Raw data outputs 1-18 Raw data output 1. Differentially expressed genes in AML CSCs compared with GTCs as well as in TCGA AML cancer samples compared with normal ones. This data was generated based on the results of AML microarray and TCGA data analysis. Raw data output 2. Commonly and uniquely differentially expressed genes in AML CSC/GTC microarray and TCGA bulk RNA-seq datasets. This data was generated based on the results of AML microarray and TCGA data analysis. Raw data output 3. Common differentially expressed genes between training and test set samples the microarray dataset. This data was generated based on the results of AML microarray data analysis. Raw data output 4. Detailed information on the samples of the breast cancer microarray dataset (GSE52327) used in this study. Raw data output 5. Differentially expressed genes in breast CSCs compared with GTCs as well as in TCGA BRCA cancer samples compared with normal ones. Raw data output 6. Commonly and uniquely differentially expressed genes in breast cancer CSC/GTC microarray and TCGA BRCA bulk RNA-seq datasets. This data was generated based on the results of breast cancer microarray and TCGA BRCA data analysis. CSC, and GTC are abbreviations of cancer stem cell, and general tumor cell, respectively. Raw data output 7. Differential and common co-expression and protein-protein interaction of genes between CSC and GTC samples. This data was generated based on the results of AML microarray and STRING database-based protein-protein interaction data analysis. CSC, and GTC are abbreviations of cancer stem cell, and general tumor cell, respectively. Raw data output 8. Differentially expressed genes between AML dormant and active CSCs. This data was generated based on the results of AML scRNA-seq data analysis. Raw data output 9. Uniquely expressed genes in dormant or active AML CSCs. This data was generated based on the results of AML scRNA-seq data analysis. Raw data output 10. Intersections between the targeting transcription factors of AML key CSC genes and differentially expressed genes between AML CSCs vs GTCs and between dormant and active AML CSCs or the uniquely expressed genes in either class of CSCs. Raw data output 11. Targeting desirableness score of AML key CSC genes and their targeting transcription factors. These scores were generated based on an in-house scoring function described in the Methods section. Raw data output 12. CSC-specific targeting desirableness score of AML key CSC genes and their targeting transcription factors. These scores were generated based on an in-house scoring function described in the Methods section. Raw data output 13. The protein-protein interactions between AML key CSC genes with themselves and their targeting transcription factors. This data was generated based on the results of AML microarray and STRING database-based protein-protein interaction data analysis. Raw data output 14. The previously confirmed associations of genes having the highest targeting desirableness and CSC-specific targeting desirableness scores with AML or other cancers’ (stem) cells as well as hematopoietic stem cells. These data were generated based on a PubMed database-based literature mining. Raw data output 15. Drug score of available drugs and bioactive small molecules targeting AML key CSC genes and/or their targeting transcription factors. These scores were generated based on an in-house scoring function described in the Methods section. Raw data output 16. CSC-specific drug score of available drugs and bioactive small molecules targeting AML key CSC genes and/or their targeting transcription factors. These scores were generated based on an in-house scoring function described in the Methods section. Raw data output 17. Candidate drugs for experimental validation. These drugs were selected based on their respective (CSC-specific) drug scores. CSC is the abbreviation of cancer stem cell. Raw data output 18. Detailed information on the samples of the AML microarray dataset GSE30375 used in this study.

XRD Raw data collected. This dataset is associated with the following publication: Nadagouda , M., C. Han , D. Dionysiou, and L. Wang. An innovative zinc oxide-coated zeolite adsorbent for removal of humic acid. JOURNAL OF HAZARDOUS MATERIALS. Elsevier Science Ltd, New York, NY, USA, 313: 283-290, (2016).

The dataset contains data collected as part of the Ancient Adhesives project under the European Union’s Horizon 2020 research and innovation programme Grant Agreement No. 678 804151 (Grant holder G.H.J.L.).

It is being made public to act as supplementary data for a publication and for other researchers to use this data in their own work.

The data in this dataset were collected at TUDelft, University of Cantabria, and Museum of Prehistory and Archaeology of Cantabria in 2023.

This dataset contains:

1. Raw data for SEM-EDX of 11 archaeological objects named: MOR2; MOR4; MOR9; MOR12; MOR13; MOR17; MOR22; MOR35; MOR42; MOR50: MOR59. The file format is .pdf
2. Raw data for micro-Raman of 6 archaeological objects named MOR2; MOR4; MOR9; MOR13; MOR22; MOR59. Raw-data for micro-Raman of 5 experimentally recreated adhesive samples: pine tar, birch tar, pine resin, beeswax, pine resin+beeswax, Ppine resin+beeswax+hematite. The analysis was performed with 532 and 785 laser lines. The file formats are .txt and .csv
3. Raw data for ATR-FTIR of 7 archaeological objects and 1 sediment sample named: MOR11; MOR38; MOR40a; MOR43; MOR44; MOR46; MOR47; MORSediment. The file format is .csv
4. Raw data for GC-MS of 23 archaeological objects (including sub-samples) and 2 sediment samples named: 230404 MOR 1.1.sirslt; 230404 MOR 5.1.sirslt; 230404 MOR 14.1.sirslt; 230404 MOR 24.1.sirslt; 230404 MOR 26.1.sirslt; 230404 MOR 28.1.sirslt; 230404 MOR 32.1.sirslt; 230404 MOR 43.1.sirslt; 230404 MOR 49.1.sirslt; 230404 MOR 57.1.sirslt; 230404 MOR 58.1.sirslt; 230421 MOR 5a.s.sirslt; 230421 MOR 11.1.sirslt; 230421 MOR 40a.3.sirslt; 230421 MOR 45.1.sirslt; 230421 MOR 47.2.sirslt; 230421 MOR 61.1.sirslt; 230421 MOR62.2.sirslt; 20220718 MOR25_1.sirslt; 20220718 MOR25_2.sirslt; 20220718 MOR38_1.sirslt; 20220718 MOR38_2.sirslt; 20220718 MOR40a_1.sirslt; 20220718 MOR40a_2.sirslt; 20220718 MOR47_1.sirslt; 20230316 MOR_41.1.sirslt; 20230316 MOR_44.1.sirslt; 20230316 MOR_46.1.sirslt; 20230316 MOR_60.1.sirslt; 20231024_MOR_SED 10.sirslt. Each.sirslt file contains the files necessary to open and manipulate the data using the original software Agilent OpenLab 2.5. Within each file there is a .DX file (for opening with Agilent OpenLab 2.5) and accompanying .ACAML, .DX, .MFX, .BIN, .RX, .PMX, and .AMX files. In addition, a .xlsx file (Morin GC-MS results.xlsx) is provided. Each sheet contains the complete GC-MS data exported for samples analyzed as well as the MS data and automated molecular data against the National Institute of Standards and Technology (NIST) library.

The acronym MOR stands for Morín Cave, a cave in Cantabria (Spain) where the objects were found.

The data included in this dataset has been organized per method. For each specimen, more than one point was measured as indicated in the file name. Only the measurements with interpretable results are made available.

The file name includes the unique ID of the object + the analytical technique + the number of the scan. For example: MOR11_ATR_loc1

This imaging mass cytometry (IMC) dataset serves as an example to demonstrate raw data processing and downstream analysis tools. The data was generated as part of the Integrated iMMUnoprofiling of large adaptive CANcer patient cohorts (IMMUcan) project (immucan.eu) using the Hyperion imaging system (www.fluidigm.com/products-services/instruments/hyperion). To get an overview on the technology and available analysis strategies, please visit bodenmillergroup.github.io/IMCWorkflow. The individual data files are described below:

• Patient1.zip, Patient2.zip, Patient3.zip, Patient4.zip: raw data files of 4 patient samples. Each .zip archive contains a folder in which one .mcd file (IMC raw data) and multiple .txt files (one per acquisition) can be found.
• compensation.zip: This .zip archive holds a folder which contains one .mcd file and multiple .txt files. Multiple spots of a "spillover slide" were acquired and each .txt file is named based on the spotted metal. This data is used for channel spillover correction. For more information, please refer to the original publication: Compensation of Signal Spillover in Suspension and Imaging Mass Cytometry
• panel.csv: This file contains metadata for each antibody/channel used in the experiment. The full column indicates which channel should be analysed. The ilastik column specifies which channels were used for ilastik pixel classification and the deepcell column indicates the channels used for deepcell segmentation.
• sample_metadata.csv: This file links each patient to their cancer type (SCCHN - head and neck cancer; BCC - breast cancer; NSCLC - lung cancer; CRC - colorectal cancer).

Here you can find raw data and information about each of the 34 datasets generated by the mulset algorithm and used for further analysis in SIMON.
Each dataset is stored in separate folder which contains 4 files:

json_info: This file contains, number of features with their names and number of subjects that are available for the same dataset
data_testing: data frame with data used to test trained model
data_training: data frame with data used to train models
results: direct unfiltered data from database

Files are written in feather format. Here is an example of data structure for each file in repository.

File was compressed using 7-Zip available at https://www.7-zip.org/.

Sample 1 was used for Exploratory Factor Analysis, Sample 2 was used for Confirmatory Factor Analysis.

Raw data for liquid chromatography coupled with mass spectrometry (LC-MS) experiments along with skyline template used to extract peak area from raw data.

Raw data from HDMSe and SWATH MS analyses of 309 prostate cancer serum samples. Prostate cancer cohort:
309 patients were divided into control (n=112), prostate cancer (PCa) (n=175), and benign prostate hyperplasia (BPH) (n=22). PCa patients were then subdivided into active surveillance (AS) (n=51) or treatment group. Treatments were radiotherapy (pre: n=26, post: n=14), hormone therapy (pre: n=7, post: n=8), prostatectomy (pre: n=21, post: n=8), and radiotherapy (pre: n=23, post: n=17)

These data (illumina paired end fastq) exemplify the different WGS types which have been isolated from UK

This file contains raw data for cameras and wearables of the ConfLab dataset.

./cameras

contains the overhead video recordings for 9 cameras (cam2-10) in MP4 files.

These cameras cover the whole interaction floor, with camera 2 capturing the

bottom of the scene layout, and camera 10 capturing top of the scene layout.

Note that cam5 ran out of battery before the other cameras and thus the recordings

are cut short. However, cam4 and 6 contain significant overlap with cam 5, to

reconstruct any information needed.

Note that the annotations are made and provided in 2 minute segments.

The annotated portions of the video include the last 3min38sec of x2xxx.MP4

video files, and the first 12 min of x3xxx.MP4 files for cameras (2,4,6,8,10),

with "x" being the placeholder character in the mp4 file names. If one wishes

to separate the video into 2 min segments as we did, the "video-splitting.sh"

script is provided.

./camera-calibration contains the camera instrinsic files obtained from

https://github.com/idiap/multicamera-calibration. Camera extrinsic parameters can

be calculated using the existing intrinsic parameters and the instructions in the

multicamera-calibration repo. The coordinates in the image are provided by the

crosses marked on the floor, which are visible in the video recordings.

The crosses are 1m apart (=100cm).

./wearables

subdirectory includes the IMU, proximity and audio data from each

participant at the Conflab event (48 in total). In the directory numbered

by participant ID, the following data are included:

1. raw audio file

2. proximity (bluetooth) pings (RSSI) file (raw and csv) and a visualization

3. Tri-axial accelerometer data (raw and csv) and a visualization

4. Tri-axial gyroscope data (raw and csv) and a visualization

5. Tri-axial magnetometer data (raw and csv) and a visualization

6. Game rotation vector (raw and csv), recorded in quaternions.

All files are timestamped.

The sampling frequencies are:

- audio: 1250 Hz

- rest: around 50Hz. However, the sample rate is not fixed

and instead the timestamps should be used.

For rotation, the game rotation vector's output frequency is limited by the

actual sampling frequency of the magnetometer. For more information, please refer to

https://invensense.tdk.com/wp-content/uploads/2016/06/DS-000189-ICM-20948-v1.3.pdf

Audio files in this folder are in raw binary form. The following can be used to convert

them to WAV files (1250Hz):

ffmpeg -f s16le -ar 1250 -ac 1 -i /path/to/audio/file

Synchronization of cameras and werables data

Raw videos contain timecode information which matches the timestamps of the data in

the "wearables" folder. The starting timecode of a video can be read as:

ffprobe -hide_banner -show_streams -i /path/to/video

./audio

./sync: contains wav files per each subject

./sync_files: auxiliary csv files used to sync the audio. Can be used to improve the synchronization.

The code used for syncing the audio can be found here:

https://github.com/TUDelft-SPC-Lab/conflab/tree/master/preprocessing/audio

This document mainly includes Coding sequences of PME-domain and pro-region of Type-1 PME in representative plants,Raw data from fusion gene analysis by LIR inference,Raw data from repeated sequence studies within four Cruciferae representative species and Graphical Abstract.

Overview In support of the Wind Forecasting Improvement Project, Pacific Northwest National Laboratory (PNNL) deployed surface meteorological stations in Oregon. Data Details A PNNL computer is used as the base station to download the meteorological data acquired by the data logger at each site via a cellular modem. The data collected will be made available to the National Oceanic and Atmospheric Administration each hour and used to support the short-term forecasting project by providing an independent evaluation of the added value of new data to meteorological forecasts. Each meteorological station consists of a solar-powered data acquisition system and wind speed, wind direction, temperature, humidity, barometric pressure, and solar radiation sensors on a 3-m tower. Specifically, the stations are comprised of the following instruments and equipment: Campbell Scientific CM6 Tripod Campbell Scientific CR10X Measurement and Control System R.M. Young 05106 Wind Monitor Vaisala HMP45C Temperature and Humidity Probe Vaisala PTB101B Barometric Pressure Sensor Li-Cor LI200X Pyranometer RavenXT Cellular Modem The data logger is used to sample, at 1-second intervals, the horizontal wind speed and direction at 3 meters above ground level (AGL); the air temperature, relative humidity, barometric pressure, and solar radiation at 2 meters AGL; and the logger temperature and power supply. The logger outputs the 1-minute averages of these measurements to final storage and power on the cellular modem, so the data can be retrieved and downloaded to a base station computer. The data are archived as 1-hour comma-delimited ASCII files (see "Table 2. Format of the WFIP2 Comma-delimited ASCII Data Files" in wfip2-met-data.pdf). All dates and times in the file names and data records are in UTC and denote the end of the 1-minute average. Data Quality Data for each primary measurement at every site are automatically plotted daily and reviewed about every three days. Instrument outages or events are reported with the Instrument and Model Data Problem Log at: .

This entry contains raw data files from experiments performed on the Vulcan beamline at the Spallation Neutron Source at Oak Ridge National Laboratory using a pressure cell. Cylindrical granite and marble samples were subjected to confining pressures of either 0 psi or approximately 2500 psi and internal pressures of either 0 psi, 1500 psi or 2500 psi through a blind axial hole at the center of one end of the sample. The sample diameters were 1.5" and the sample lengths were 6". The blind hole was 0.25" in diameter and 3" deep. One set of experiments measured strains at points located circumferentially around the center of the sample with identical radii to determine if there was strain variability (this would not be expected for a homogeneous material based on the symmetry of loading). Another set of experiments measured load variation across the radius of the sample at a fixed axial and circumferential location. Raw neutron diffraction intensity files and experimental parameter descriptions are included.

Raw LC-MS (liquid chromatography-mass spectrometry) data for photocatalyst 1 (PC1). Data acquired on a Waters Acquity UPLC + Xevo G2-XS (LC-MS/MS). Sample in Water:Acetonitrile 95:5.

Raw data on sample languages

This repository contains all original code for the system control, image reconstruction and image registration for the MLS-SIM system. The example raw data was generated by the MLS-SIM imaging system on awake head-fixed mice. No further processing was involved. For detailed information, please refer to the published literature related to this data.

Dataset comprising raw paired RNA-seq data in fastq.gz format for 7 samples of rosette forming brain tumors

The dataset contains data collected as part of the Ancient Adhesives project under the European Union’s Horizon 2020 research and innovation programme Grant Agreement No. 678 804151 (Grant holder G.H.J.L.).

It is being made public to act as supplementary data for a publication and for other researchers to use this data in their own work.

The data in this dataset were collected at TUDelft in 2022 and 2023.

This dataset contains:

-Raw data of XRD of 11 archaeological objects named: SBF4; SBF5; SBF9; SBF10; SBF14; SBF15; SBF17; SBF20; SBF21; SBF23; SBF24. The filfe format is .raw

-Raw data of FTIR of 6 archaeological objects named SBF4; SBF9; SBF10; SBF20; SBF21; SBF24. The file format is .csv

-Raw data of ATR-FTIR of 1 archaeological object named SBF14. The file format is .csv

The acronym SBF stands for Steenbokfontein, a cave in the Western Cape province (South Africa) where the objects were found.

The data included in this dataset has been organized per specimen. For each specimen, more than one point was measured as indicated in the file name.

The file name includes the unique ID of the object + the analytical technique + the number of the scan (at least 2 per object). For example: SBF14_ATR_scan01

The ont-open-data registry provides reference sequencing data from Oxford Nanopore Technologies to support, 1) Exploration of the characteristics of nanopore sequence data. 2) Assessment and reproduction of performance benchmarks 3) Development of tools and methods. The data deposited showcases DNA sequences from a representative subset of sequencing chemistries. The datasets correspond to publicly-available reference samples (e.g. Genome In A Bottle reference cell lines). Raw data are provided with metadata and scripts to describe sample and data provenance.

This data set includes the raw data and the posterior samples from the Bayesian models referring to the article, Seeing Both the Forest and the Trees Distinct Resolution of Hierarchical Representations in Visual Working Memory