCrl_2019 WN_N_2020
chr1_16211 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 0 2 0 2 2 0 2 0 2 0 0 0 2 0 0 2 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
chr1_17226 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 0 2 0 2 2 0 2 0 2 0 0 0 2 0 0 2 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
chr1_17294 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 0 2 0 2 2 0 2 0 2 0 0 0 2 0 0 2 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Utility Functions

filterGTF()

filterGTF( gtfDataFrame, splitIDColumn=FALSE, select="ALL" ) - can be used on the dataFrame returned from getting a GTF. The options can be used seperately or together. splitIDColumn - indicates if the 9th column of additional annotations should be split into multiple columns. Currently this is limited to 2 columns Gene and Transcript. select - can be used to filter rows to contain only: transcripts (select="TRANSCRIPTS") or exons (select="EXONS")


Example Usage

Load a Data Set

Load a Marker Set


Load a Phenogen Data Set

1. Get a list of Datasets Available on PhenoGen

phenoGenDatasets=getDatasets()
View(phenoGenDatasets)
datasetID organism panel description created tissue SeqType GenomeVer
3 Mm ILS/ISS Whole Brain from ILS/ISS Parental Strains 2017-10-26 00:00:00 Whole Brain smallRNA mm10
4 Mm ILS/ISS Panel Whole Brain from ILS/ISS RI Panel 2017-10-30 00:00:00 Whole Brain smallRNA mm10
5 Rn HRDP HRDP v5 Whole Brain 45 Strains 2020-06-20 00:00:00 Whole Brain ribosome depleted totalRNA rn6
6 Rn HRDP HRDP v5 Liver 45 Strains 2020-06-20 00:00:00 Liver ribosome depleted totalRNA rn6
7 Rn HRDP HRDP v5 Kidney 28 Strains 2020-06-20 00:00:00 Kidney ribosome depleted totalRNA rn6
8 Rn HRDP HRDP v5 Heart BNLx/SHR 2021-08-07 00:00:00 Heart ribosome depleted totalRNA rn6

2. Find the datasetID of the dataset to use: datasetID = 5 - for HRDPv5 Whole Brain

3. Get a list of results for the selected dataset.

phenoGenDataset=getDatasetResults(datasetID=5)
View(phenoGenDataset)
resultID type genomeVersion hrdpVersion dateCreated
2 Quantification-RSEM - Ensembl rn6 5 2020-06-20 00:00:00
3 Transcriptome Reconstruction rn6 5 2020-06-20 00:00:00
4 Quantification-RSEM - Reconstruction rn6 5 2020-06-20 00:00:00

4. Find the resultID of the results that you would like to load typical options are typically Ensembl, RefSeq, or Reconstructed Transcriptomes: - resultID = 4 for Expression values of the reconstructed transcriptome.

5.

phenoGenDatasetResults=getDatasetResultFiles(datasetID=5,resultID=4)
View(phenoGenDatasetResults)
fileID uploadDate fileName URL checksum genomeVersion description annotation level strainMeans
6 2020-06-20 00:00:00 PhenoGen.HRDP.v5.totalRNA.Brain.gene.reconstruction.strainMeans.txt.gz https://phenogen.org/downloads/RNASeq/RSEM/PhenoGen.HRDP.v5.totalRNA.Brain.gene.reconstruction.strainMeans.txt.gz 14201681cbd5996dca0ad0c44562ea12 rn6 NA Reconstruction Gene TRUE
7 2020-06-20 00:00:00 PhenoGen.HRDP.v5.totalRNA.Brain.transcript.reconstruction.strainMeans.txt.gz https://phenogen.org/downloads/RNASeq/RSEM/PhenoGen.HRDP.v5.totalRNA.Brain.transcript.reconstruction.strainMeans.txt.gz b463a647ae9150eade8a1459a72fafc2 rn6 NA Reconstruction Transcript TRUE
10 2020-06-20 00:00:00 PhenoGen.HRDP.v5.totalRNA.Brain.gene.reconstruction.txt.gz https://phenogen.org/downloads/RNASeq/RSEM/PhenoGen.HRDP.v5.totalRNA.Brain.gene.reconstruction.txt.gz 142ecc3eb16b1d8adae60d6709948ba0 rn6 NA Reconstruction Gene FALSE
11 2020-06-20 00:00:00 PhenoGen.HRDP.v5.totalRNA.Brain.transcript.reconstruction.txt.gz https://phenogen.org/downloads/RNASeq/RSEM/PhenoGen.HRDP.v5.totalRNA.Brain.transcript.reconstruction.txt.gz c238dcb839fdae5acb384eef9c430592 rn6 NA Reconstruction Transcript FALSE

6. Copy the URL of the file you would like to load. Options usually include gene level or transcript level quantification and individual samples or strain means. - https://phenogen.org/downloads/RNASeq/RSEM/PhenoGen.HRDP.v5.totalRNA.Brain.gene.reconstruction.txt.gz for Gene Level individual samples on the reconstructed transcriptome.

7. Get the file and load the complete file as a dataframe.

BrainGeneReconstruction=getDatasetResultFile(URL="https://phenogen.org/downloads/RNASeq/RSEM/PhenoGen.HRDP.v5.totalRNA.Brain.gene.reconstruction.txt.gz")
View(BrainGeneReconstruction)
Cop.CrCrl_1_batch9 SS_2_batch8 SR_2_batch8 SR_1_batch8 SHRSP_3_batch8 LEW.Crl_3_batch8 F344.NCl_3_batch8 DA_3_batch8 Cop.CrCrl_3_batch8 ACI.SegHsd_3_batch8 HXB31_2_batch7 HXB29_2_batch7 BXH9_3_batch7 BXH8_4_batch7 BXH6_3_batch7 BXH5_2_batch7 BXH3_3_batch7 BXH2_2_batch7 BXH11_3_batch7 BXH10_3_batch7 SHR_3_batch6 HXB27_3_batch6 HXB25_3_batch6 HXB24_3_batch6 HXB24_2_batch6 HXB23_3_batch6 HXB23_2_batch6 HXB22_3_batch6 HXB22_2_batch6 HXB21_3_batch6 HXB21_2_batch6 HXB20_3_batch6 HXB20_2_batch6 HXB2_3_batch6 HXB18_3_batch6 HXB18_2_batch6 HXB17_3_batch6 HXB1_2_batch6 BXH13_3_batch6 BXH13_2_batch6 BXH12_3_batch6 HXB7_3_batch5 HXB5_3_batch5 HXB5_2_batch5 HXB4_3_batch5 HXB4_2_batch5 HXB3_3_batch5 HXB3_2_batch5 HXB15_3_batch5 HXB15_2_batch5 HXB13_3_batch5 HXB10_3_batch5 HXB10_2_batch5 HXB1_3_batch5 BXH9_2_batch3 BXH9_1_batch3 BXH8_1_batch3 BXH6_2_batch3 BXH6_1_batch3 BXH5_1_batch3 BXH3_2_batch3 BXH3_1_batch3 BXH13_1_batch3 BXH11_2_batch3 BXH11_1_batch3 BXH10_2_batch3 BXH10_1_batch3 BNLx_2_batch3 BNLx_1_batch3 HXB5_1_batch2 HXB4_1_batch2 HXB31_1_batch2 HXB3_1_batch2 HXB29_1_batch2 HXB24_1_batch2 HXB23_1_batch2 HXB22_1_batch2 HXB21_1_batch2 HXB20_1_batch2 HXB18_1_batch2 HXB15_1_batch2 HXB10_1_batch2 HXB1_1_batch2 BXH2_1_batch2 WKY_3_batch11 SS_3_batch11 SR_3_batch11 LEW.SsNHsd_3_batch11 LEW.SsNHsd_2_batch11 LEW.SsNHsd_1_batch11 F344.NHsd_3_batch11 F344.NHsd_2_batch11 F344.NHsd_1_batch11 SHR_2_batch1 HXB7_2_batch1 HXB7_1_batch1 HXB27_2_batch1 HXB27_1_batch1 HXB25_2_batch1 HXB25_1_batch1 HXB2_2_batch1 HXB2_1_batch1 HXB17_2_batch1 HXB17_1_batch1 HXB13_2_batch1 HXB13_1_batch1 BXH12_2_batch1 BXH12_1_batch1 SHRSP_1_batch10 LEW.Crl_1_batch10 F344.NCl_1_batch10 WKY_2_batch10 WKY_1_batch10 SS_1_batch11 SHRSP_2_batch10 LEW.Crl_2_batch10 F344.NCl_2_batch10 DA_2_batch10 DA_1_batch10 Cop.CrCrl_2_batch10 ACI.SegHsd_2_batch10 ACI.SegHsd_1_batch11 HXB31_3_batch10 HXB29_3_batch10 BXH8_3_batch10 BXH5_3_batch10 BXH2_3_batch10 LE.Stm_2_batch14 BNLx_3_batch4 LE.Stm_3_batch13 F344.Stm_3_batch13 F344.Stm_2_batch13 F344.Stm_1_batch13 SHR_1_batch6 LE.Stm_1_batch14
PRN6.5G0000001 0.9015041 1.553993 2.381352 3.366840 1.621525 2.402869 2.389743 2.055506 2.789524 2.293886 2.035591 2.222622 1.264247 2.5615389 2.1922113 1.562573 1.199578 2.451458 2.382375 1.8580741 2.288696 2.6892576 0.8037906 2.713053 2.1153541 2.311140 1.9314869 2.704566 2.697639 1.937302 1.4867697 1.699251 1.967207 1.962481 2.510098 2.722358 1.925923 1.2435934 1.7463353 1.572330 2.190645 1.8098031 2.573240 1.6961145 1.287931 1.617457 2.662602 2.123104 0.7756686 2.864624 1.205841 1.243438 2.1043013 1.7271936 1.825702 1.9956577 2.7604304 2.0195789 3.2621524 1.257348 1.296388 1.311475 1.612577 3.0601113 2.4119596 1.587462 1.887902 1.9853786 2.567103 2.4493267 1.545996 2.1581425 2.2556750 2.517924 2.284219 2.237009 2.778412 2.213422 3.783119 3.054111 2.5732229 2.811710 2.276169 1.870567 1.8336147 1.824086 1.737258 2.3545748 1.289635 2.854276 2.023936 1.290977 2.285456 2.475756 2.751226 2.146168 2.5544311 3.145615 1.592265 1.829779 2.180615 1.325851 0.8801269 2.3431665 2.338004 1.7629701 2.5046370 1.771640 2.864588 1.955266 2.3402916 2.679990 0.8390833 0.8620538 1.590967 2.607304 2.762839 2.0859088 2.420274 1.7054236 1.313353 1.290057 1.958429 1.963241 2.799207 2.3981490 2.524465 2.158394 2.5467742 2.405483 1.8499461 2.747930 1.548196 1.580560 3.184267
PRN6.5G0000002 4.5954611 4.590913 4.485530 5.185467 4.700294 4.214312 4.768959 4.657243 4.484925 4.088292 4.466700 3.933180 4.375247 4.4466475 3.3842843 4.088553 4.207381 4.567559 4.486802 4.3703531 4.265717 4.4979834 4.3902643 4.189746 4.2037329 4.353852 4.0866334 3.740454 4.128175 4.040205 4.2308143 4.362144 3.762126 4.277346 1.840842 3.573212 3.779802 4.2888660 3.8082694 3.501589 3.665834 4.3012751 3.743925 4.5077671 4.320372 4.048116 3.734434 4.512831 3.8069787 3.445512 4.591534 3.260750 4.5147919 4.4810237 4.506001 4.7509303 4.0866707 4.4005033 4.0101932 4.314301 4.611081 4.363652 4.040692 3.8958356 4.6485940 4.524782 4.254037 3.7097367 4.453297 3.8601061 3.801102 4.4805192 4.2243535 4.528530 4.076425 4.771581 3.737663 4.278753 1.964008 3.367746 4.0541765 4.719703 4.130910 4.110790 4.5990622 4.416181 3.925109 4.3133456 4.468875 4.050852 4.535176 4.679993 4.936068 4.767698 4.413069 4.504664 4.4381515 3.984339 4.398393 4.553390 4.130160 4.440855 4.3505861 3.5781595 5.450794 4.2818771 4.1727120 4.340343 4.659712 3.325563 4.4344559 3.751688 4.0235290 2.8982150 4.297711 4.173370 4.437450 4.3443649 4.179917 4.4770655 4.139544 3.817244 3.750947 3.681832 4.519668 3.4900481 4.432348 4.258772 3.9009047 4.217468 4.7358738 4.496875 4.230501 4.379841 4.145373
PRN6.5G0000003 1.4271851 1.579125 1.617124 2.094803 1.391773 1.634894 1.043924 1.366452 1.060712 2.708008 2.147084 2.721420 1.029104 1.6520845 2.5947245 1.588224 2.051738 1.770452 1.617969 0.6152209 1.409059 1.3190398 1.7295608 2.398055 0.5570825 0.995394 0.5515705 1.966052 1.783593 1.719163 0.5499458 2.357587 1.543104 2.323452 1.515368 1.273791 1.708155 1.0099135 0.5593437 1.807811 2.125097 2.4937162 2.629711 0.5341352 2.181431 1.387901 2.447314 1.732042 1.6790040 1.307649 1.735882 1.009769 2.3591144 0.5497403 1.348221 1.9516416 2.0799091 1.7988076 0.6083105 1.595660 1.856924 2.058692 1.383256 1.3800773 1.0576368 1.825094 1.401889 1.5594447 2.051381 1.3123192 1.777746 0.5761805 1.6417638 2.298888 1.075442 2.016431 1.380298 1.351208 2.221713 2.247345 1.5646468 1.663550 1.873219 2.333388 0.6030221 1.810047 1.517164 0.5953389 1.635799 2.096441 2.392712 1.379828 1.881795 1.695129 1.540888 2.080052 1.3878175 1.917657 2.009587 1.994150 1.009052 1.418752 1.0663993 2.1246021 0.588233 0.5676835 2.1492623 1.755749 1.921475 1.460038 2.1217973 2.041854 1.3328068 2.3068599 1.362693 0.643840 2.115537 2.4625374 1.538913 0.6701127 2.218834 0.616753 2.198903 1.539539 0.957446 0.5569069 2.054794 1.764562 0.9840184 1.849229 2.0161829 3.123833 2.366216 1.031403 1.669373

Load a Phenogen Marker Set

1. Get a list of Marker Sets available.

phenoGenMarkerSets=getMarkerSets()

marker_set_id display_name organism genome_version panel description type
1 HRDPv6 Markers Rat rn7.2 HRDP HRDP v6 markers from strain sequencing variant calls Marker
2 HRDPv4 Markers Rat rn6 HRDP STAR Consortium Genotype Arrays ( http://oct2012.archive.ensembl.org/Rattus_norvegicus/Info/Content?file=star.html ) Marker
3 HXB/BXH Markers Rat rn5 HXB/BXH STAR Consortium Genotype Arrays ( http://oct2012.archive.ensembl.org/Rattus_norvegicus/Info/Content?file=star.html ) Marker
4 BXD Markers Mouse mm9 BXD Wellcome-CTC Mouse Strain SNP Genotype Set Marker
5 LXS Markers Mouse mm10 LXS Affymetrix Mouse Diversity SNP Array Marker

2. Get a list of marker files linked to the selected marker set by providing the marker_set_id from step 1.

phenoGenMarkerFiles=getMarkerFiles(markerSetID=1)

download_file_id marker_set_id description filename checksum URL
1 1 HRDPv6 Marker Genotypes HRDP.v6.rn7.genotypes.2023-01-17.txt.gz 110da4cb07901b7e8fcec0778d89a141 https://phenogen.org/web/sysbio/downloadLink.jsp?url=/downloads/Markers/HRDP.v6.rn7.genotypes.2023-01-17.txt.gz
2 1 HRDPv6 Marker Positions HRDP.v6.rn7.positions.2023-01-17.txt.gz 22e76bcdb6a8b4aa6cf75ea73f969bd1 https://phenogen.org/web/sysbio/downloadLink.jsp?url=/downloads/Markers/HRDP.v6.rn7.positions.2023-01-17.txt.gz

3. Get a dataframe with the data from a selected file. Provide the URL from step 2 to specify the file to load.

phenogenMarkerData=getMarkerFile(URL="https://phenogen.org/web/sysbio/downloadLink.jsp?url=/downloads/Markers/HRDP.v6.rn7.genotypes.2023-01-17.txt.gz")

BN.Lx_Cub_mRatNor1 BXH10_mRatNor1 BXH11_mRatNor1 BXH12_mRatNor1 BXH13_mRatNor1 BXH2_mRatNor1 BXH3_mRatNor1 BXH5_mRatNor1 BXH6_mRatNor1 BXH8_mRatNor1 BXH9_mRatNor1 HXB1_mRatNor1 HXB10_mRatNor1 HXB13_mRatNor1 HXB15_mRatNor1 HXB17_mRatNor1 HXB18_mRatNor1 HXB2_mRatNor1 HXB20_mRatNor1 HXB21_mRatNor1 HXB22_mRatNor1 HXB23_mRatNor1 HXB24_mRatNor1 HXB25_mRatNor1 HXB27_mRatNor1 HXB29_mRatNor1 HXB3_mRatNor1 HXB31_mRatNor1 HXB4_mRatNor1 HXB5_mRatNor1 HXB7_mRatNor1 SHR_OlaIpcv_mRatNor1 ACI_EurMcwi_2019NOV BN_NHsdMcwi_2019 BUF_N_2020 DA_OlaHsd_2019NOV F344_NCrl_2019NOV F344_NHsd_2021 F344_Stm_2019 FHH_EurMcwi_2019NOV FXLE12_Stm_2019NOV FXLE13_Stm_2019NOV FXLE14_Stm_2019NOV FXLE15_Stm_2019NOV FXLE16_Stm_2019 FXLE17_Stm_2019NOV FXLE18_Stm_2019 FXLE20_Stm_2019NOV GK_FarMcwi_2019NOV LE_Stm_2019 LEW_Crl_2019 LXF10A_StmMcwi_2020 LEXF11_Stm_2020 LEXF1A_Stm_2019 LEXF1C_Stm_2019 LEXF2B_Stm_2019 LEXF3_Stm_2020 LEXF4_Stm_2020 LEXF5_Stm_2019NOV LEXF6B_Stm_2019NOV LEXF6B_Stm_2021_A LEXF6B_Stm_2021_BH LEXF6B_Stm_2021_FH LEXF7A_Stm_2019NOV LEXF8A_Stm_2021 LH_MavRrrcAek_2020 LL_MavRrrcAek_2020 LN_MavRrrcAek_2020 M520_N_2020 MR_N_2020 MWF_Hsd_2019NOV PVG_Seac_2019 RCS_LavRrrc_2021 SHR_NCrl_2021 SHRSP_A3NCrl_2019NOV SR_JrHsd_2020 SS_JrHsd_2021 WAG_RijCrl_2020 WKY_N_2020 WKY_NCrl_2019 WN_N_2020
chr1_16211 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 0 2 0 2 2 0 2 0 2 0 0 0 2 0 0 2 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
chr1_17226 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 0 2 0 2 2 0 2 0 2 0 0 0 2 0 0 2 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
chr1_17294 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 0 2 0 2 2 0 2 0 2 0 0 0 2 0 0 2 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

PhenoGen REST API

https://github.com/TabakoffLab/PhenoGenRESTAPI

API Documentation

https://rest-doc.phenogen.org - Documentation of current functions. Please note some may be under development. Future updates will seperate development and production documentation.

All functions should include help as a response if you call the function with this appended to the end ?help=Y. The response returns a JSON object with supported methods and then list of parameters and description of each parameter as well as a list of options if there is a defined list of values.