As the number of samples handled simultaneously increases, the time until the RNA is protected can increase. Therefore, to isolate RNA that accurately reflects the transcriptome at the point of harvest, raw biological samples should be processed by freezing in liquid nitrogen, immersing in RNA stabilization reagent or lysing and homogenizing in RNA lysis buffer containing guanidine thiocyanate as soon as possible. In the case of RNA sequencing (RNA-Seq), which reveals the presence and quantity of RNA in a biological sample at any moment, it is necessary to consider that gene expression responds over a short time interval (several seconds to a few minutes) in many organisms. The lack of experimental metadata associated with the data makes reuse and understanding data quality very difficult. Large volumes of high-throughput sequencing data have been submitted to the Sequencing Read Archive (SRA). Importance of experimental information (metadata) for archived sequence data: case of specific gene bias due to lag time between sample harvest and RNA protection in RNA sequencing. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. InfoDict.strip()] = line.Nihon BioData Corporation, Kawasaki, Kanagawa, Japan DOI 10.7717/peerj.11875 Published Accepted Received Academic Editor Michael Olson Subject Areas Bioinformatics, Cell Biology Keywords High-throughput sequencing, RNA-Seq, Sample harvest, RNA protection, Metadata, Database, Working time, Processing lag time, RNA isolation Copyright © 2021 Matsuda Licence This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. Stdout=subprocess.PIPE, stderr=subprocess.STDOUT, It can give metadata for most of the file formats but gives less information than Exif tool. Similar to exif tool, it is also a command line tool except that it's a python packageĪnd user can install it using pip install hachoir. However the drawback of using this method is it doesn't works with all the images. Refer any of the other post for this method. Thumbnail Image : (Binary data 5448 bytes, use -b option to extract) Interoperability Index : R98 - DCF basic file (sRGB)Įncoding Process : Baseline DCT, Huffman coding InfoDict.strip()] = line.strip()įull Tag list is here: """ ExifTool Version Number : 11.63ĭirectory : /Projects/ImageMetaData/ImagesĮxif Byte Order : Little-endian (Intel, II)Ĭanon Firmware Version : Firmware Version 1.10 Process = subprocess.Popen(,stdout=subprocess.PIPE, stderr=subprocess.STDOUT,universal_newlines=True) ''' use Exif tool to get the metadata '''
( infoDict = #Creating the dict to get the metadata tagsĮxifToolPath = 'D:/ExifTool/exifTool.exe' #for Windows user have to specify the Exif tool exe path for metadata extraction. Please refer the below code snippet to get the meta data using exif tool. It is a command line tool and to use it in Python user have to create a subprocess and pass the tool and image file path as an argument. This is recommended approach to get the meta data as it gives more tags than any other way. You can now run ExifTool anywhere in your terminal by typing exiftool. You can install ExifTool on Ubuntu using the apt utility There is couple of ways by which you can get the data from the file.
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