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NoRCE: Non-coding RNA Sets Cis Enrichment Tool

Non-coding RNA Sets Cis Enrichment Tool (NoRCE) performs cis enrichment analysis for a given set of ncRNAs. Enrichment is carried out by using the functional annotations of the coding genes located proximally to the input ncRNAs. NoRCE allows incorporating other biological information such as the topologically associating domain (TAD) regions, co-expression patterns, and miRNA target information. NoRCE repository includes several data files, such as cell line specific TAD regions, functional gene sets, and cancer expression data. Additionally, users can input custom data files. Results can be retrieved in a tabular format or viewed as graphs. NoRCE is currently available for the following species: human, mouse, rat, zebrafish, fruit fly, worm and yeast. NoRCE accepts gene lists and gene regions as an input.

Tutorial for how to run this package and example codes can be found at https://rpubs.com/golgun/649085

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norce's Issues

Issue with the installation and running

Hi,
I successfully installed NoRCE on 2 different systems, and tried running the example code. Each time I get the same error.
"Error in assembly(org_assembly) :
Install package TxDb.Hsapiens.UCSC.hg19.knownGene in order to use this function."
I have installed the TxDb.Hsapiens.UCSC.hg19.knownGene package and imported the library also, before running the example code. Still getting same error. Can you please help, what mistake I am doing?

Here is my session Info.
sessionInfo()
R version 4.0.3 (2020-10-10)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: Ubuntu 18.04.5 LTS

Matrix products: default
BLAS/LAPACK: /home/R-4/lib/libopenblasp-r0.3.12.so

locale:
[1] LC_CTYPE=en_IN.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_IN.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_IN.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] NoRCE_1.2.0

loaded via a namespace (and not attached):
[1] Rcpp_1.0.5
[2] lattice_0.20-41
[3] GO.db_3.12.1
[4] prettyunits_1.1.1
[5] Rsamtools_2.6.0
[6] Biostrings_2.58.0
[7] assertthat_0.2.1
[8] digest_0.6.27
[9] BiocFileCache_1.14.0
[10] plyr_1.8.6
[11] R6_2.5.0
[12] GenomeInfoDb_1.26.0
[13] stats4_4.0.3
[14] RSQLite_2.2.1
[15] ggplot2_3.3.2
[16] httr_1.4.2
[17] pillar_1.4.6
[18] zlibbioc_1.36.0
[19] rlang_0.4.8
[20] GenomicFeatures_1.42.1
[21] progress_1.2.2
[22] curl_4.3
[23] blob_1.2.1
[24] S4Vectors_0.28.0
[25] Matrix_1.2-18
[26] BiocParallel_1.24.1
[27] readr_1.4.0
[28] stringr_1.4.0
[29] igraph_1.2.6
[30] munsell_0.5.0
[31] RCurl_1.98-1.2
[32] bit_4.0.4
[33] biomaRt_2.46.0
[34] DelayedArray_0.16.0
[35] compiler_4.0.3
[36] rtracklayer_1.50.0
[37] pkgconfig_2.0.3
[38] askpass_1.1
[39] BiocGenerics_0.36.0
[40] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
[41] openssl_1.4.3
[42] tidyselect_1.1.0
[43] SummarizedExperiment_1.20.0
[44] tibble_3.0.4
[45] GenomeInfoDbData_1.2.4
[46] IRanges_2.24.0
[47] matrixStats_0.57.0
[48] XML_3.99-0.5
[49] crayon_1.3.4
[50] dplyr_1.0.2
[51] dbplyr_2.0.0
[52] GenomicAlignments_1.26.0
[53] bitops_1.0-6
[54] rappdirs_0.3.1
[55] grid_4.0.3
[56] gtable_0.3.0
[57] lifecycle_0.2.0
[58] DBI_1.1.0
[59] magrittr_1.5
[60] scales_1.1.1
[61] stringi_1.5.3
[62] reshape2_1.4.4
[63] XVector_0.30.0
[64] xml2_1.3.2
[65] ellipsis_0.3.1
[66] generics_0.1.0
[67] vctrs_0.3.4
[68] tools_4.0.3
[69] bit64_4.0.5
[70] Biobase_2.50.0
[71] glue_1.4.2
[72] purrr_0.3.4
[73] hms_0.5.3
[74] MatrixGenerics_1.2.0
[75] parallel_4.0.3
[76] colorspace_2.0-0
[77] AnnotationDbi_1.52.0
[78] GenomicRanges_1.42.0
[79] memoise_1.1.0

Use NoRCE on Total-RNAseq data from Control KO study

Hi

I have a dataset as follows: 2 Ctrl samples, 2 KO samples of isoform 1 of GeneA, and 2 KO samples of Isoform2 of GeneA.

KO of isoform1 results in a lot of lncRNA and other ncRNAs being differentially regulated as compared to KO of Isoform2.

Is it fine to use your tool on TotalRNAseq data? I wish to see which ncRNAs might be interesting to study further and use geneGOEnricher but I am confused as to whether I should only use the KO sample matrix when specifying the following inputs exp1 = mirna, exp2 = mrna? Also, should I supply raw counts or normalized counts?

Error in stop_if_wrong_length(what, ans_len)

I am using the BioConductor package and I keep getting the following error:

Error in stop_if_wrong_length(what, ans_len) :
'ranges' must have the length of the object to construct (1) or length 1

when I run the command:

geneGOEnricher(gene = my_ensembl_genes, genetype = "Ensembl_gene", org_assembly = "mm10", near = TRUE)

There is also a warning message:
'track' parameter is deprecated now you go by the 'table' instead
use ucscTables(genome, track) to retrieve the list of tables for a track

I managed to get results once but now I consistently get the error.

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