DANA paper supplementary materials

Overview

DANA Supplements

This repository stores the data, results, and R scripts to generate these reuslts and figures for the corresponding paper Depth Normalization of Small RNA Sequencing: Using Data and Biology to Select a Suitable Method. The DANA package is available on github: https://github.com/LXQin/DANA

DANA is an approach for assessing the performance of normalization for microRNA-Seq data based on biology-motivated and data-driven metrics. Our approach takes advantage of well-known biological features of microRNAs for their expression pattern and polycistronic clustering to assess (1) how effectively normalization removes handling effects and (2) how normalization biases true biological signals. DANA is implemented in R and can be used for assessing any normalization method (under minimal assumptions) for any microRNA-Seq data set and only requires additional information on polycistronic clustering, which is typically readily available.

Installation

This repository is not a package for DANA. It stores the R scripts and data to generate the results and figures in the paper. For simplicity, this package contains a "snapshot" of the DANA implementation as includable R code. This way you don't need to install the DANA package to run the analysis and future updates of the DANA package do not affect the results generated here. You can install the released version of DANA directly from github using devtools.

Dependencies

To run the R code, you need to install the following packages: ggplot2, gridExtra, ggnewscale, corrplot, stargazer, plotly, ggrepel, glmnet, huge, Rcpp, FastGGM, edgeR, DESeq, PoissonSeq, sva, RUVSeq, vsn, DescTools, ffpe. Please make sure to install all dependencies prior to running the code. The code presented here was implemented and tested in R version 4.0.2.

Usage

  1. Download this repository.
  2. Set your R working directory to the root directory of the project.
  3. Run or knit any of the following R markdowns
    • MSK_Data_Analysis.Rmd to generate the DANA results for the paired MSK sarcoma data sets
    • TCGA_UCEC_Data_Analysis.Rmd to generate the DANA results for the single-batch and mixed-batch data sets from the TCGA-UCEC project.
    • TCGA_BRCA_UCS_Data_Analysis.Rmd to generate the DANA results for the combined TCGA-BRCA and TCGA-UCS data set.

All of these markdowns were previously run (so you don't have to) and the resulting knitted html files can be found in the directory docs/

Tree Nested PyTorch Tensor Lib

DI-treetensor treetensor is a generalized tree-based tensor structure mainly developed by OpenDILab Contributors. Almost all the operation can be supp

OpenDILab 167 Dec 29, 2022
Session-aware Item-combination Recommendation with Transformer Network

Session-aware Item-combination Recommendation with Transformer Network 2nd place (0.39224) code and report for IEEE BigData Cup 2021 Track1 Report EDA

Tzu-Heng Lin 6 Mar 10, 2022
Compressed Video Action Recognition

Compressed Video Action Recognition Chao-Yuan Wu, Manzil Zaheer, Hexiang Hu, R. Manmatha, Alexander J. Smola, Philipp Krähenbühl. In CVPR, 2018. [Proj

Chao-Yuan Wu 479 Dec 26, 2022
Multi-task Self-supervised Object Detection via Recycling of Bounding Box Annotations (CVPR, 2019)

Multi-task Self-supervised Object Detection via Recycling of Bounding Box Annotations (CVPR 2019) To make better use of given limited labels, we propo

126 Sep 13, 2022
Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images

Lung Segmentation (2D) Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images. Demo See the application of the

163 Sep 21, 2022
The codes of paper 'Active-LATHE: An Active Learning Algorithm for Boosting the Error exponent for Learning Homogeneous Ising Trees'

Active-LATHE: An Active Learning Algorithm for Boosting the Error exponent for Learning Homogeneous Ising Trees This project contains the codes of pap

0 Apr 20, 2022
Bravia core script for python

Bravia-Core-Script You need to have a mandatory account If this L3 does not work, try another L3. enjoy

5 Dec 26, 2021
Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"

On the Bottleneck of Graph Neural Networks and its Practical Implications This is the official implementation of the paper: On the Bottleneck of Graph

75 Dec 22, 2022
A hobby project which includes a hand-gesture based virtual piano using a mobile phone camera and OpenCV library functions

Overview This is a hobby project which includes a hand-gesture controlled virtual piano using an android phone camera and some OpenCV library. My moti

Abhinav Gupta 1 Nov 19, 2021
Simple Python project using Opencv and datetime package to recognise faces and log attendance data in a csv file.

Attendance-System-based-on-Facial-recognition-Attendance-data-stored-in-csv-file- Simple Python project using Opencv and datetime package to recognise

3 Aug 09, 2022
LBBA-boosted WSOD

LBBA-boosted WSOD Summary Our code is based on ruotianluo/pytorch-faster-rcnn and WSCDN Sincerely thanks for your resources. Newer version of our code

Martin Dong 20 Sep 19, 2022
tf2onnx - Convert TensorFlow, Keras and Tflite models to ONNX.

tf2onnx converts TensorFlow (tf-1.x or tf-2.x), tf.keras and tflite models to ONNX via command line or python api.

Open Neural Network Exchange 1.8k Jan 08, 2023
Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly

Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly Code for this paper Ultra-Data-Efficient GAN Tra

VITA 77 Oct 05, 2022
A collection of resources, problems, explanations and concepts that are/were important during my Data Science journey

Data Science Gurukul List of resources, interview questions, concepts I use for my Data Science work. Topics: Basics of Programming with Python + Unde

Smaranjit Ghose 10 Oct 25, 2022
Using Tensorflow Object Detection API to detect Waymo open dataset

Waymo-2D-Object-Detection Using Tensorflow Object Detection API to detect Waymo open dataset Result CenterNet Training Loss SSD ResNet Training Loss C

76 Dec 12, 2022
OREO: Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning (NeurIPS 2021)

OREO: Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning (NeurIPS 2021) Video demo We here provide a video demo from co

20 Nov 25, 2022
Subnet Replacement Attack: Towards Practical Deployment-Stage Backdoor Attack on Deep Neural Networks

Subnet Replacement Attack: Towards Practical Deployment-Stage Backdoor Attack on Deep Neural Networks Official implementation of paper Towards Practic

Xiangyu Qi 8 Dec 30, 2022
Code release for NeuS

NeuS We present a novel neural surface reconstruction method, called NeuS, for reconstructing objects and scenes with high fidelity from 2D image inpu

Peng Wang 813 Jan 04, 2023
Teaches a student network from the knowledge obtained via training of a larger teacher network

Distilling-the-knowledge-in-neural-network Teaches a student network from the knowledge obtained via training of a larger teacher network This is an i

Abhishek Sinha 146 Dec 11, 2022
Coarse implement of the paper "A Simultaneous Denoising and Dereverberation Framework with Target Decoupling", On DNS-2020 dataset, the DNSMOS of first stage is 3.42 and second stage is 3.47.

SDDNet Coarse implement of the paper "A Simultaneous Denoising and Dereverberation Framework with Target Decoupling", On DNS-2020 dataset, the DNSMOS

Cyril Lv 43 Nov 21, 2022