This LaTeX package executes programming source codes (including all command line tools) from within LaTeX and embeds the output in the resulting .pdf file. Many programming languages can be easily used and any command-line executable can be invoked when preparing the .pdf file from a .tex file. It is however recommended to use this package in server-mode together with the Python talk2stat package. Currently, this server-mode supports Julia, MatLab, Python, and R.

This package contains: 1. A microarray gene expression dataset from a human breast cancer study. 2. A RNA-Seq gene expression dataset from a mouse study on IFNG knockout. 3. ID mapping tables between gene IDs and SBGN-ML file glyph IDs. 4. Percent of orthologs detected in other species of the genes in a pathway. Cutoffs of this percentage for defining if a pathway exists in another species. 5. XML text of SBGN-ML files for all pre-collected pathways.

The Structstrings package implements the widely used dot bracket annotation for storing base pairing information in structured RNA. Structstrings uses the infrastructure provided by the Biostrings package and derives the DotBracketString and related classes from the BString class. From these, base pair tables can be produced for in depth analysis. In addition, the loop indices of the base pairs can be retrieved as well. For better efficiency, information conversion is implemented in C, inspired to a large extend by the ViennaRNA package.

This package provides a resampling-based inference based on data resampling and permutation.

Features:

• Bootstrap resampling: ordinary or balanced with optional stratification

• Extended bootstrap resampling: also varies sample size

• Parametric resampling: Gaussian, Poisson, gamma, etc.)

• Jackknife estimates of bias and variance of any estimator

• Compute bootstrap confidence intervals (percentile or BCa) for any estimator

• Permutation-based variants of traditional statistical tests (USP test of independence and others)

• Tools for working with empirical distributions (CDF, quantile, etc.)

This package aligns LC-HRMS metabolomics datasets acquired from biologically similar specimens analyzed under similar, but not necessarily identical, conditions. Peak-picked and simply aligned metabolomics feature tables (consisting of m/z, rt, and per-sample abundance measurements, plus optional identifiers & adduct annotations) are accepted as input. The package outputs a combined table of feature pair alignments, organized into groups of similar m/z, and ranked by a similarity score. Input tables are assumed to be acquired using similar (but not necessarily identical) analytical methods.

This library is a collection of pseudo random number generators.

While Common Lisp does provide a RANDOM function, it does not allow the user to pass an explicit SEED, nor to portably exchange the random state between implementations. This can be a headache in cases like games, where a controlled seeding process can be very useful.

For both curiosity and convenience, this library offers multiple algorithms to generate random numbers, as well as a bunch of generally useful methods to produce desired ranges.

This is an R package for the imputation of left-censored data under a compositional approach. The implemented methods consider aspects of relevance for a compositional approach such as scale invariance, subcompositional coherence or preserving the multivariate relative structure of the data. Based on solid statistical frameworks, it comprises the ability to deal with single and varying censoring thresholds, consistent treatment of closed and non-closed data, exploratory tools, multiple imputation, Markov Chain Monte Carlo (MCMC), robust and non-parametric alternatives, and recent proposals for count data.

Precise measurements are important for epigenome-wide studies investigating DNA methylation in whole blood samples, where effect sizes are expected to be small in magnitude. The 450K platform is often affected by batch effects and proper preprocessing is recommended. This package provides functions to read and normalize 450K .idat files. The normalization corrects for dye bias and biases related to signal intensity and methylation of probes using local regression. No adjustment for probe type bias is performed to avoid the trade-off of precision for accuracy of beta-values.

Guile-Reader is a simple framework for building readers for GNU Guile.

The idea is to make it easy to build procedures that extend Guile’s read procedure. Readers supporting various syntax variants can easily be written, possibly by re-using existing “token readers” of a standard Scheme readers. For example, it is used to implement Skribilo’s R5RS-derived document syntax.

Guile-Reader’s approach is similar to Common Lisp’s “read table”, but hopefully more powerful and flexible (for instance, one may instantiate as many readers as needed).

DoubletFinder identifies doublets by generating artificial doublets from existing scRNA-seq data and defining which real cells preferentially co-localize with artificial doublets in gene expression space. Other DoubletFinder package functions are used for fitting DoubletFinder to different scRNA-seq datasets. For example, ideal DoubletFinder performance in real-world contexts requires optimal pK selection and homotypic doublet proportion estimation. pK selection is achieved using pN-pK parameter sweeps and maxima identification in mean-variance-normalized bimodality coefficient distributions. Homotypic doublet proportion estimation is achieved by finding the sum of squared cell annotation frequencies.

Noise Repellent is an LV2 plugin to reduce noise. It has the following features:

1. Spectral gating and spectral subtraction suppression rule

2. Adaptive and manual noise thresholds estimation

3. Adjustable noise floor

4. Adjustable offset of thresholds to perform over-subtraction

5. Time smoothing and a masking estimation to reduce artifacts

6. Basic onset detector to avoid transients suppression

7. Whitening of the noise floor to mask artifacts and to recover higher frequencies

8. Option to listen to the residual signal

9. Soft bypass

10. Noise profile saved with the session

When analyzing data, plots are a helpful tool for visualizing data and interpreting statistical models. This package provides a set of simple tools for building plots incrementally, starting with an empty plot region, and adding bars, data points, regression lines, error bars, gradient legends, density distributions in the margins, and even pictures. The package builds further on R graphics by simply combining functions and settings in order to reduce the amount of code to produce for the user. As a result, the package does not use formula input or special syntax, but can be used in combination with default R plot functions.

This package contains tools for exploring Hardy-Weinberg equilibrium for diallelic genetic marker data. All classical tests (chi-square, exact, likelihood-ratio and permutation tests) for Hardy-Weinberg equilibrium are included in the package, as well as functions for power computation and for the simulation of marker data under equilibrium and disequilibrium. Routines for dealing with markers on the X-chromosome are included. Functions for testing equilibrium in the presence of missing data by using multiple imputation are also provided. Implements several graphics for exploring the equilibrium status of a large set of diallelic markers: ternary plots with acceptance regions, log-ratio plots and Q-Q plots.

This package implements a method that aims to identify enhancers on large scale. The STARR-seq data consists of two sequencing datasets of the same targets in a specific genome. The input sequences show which regions where tested for enhancers. Significant enriched peaks i.e. a lot more sequences in one region than in the input where enhancers in the genomic DNA are, can be identified. So the approach pursued is to call peak every region in which there is a lot more (significant in a binomial model) STARR-seq signal than input signal and propose an enhancer at that very same position. Enhancers then are called weak or strong dependent of there degree of enrichment in comparison to input.

This package implements easy-to-use functions to generate 2-7 sets Venn plot in publication quality. ggVennDiagram plot Venn using well-defined geometry dataset and ggplot2. The shapes of 2-4 sets Venn use circles and ellipses, while the shapes of 4-7 sets Venn use irregular polygons (4 has both forms), which are developed and imported from another package venn. We provide internal functions to integrate shape data with user provided sets data, and calculated the geometry of every regions/intersections of them, then separately plot Venn in three components: set edges, set labels, and regions. From version 1.0, it is possible to customize these components as you demand in ordinary ggplot2 grammar.

Defines a major mode rjsx-mode based on js2-mode for editing JSX files. rjsx-mode extends the parser in js2-mode to support the full JSX syntax. This means you get all of the js2 features plus proper syntax checking and highlighting of JSX code blocks.

Some features that this mode adds to js2:

• Highlighting JSX tag names and attributes (using the rjsx-tag and rjsx-attr faces)

• Highlight undeclared JSX components

• Parsing the spread operator ...otherProps

• Parsing && and || in child expressions cond && <BigComponent/>

• Parsing ternary expressions toggle ? <ToggleOn /> : <ToggleOff />

Additionally, since rjsx-mode extends the js2 AST, utilities using the parse tree gain access to the JSX structure.

Efficient implementations for analyzing pre-clinical multiple drug combination datasets. It provides efficient implementations for 1.the popular synergy scoring models, including HSA, Loewe, Bliss, and ZIP to quantify the degree of drug combination synergy; 2. higher order drug combination data analysis and synergy landscape visualization for unlimited number of drugs in a combination; 3. statistical analysis of drug combination synergy and sensitivity with confidence intervals and p-values; 4. synergy barometer for harmonizing multiple synergy scoring methods to provide a consensus metric of synergy; 5. evaluation of synergy and sensitivity simultaneously to provide an unbiased interpretation of the clinical potential of the drug combinations. Based on this package, we also provide a web application (http://www.synergyfinder.org) for users who prefer graphical user interface.

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. This is a another exporter for org-mode that translates Org-mode file to beautiful PDF file EXAMPLE ORG FILE HEADER: #+title:Readme ox-notes #+author: Matthias David #+options: toc:nil #+ou:Zoom #+quand: 20/2/2021 #+projet: ox-minutes #+absent: C. Robert,T. tartanpion #+present: K. Soulet,I. Payet #+excuse:Sophie Fonsec,Karine Soulet #+logo: logo.png

Estimate a suite of normalizing transformations, including a new adaptation of a technique based on ranks which can guarantee normally distributed transformed data if there are no ties: ordered quantile normalization (ORQ). ORQ normalization combines a rank-mapping approach with a shifted logit approximation that allows the transformation to work on data outside the original domain. It is also able to handle new data within the original domain via linear interpolation. The package is built to estimate the best normalizing transformation for a vector consistently and accurately. It implements the Box-Cox transformation, the Yeo-Johnson transformation, three types of Lambert WxF transformations, and the ordered quantile normalization transformation. It estimates the normalization efficacy of other commonly used transformations, and it allows users to specify custom transformations or normalization statistics. Finally, functionality can be integrated into a machine learning workflow via recipes.

Free and open source fonts from Kreative Software:

Constructium is a fork of SIL Gentium designed specifically to support constructed scripts as encoded in the Under-ConScript Unicode Registry. It is ideal for mixed Latin, Greek, Cyrillic, IPA, and conlang text in web sites and documents.

Fairfax is a 6x12 bitmap font for terminals, text editors, IDEs, etc. It supports many scripts and a large number of Unicode blocks as well as constructed scripts as encoded in the Under-ConScript Unicode Registry, pseudographics and semigraphics, and tons of private use characters. It has been superceded by Fairfax HD but is still maintained.

Fairfax HD is a halfwidth scalable monospace font for terminals, text editors, IDEs, etc. It supports many scripts and a large number of Unicode blocks as well as constructed scripts as encoded in the Under-ConScript Unicode Registry, pseudographics and semigraphics, and tons of private use characters.

Kreative Square is a fullwidth scalable monospace font designed specifically to support pseudographics, semigraphics, and private use characters.

An experimentdata package to supplement the preciseTAD package containing pre-trained models and the variable importances of each genomic annotation used to build the model parsed into list objects and available in ExperimentHub. In total, preciseTADhub provides access to n=84 random forest classification models optimized to predict TAD/chromatin loop boundary regions and stored as .RDS files. The value, n, comes from the fact that we considered l=2 cell lines GM12878, K562, g=2 ground truth boundaries Arrowhead, Peakachu, and c=21 autosomal chromosomes CHR1, CHR2, ..., CHR22 (omitting CHR9). Furthermore, each object is itself a two-item list containing: (1) the model object, and (2) the variable importances for CTCF, RAD21, SMC3, and ZNF143 used to predict boundary regions. Each model is trained via a "holdout" strategy, in which data from chromosomes CHR1, CHR2, ..., CHRi-1, CHRi+1, ..., CHR22 were used to build the model and the ith chromosome was reserved for testing. See https://doi.org/10.1101/2020.09.03.282186 for more detail on the model building strategy.

ChunkyPNG is a pure Ruby library that can read and write Portable Network Graphics (PNG) images without depending on an external image library. It tries to be memory efficient and reasonably fast. It has features such as:

• Decoding support for any image that the PNG standard allows. This includes all standard color modes, all bit depths, all transparency, and interlacing and filtering options.

• Encoding support for images of all color modes (true color, grayscale, and indexed) and transparency for all these color modes. The best color mode is chosen automatically, based on the amount of used colors.

• Read/write access to the image's pixels.

• Read/write access to all image metadata that is stored in chunks.

• Memory efficiency: fixnum are used, i.e. 4 or 8 bytes of memory per pixel, depending on the hardware).

• Performance: ChunkyPNG is reasonably fast for Ruby standards, by only using integer math and a highly optimized saving routine.

• Interoperability with RMagick.

ChunkyPNG is vulnerable to decompression bombs and can run out of memory when loading a specifically crafted PNG file. This is hard to fix in pure Ruby. Deal with untrusted images in a separate process, e.g., by using fork or a background processing library.

Nonfree firmware for Realtek ethernet, wifi, and Bluetooth chips. This package contains nonfree firmware for the following chips:

• Realtek RTL8188EE firmware (rtlwifi/rtl8188efw.bin)

• Realtek RTL8188EU firmware (rtlwifi/rtl8188eufw.bin)

• Realtek RTL8192CE/RTL8188CE firmware (rtlwifi/rtl8192cfw.bin)

• Realtek RTL8192CE/RTL8188CE B-cut firmware (rtlwifi/rtl8192cfwU_B.bin)

• Realtek RTL8188CE A-cut firmware, version 4.816.2011 (rtlwifi/rtl8192cfwU.bin)

• Realtek RTL8192CU/RTL8188CU UMC A-cut firmware (rtlwifi/rtl8192cufw_A.bin)

• Realtek RTL8192CU/RTL8188CU UMC B-cut firmware (rtlwifi/rtl8192cufw_B.bin)

• Realtek RTL8192CU/RTL8188CU TMSC firmware (rtlwifi/rtl8192cufw_TMSC.bin)

• Realtek RTL8192CU/RTL8188CU fallback firmware (rtlwifi/rtl8192cufw.bin)

• Realtek RTL8192DE firmware (rtlwifi/rtl8192defw.bin)

• Realtek RTL8192EE wifi firmware (rtlwifi/rtl8192eefw.bin)

• Realtek RTL8192EU non-WoWLAN firmware (rtlwifi/rtl8192eu_nic.bin)

• Realtek RTL8192EU WoWLAN firmware (rtlwifi/rtl8192eu_wowlan.bin)

• Realtek RTL8192SE/RTL8191SE firmware, version 4.816.2011 (rtlwifi/rtl8192sefw.bin)

• Realtek RTL8192SU/RTL8712U firmware (rtlwifi/rtl8712u.bin)

• Realtek RTL8723AU rev A wifi-with-BT firmware (rtlwifi/rtl8723aufw_A.bin)

• Realtek RTL8723AU rev B wifi-with-BT firmware (rtlwifi/rtl8723aufw_B.bin)

• Realtek RTL8723AU rev B wifi-only firmware (rtlwifi/rtl8723aufw_B_NoBT.bin)

• Realtek RTL8723BE firmware, version 36 (rtlwifi/rtl8723befw_36.bin)

• Realtek RTL8723BE firmware (rtlwifi/rtl8723befw.bin)

• Realtek RTL8723BS BT firmware (rtlwifi/rtl8723bs_bt.bin)

• Realtek RTL8723BS wifi non-WoWLAN firmware (rtlwifi/rtl8723bs_nic.bin)

• Realtek RTL8723BS wifi WoWLAN firmware (rtlwifi/rtl8723bs_wowlan.bin)

• Realtek RTL8723BU non-WoWLAN firmware (rtlwifi/rtl8723bu_nic.bin)

• Realtek RTL8723BU WoWLAN firmware (rtlwifi/rtl8723bu_wowlan.bin)

• Realtek RTL8723DE firmware (rtlwifi/rtl8723defw.bin)

• Realtek RTL8723AE rev B firmware (rtlwifi/rtl8723fw_B.bin)

• Realtek RTL8723AE rev A firmware (rtlwifi/rtl8723fw.bin)

• Realtek RTL8821AE firmware, version 29 (rtlwifi/rtl8821aefw_29.bin)

• Realtek RTL8821AE firmware (rtlwifi/rtl8821aefw_wowlan.bin)

• Realtek RTL8821AE firmware (rtlwifi/rtl8821aefw.bin)

• Realtek RTL8822BE firmware (rtlwifi/rtl8822befw.bin)

• Realtek RTL8105E-1 firmware (rtl_nic/rtl8105e-1.fw)

• Realtek RTL8106E-1 firmware, version 0.0.1 (rtl_nic/rtl8106e-1.fw)

• Realtek RTL8106E-2 firmware, version 0.0.1 (rtl_nic/rtl8106e-2.fw)

• Realtek RTL8107E-1 firmware, version 0.0.2 (rtl_nic/rtl8107e-1.fw)

• Realtek RTL8107E-2 firmware, version 0.0.2 (rtl_nic/rtl8107e-2.fw)

• Realtek RTL8111D-1/RTL8168D-1 firmware (rtl_nic/rtl8168d-1.fw)

• Realtek RTL8111D-2/RTL8168D-2 firmware (rtl_nic/rtl8168d-2.fw)

• Realtek RTL8168E-1 firmware (rtl_nic/rtl8168e-1.fw)

• Realtek RTL8168E-2 firmware (rtl_nic/rtl8168e-2.fw)

• Realtek RTL8168E-3 firmware, version 0.0.4 (rtl_nic/rtl8168e-3.fw)

• Realtek RTL8168F-1 firmware, version 0.0.5 (rtl_nic/rtl8168f-1.fw)

• Realtek RTL8168F-2 firmware, version 0.0.4 (rtl_nic/rtl8168f-2.fw)

• Realtek RTL8168G-1 firmware, version 0.0.3 (rtl_nic/rtl8168g-1.fw)

• Realtek RTL8168G-2 firmware, version 0.0.1 (rtl_nic/rtl8168g-2.fw)

• Realtek RTL8168G-3 firmware, version 0.0.1 (rtl_nic/rtl8168g-3.fw)

• Realtek RTL8168H-1 firmware, version 0.0.2 (rtl_nic/rtl8168h-1.fw)

• Realtek RTL8168H-2 firmware, version 0.0.2 (rtl_nic/rtl8168h-2.fw)

• Realtek RTL8402-1 firmware, version 0.0.1 (rtl_nic/rtl8402-1.fw)

• Realtek RTL8411-1 firmware, version 0.0.3 (rtl_nic/rtl8411-1.fw)

• Realtek RTL8411-2 firmware, version 0.0.1 (rtl_nic/rtl8411-2.fw)

• Realtek RTL8192EE Bluetooth firmware (rtl_bt/rtl8192ee_fw.bin)

• Realtek RTL8812AE Bluetooth firmware (rtl_bt/rtl8812ae_fw.bin)

• Realtek RTL8761A Bluetooth firmware (rtl_bt/rtl8761a_fw.bin)

• Realtek RTL8821A Bluetooth firmware (rtl_bt/rtl8821a_fw.bin)

• Realtek RTL8192EU Bluetooth firmware (rtl_bt/rtl8192eu_fw.bin)

• Realtek RTL8723AU rev A Bluetooth firmware (rtl_bt/rtl8723a_fw.bin)

• Realtek RTL8723BU rev B Bluetooth firmware (rtl_bt/rtl8723b_fw.bin)

• Realtek RTL8723D Bluetooth config (rtl_bt/rtl8723d_config.bin)

• Realtek RTL8723D Bluetooth firmware (rtl_bt/rtl8723d_fw.bin)

• Realtek RTL8821C Bluetooth config (rtl_bt/rtl8821c_config.bin)

• Realtek RTL8821C Bluetooth firmware (rtl_bt/rtl8821c_fw.bin)

• Realtek RTL8822B Bluetooth config (rtl_bt/rtl8822b_config.bin)

• Realtek RTL8822B Bluetooth firmware (rtl_bt/rtl8822b_fw.bin)

• Realtek RTL8822CU Bluetooth firmware (rtl_bt/rtl8822cu_fw.bin)

This package provides an automated way to track, and then re-run failed RSpec tests.