Package: noisyr 1.1.0

Ilias Moutsopoulos

noisyr: Noise Quantification in High Throughput Sequencing Output

Quantifies and removes technical noise from high-throughput sequencing data. Two approaches are used, one based on the count matrix, and one using the alignment BAM files directly. Contains several options for every step of the process, as well as tools to quality check and assess the stability of output.

Authors:Ilias Moutsopoulos [aut, cre], Irina Mohorianu [aut, ctb], Hajk-Georg Drost [ctb], Elze Lauzikaite [ctb]

noisyr_1.1.0.tar.gz
noisyr_1.1.0.zip(r-4.5)noisyr_1.1.0.zip(r-4.4)noisyr_1.1.0.zip(r-4.3)
noisyr_1.1.0.tgz(r-4.4-any)noisyr_1.1.0.tgz(r-4.3-any)
noisyr_1.1.0.tar.gz(r-4.5-noble)noisyr_1.1.0.tar.gz(r-4.4-noble)
noisyr_1.1.0.tgz(r-4.4-emscripten)noisyr_1.1.0.tgz(r-4.3-emscripten)
noisyr.pdf |noisyr.html✨
noisyr/json (API)

# Install 'noisyr' in R:
install.packages('noisyr', repos = c('https://core-bioinformatics.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/core-bioinformatics/noisyr/issues

On CRAN:

4.13 score 9 stars 1 packages 5 scripts 195 downloads 18 exports 69 dependencies

Last updated 3 years agofrom:0c4b3b1f13. Checks:ERROR: 2 WARNING: 5. Indexed: yes.

TargetResultDate
Doc / VignettesFAILNov 11 2024
R-4.5-winWARNINGNov 11 2024
R-4.5-linuxERRORNov 11 2024
R-4.4-winWARNINGNov 11 2024
R-4.4-macWARNINGNov 11 2024
R-4.3-winWARNINGNov 11 2024
R-4.3-macWARNINGOct 12 2024

Exports:calculate_expression_profilecalculate_expression_similarity_countscalculate_expression_similarity_transcriptcalculate_first_minimum_densitycalculate_noise_thresholdcalculate_noise_threshold_method_statisticscast_gtf_to_genescast_matrix_to_numericfilter_genes_transcriptget_methods_calculate_noise_thresholdget_methods_correlation_distancenoisyrnoisyr_countsnoisyr_transcriptoptimise_window_lengthplot_expression_similarityremove_noise_from_bamsremove_noise_from_matrix

Dependencies:askpassBHBiocGenericsBiocParallelBiostringsbitopsclicodetoolscolorspacecpp11crayoncurldoParalleldplyrfansifarverforeachformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegtablehttrIRangesisobanditeratorsjsonliteKernSmoothlabelinglambda.rlatticelifecyclemagrittrMASSMatrixmgcvmimemunsellnlmeopensslphilentropypillarpkgconfigpoormanpreprocessCoreR6RColorBrewerRcppRhtslibrlangRsamtoolsS4VectorsscalessnowsystibbletidyselectUCSC.utilsutf8vctrsviridisLitewithrXVectorzlibbioc

Readme and manuals

Help Manual

Help pageTopics
Calculate the expression profile of a genecalculate_expression_profile
Calcualate the expression levels and expression levels similarity matrices using the count matrixcalculate_expression_similarity_counts
Calcualte the distance matrices using the BAM filescalculate_expression_similarity_transcript
Function to find the first local minimum of the density of a vectorcalculate_first_minimum_density
Function to calculate the noise threshold for a given expression matrix and parameterscalculate_noise_threshold
Function to tabulate statistics for different methods of calculating the noise thresholdcalculate_noise_threshold_method_statistics
Function to extract exon names and positions from a gtf filecast_gtf_to_genes
Cast a matrix of any type to numericcast_matrix_to_numeric
Function to filter the gene table for the transcript approachfilter_genes_transcript
Show the methods for calculating a noise thresholdget_methods_calculate_noise_threshold
Show the methods for calculating correlation or distanceget_methods_correlation_distance
Run the noisyR pipelinenoisyr
Run the noisyR pipeline for the count matrix approachnoisyr_counts
Run the noisyR pipeline for the transcript approachnoisyr_transcript
Optimise the elements per window for the count matrix approachoptimise_window_length
Plot the similarity against expression levelsplot_expression_similarity
Function to remove the noisy reads from the BAM filesremove_noise_from_bams
Function to remove the noisy reads from the expression matrixremove_noise_from_matrix